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Gujral K, Van Campen J, Jacobs J, Lo J, Kimerling R, Blonigen DM, Wagner TH, Zulman DM. Sociodemographic Differences in the Impacts of Video-Enabled Tablets on Psychotherapy Usage Among Veterans. Psychiatr Serv 2024; 75:434-443. [PMID: 38088041 DOI: 10.1176/appi.ps.20230134] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/02/2024]
Abstract
OBJECTIVE To examine potential health disparities due to a broad reliance on telehealth during the COVID-19 pandemic, the authors studied the impact of video-enabled tablets provided by the U.S. Department of Veterans Affairs (VA) on psychotherapy usage among rural versus urban, Black versus White, and female versus male veterans. METHODS Psychotherapy usage trends before and after onset of the COVID-19 pandemic were examined among veterans with at least one mental health visit in 2019 (63,764 tablet recipients and 1,414,636 nonrecipients). Adjusted difference-in-differences and event study analyses were conducted to compare psychotherapy usage among tablet recipients and nonrecipients (March 15, 2020-December 31, 2021) 10 months before and after tablet issuance. Analyses were stratified by rurality, sex, and race. RESULTS Adjusted analyses demonstrated that tablet receipt was associated with increases in psychotherapy visit frequency in every patient group studied (rural, 27.4%; urban, 24.6%; women, 30.5%; men, 24.4%; Black, 20.8%; White, 28.1%), compared with visits before tablet receipt. Compared with men, women had statistically significant tablet-associated psychotherapy visit increases (video visits, 1.2 per year; all modalities, 1.0 per year). CONCLUSIONS VA-issued tablets led to increased psychotherapy usage for all groups examined, with similar increases found for rural versus urban and Black versus White veterans and higher increases for women versus men. Eliminating barriers to Internet access or device ownership may improve mental health care access among underserved or historically disadvantaged populations. VA's tablet program offers insights to inform policy makers' and health systems' efforts to bridge the digital divide.
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Affiliation(s)
- Kritee Gujral
- Center for Innovation to Implementation (Gujral, Van Campen, Jacobs, Kimerling, Blonigen, Zulman), Health Economics Resource Center (Gujral, Jacobs, Lo, Wagner), and National Center for Posttraumatic Stress Disorder (Kimerling), U.S. Department of Veterans Affairs (VA) Palo Alto Health Care System, Palo Alto, California; Department of Psychiatry and Behavioral Sciences (Blonigen), Department of Surgery (Wagner), and Department of Medicine (Zulman), Stanford University School of Medicine, Stanford
| | - James Van Campen
- Center for Innovation to Implementation (Gujral, Van Campen, Jacobs, Kimerling, Blonigen, Zulman), Health Economics Resource Center (Gujral, Jacobs, Lo, Wagner), and National Center for Posttraumatic Stress Disorder (Kimerling), U.S. Department of Veterans Affairs (VA) Palo Alto Health Care System, Palo Alto, California; Department of Psychiatry and Behavioral Sciences (Blonigen), Department of Surgery (Wagner), and Department of Medicine (Zulman), Stanford University School of Medicine, Stanford
| | - Josephine Jacobs
- Center for Innovation to Implementation (Gujral, Van Campen, Jacobs, Kimerling, Blonigen, Zulman), Health Economics Resource Center (Gujral, Jacobs, Lo, Wagner), and National Center for Posttraumatic Stress Disorder (Kimerling), U.S. Department of Veterans Affairs (VA) Palo Alto Health Care System, Palo Alto, California; Department of Psychiatry and Behavioral Sciences (Blonigen), Department of Surgery (Wagner), and Department of Medicine (Zulman), Stanford University School of Medicine, Stanford
| | - Jeanie Lo
- Center for Innovation to Implementation (Gujral, Van Campen, Jacobs, Kimerling, Blonigen, Zulman), Health Economics Resource Center (Gujral, Jacobs, Lo, Wagner), and National Center for Posttraumatic Stress Disorder (Kimerling), U.S. Department of Veterans Affairs (VA) Palo Alto Health Care System, Palo Alto, California; Department of Psychiatry and Behavioral Sciences (Blonigen), Department of Surgery (Wagner), and Department of Medicine (Zulman), Stanford University School of Medicine, Stanford
| | - Rachel Kimerling
- Center for Innovation to Implementation (Gujral, Van Campen, Jacobs, Kimerling, Blonigen, Zulman), Health Economics Resource Center (Gujral, Jacobs, Lo, Wagner), and National Center for Posttraumatic Stress Disorder (Kimerling), U.S. Department of Veterans Affairs (VA) Palo Alto Health Care System, Palo Alto, California; Department of Psychiatry and Behavioral Sciences (Blonigen), Department of Surgery (Wagner), and Department of Medicine (Zulman), Stanford University School of Medicine, Stanford
| | - Daniel M Blonigen
- Center for Innovation to Implementation (Gujral, Van Campen, Jacobs, Kimerling, Blonigen, Zulman), Health Economics Resource Center (Gujral, Jacobs, Lo, Wagner), and National Center for Posttraumatic Stress Disorder (Kimerling), U.S. Department of Veterans Affairs (VA) Palo Alto Health Care System, Palo Alto, California; Department of Psychiatry and Behavioral Sciences (Blonigen), Department of Surgery (Wagner), and Department of Medicine (Zulman), Stanford University School of Medicine, Stanford
| | - Todd H Wagner
- Center for Innovation to Implementation (Gujral, Van Campen, Jacobs, Kimerling, Blonigen, Zulman), Health Economics Resource Center (Gujral, Jacobs, Lo, Wagner), and National Center for Posttraumatic Stress Disorder (Kimerling), U.S. Department of Veterans Affairs (VA) Palo Alto Health Care System, Palo Alto, California; Department of Psychiatry and Behavioral Sciences (Blonigen), Department of Surgery (Wagner), and Department of Medicine (Zulman), Stanford University School of Medicine, Stanford
| | - Donna M Zulman
- Center for Innovation to Implementation (Gujral, Van Campen, Jacobs, Kimerling, Blonigen, Zulman), Health Economics Resource Center (Gujral, Jacobs, Lo, Wagner), and National Center for Posttraumatic Stress Disorder (Kimerling), U.S. Department of Veterans Affairs (VA) Palo Alto Health Care System, Palo Alto, California; Department of Psychiatry and Behavioral Sciences (Blonigen), Department of Surgery (Wagner), and Department of Medicine (Zulman), Stanford University School of Medicine, Stanford
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Graham LA, Illarmo S, Gray CP, Harris AHS, Wagner TH, Hawn MT, Iannuzzi JC, Wren SM. Mapping the Discharge Process After Surgery. JAMA Surg 2024; 159:438-444. [PMID: 38381415 PMCID: PMC10882508 DOI: 10.1001/jamasurg.2023.7539] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Accepted: 10/28/2023] [Indexed: 02/22/2024]
Abstract
Importance Care transition models are structured approaches used to ensure the smooth transfer of patients between health care settings or levels of care, but none currently are tailored to the surgical patient. Tailoring care transition models to the unique needs of surgical patients may lead to significant improvements in surgical outcomes and reduced care fragmentation. The first step to developing surgical care transition models is to understand the surgical discharge process. Objective To map the surgical discharge process in a sample of US hospitals and identify key components and potential challenges specific to a patient's discharge after surgery. Design, Setting, and Participants This qualitative study followed a cognitive task analysis framework conducted between January 1, 2022, and April 1, 2023, in Veterans Health Administration (VHA) hospitals. Observations (n = 16) of discharge from inpatient care after a surgical procedure were conducted in 2 separate VHA surgical units. Interviews (n = 13) were conducted among VHA health care professionals nationwide. Exposure Postoperative hospital discharge. Main Outcomes and Measures Data were coded according to the principles of thematic analysis, and a swim lane process map was developed to represent the study findings. Results At the hospitals in this study, the discharge process observed for a surgical patient involved multidisciplinary coordination across the surgery team, nursing team, case managers, dieticians, social services, occupational and physical therapy, and pharmacy. Important components for a surgical discharge that were not incorporated in the current care transition models included wound care education and supplies; pain control; approvals for nonhome postdischarge locations; and follow-up plans for wounds, ostomies, tubes, and drains at discharge. Potential challenges to the surgical discharge process included social situations (eg, home environment and caregiver availability), team communication issues, and postdischarge care coordination. Conclusions and Relevance These findings suggest that current and ongoing studies of discharge care transitions for a patient after surgery should consider pain control; wounds, ostomies, tubes, and drains; and the impact of challenging social situations and interdisciplinary team coordination on discharge success.
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Affiliation(s)
- Laura A. Graham
- Health Economics Resource Center, VA Palo Alto Health Care System, Menlo Park, California
- Stanford-Surgery Policy Improvement Research and Education Center (S-SPIRE), Department of Surgery, Stanford University, Stanford, California
- Center for Innovation to Implementation, VA Palo Alto Health Care System, Menlo Park, California
| | - Samantha Illarmo
- Health Economics Resource Center, VA Palo Alto Health Care System, Menlo Park, California
| | - Caroline P. Gray
- Center for Innovation to Implementation, VA Palo Alto Health Care System, Menlo Park, California
| | - Alex H. S. Harris
- Stanford-Surgery Policy Improvement Research and Education Center (S-SPIRE), Department of Surgery, Stanford University, Stanford, California
- Center for Innovation to Implementation, VA Palo Alto Health Care System, Menlo Park, California
| | - Todd H. Wagner
- Health Economics Resource Center, VA Palo Alto Health Care System, Menlo Park, California
- Stanford-Surgery Policy Improvement Research and Education Center (S-SPIRE), Department of Surgery, Stanford University, Stanford, California
| | - Mary T. Hawn
- Department of General Surgery, VA Palo Alto Health Care System, Menlo Park, California
- Department of Surgery, Stanford University, Stanford, California
| | - James C. Iannuzzi
- Department of Surgery, San Francisco VA Medical Center, San Francisco, California
- Division of Vascular Surgery, Department of Surgery, University of California, San Francisco
| | - Sherry M. Wren
- Department of General Surgery, VA Palo Alto Health Care System, Menlo Park, California
- Department of Surgery, Stanford University, Stanford, California
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Jacobs JC, Lo J, Van Houtven CH, Wagner TH. The impact of informal caregiving on U.S. Veterans Health Administration utilization and expenditures. Soc Sci Med 2024; 344:116625. [PMID: 38324974 DOI: 10.1016/j.socscimed.2024.116625] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2023] [Revised: 01/10/2024] [Accepted: 01/19/2024] [Indexed: 02/09/2024]
Abstract
Few studies have examined the effect of informal care receipt on health care utilization and expenditures while accounting for the potentially endogenous relationship between informal and formal care, and none have examined these relationships for U.S. Veterans. With rapidly increasing investments in caregiver supports over the past decade, including stipends for caregivers, the U.S. Department of Veterans Affairs (VA) needs to better understand the costs and benefits of informal care provision. Using a unique data linkage between the 1998-2010 Health and Retirement Study and VA administrative data (n = 2083 Veterans with 9511 person-wave observations), we applied instrumental variable techniques to understand the effect of care from an adult child on Veterans' two-year VA utilization and expenditures. We found that informal care decreased overall utilization by 53 percentage points (p < 0.001) and expenditures by $19,977 (p < 0.01). These reductions can be explained by informal care decreasing the probability of inpatient utilization by 17 percentage points (p < 0.001), outpatient utilization by 57 percentage points (p < 0.001), and institutional long-term care by 3 percentage points (p < 0.05). There were no changes in the probability of non-institutional long-term care use, though these expenditures decreased by $882 (p < 0.05). Expenditure decreases were greatest amongst medically complex patients. Our results indicate relative alignment between VA's stipend payments, which are based on replacement cost methods, and the monetary benefits derived through VA cost avoidances due to informal care. For health systems considering similar caregiver stipend payments, our findings suggest that the cost of these programs may be offset by informal care substituting for formal care, particularly for higher need patients.
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Affiliation(s)
- Josephine C Jacobs
- Health Economics Resource Center, VA Palo Alto Health Care System, Menlo Park CA, USA; Department of Health Policy, Stanford University School of Medicine, Stanford, CA, USA.
| | - Jeanie Lo
- Health Economics Resource Center, VA Palo Alto Health Care System, Menlo Park CA, USA
| | - Courtney H Van Houtven
- Durham Center of Innovation to Accelerate Discovery and Practice Transformation, Durham VA Medical Center, Durham, NC, USA; Department of Population Health Sciences, Duke University, Durham, NC, USA; Duke-Margolis Center for Health Policy, Duke University, Durham, NC, USA
| | - Todd H Wagner
- Health Economics Resource Center, VA Palo Alto Health Care System, Menlo Park CA, USA; Department of Surgery, Stanford University School of Medicine, Palo Alto, CA, USA
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Rochlin DH, Rizk NM, Matros E, Wagner TH, Sheckter CC. Negotiated Rates for Surgical Cancer Care in the Era of Price Transparency-Prices Reflect Market Competition. Ann Surg 2024; 279:385-391. [PMID: 37678179 PMCID: PMC10840891 DOI: 10.1097/sla.0000000000006091] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/09/2023]
Abstract
OBJECTIVE To measure commercial price variation for cancer surgery within and across hospitals. BACKGROUND Surgical care for solid-organ tumors is costly, and negotiated commercial rates have been hidden from public view. The Hospital Price Transparency Rule, enacted in 2021, requires all hospitals to list their negotiated rates on their website, thus opening the door for an examination of pricing for cancer surgery. METHODS This was a cross-sectional study using 2021 negotiated price data disclosed by US hospitals for the 10 most common cancers treated with surgery. Price variation was measured using within-hospital and across-hospital ratios. Commercial rates relative to cancer center designation and the Herfindahl-Hirschman Index at the facility level were evaluated with mixed effects linear regression with random intercepts per procedural code. RESULTS In all, 495,200 unique commercial rates from 2232 hospitals resulted for the 10 most common solid-organ tumor cancers. Gynecologic cancer operations had the highest median rates at $6035.8/operation compared with bladder cancer surgery at $3431.0/operation. Compared with competitive markets, moderately and highly concentrated markets were associated with significantly higher rates (HHI 1501, 2500, coefficient $513.6, 95% CI, $295.5, $731.7; HHI >2500, coefficient $1115.5, 95% CI, $913.7, $1317.2). National Cancer Institute designation was associated with higher rates, coefficient $3,451.9 (95% CI, $2853.2, $4050.7). CONCLUSIONS Commercial payer-negotiated prices for the surgical management of 10 common, solid tumor malignancies varied widely both within and across hospitals. Higher rates were observed in less competitive markets. Future efforts should facilitate price competition and limit health market concentration.
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Affiliation(s)
- Danielle H. Rochlin
- Plastic and Reconstructive Surgery Service, Department of Surgery, Memorial Sloan Kettering Cancer Center
| | - Nada M. Rizk
- Division of Plastic and Reconstructive Surgery, Stanford University Medical Center
| | - Evan Matros
- Plastic and Reconstructive Surgery Service, Department of Surgery, Memorial Sloan Kettering Cancer Center
| | | | - Clifford C. Sheckter
- Division of Plastic and Reconstructive Surgery, Stanford University Medical Center
- S-SPIRE. Department of Surgery, Stanford University
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Dawes AJ, Rajasekar G, Arnow KD, Trickey AW, Harris AHS, Morris AM, Wagner TH. Disparities in Access, Quality, and Clinical Outcome for Latino Californians with Colon Cancer. Ann Surg 2024:00000658-990000000-00797. [PMID: 38407273 DOI: 10.1097/sla.0000000000006251] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
OBJECTIVE To compare access, quality, and clinical outcomes between Latino and non-Latino White Californians with colon cancer. SUMMARY BACKGROUND DATA Racial and ethnic disparities in cancer care remain understudied, particularly among patients who identify as Latino. Exploring potential mechanisms, including differential utilization of high-volume hospitals, is an essential first step to designing evidence-based policy solutions. METHODS We identified all adults diagnosed with colon cancer between January 1, 2010 and December 31, 2020 from a statewide cancer registry linked to hospital administrative records. We compared survival, access (stage at diagnosis, receipt of surgical care, treatment at a high-volume hospital), and quality of care (receipt of adjuvant chemotherapy, adequacy of lymph node resection) between patients who identified as Latino and as non-Latino White. RESULTS 75,543 patients met inclusion criteria, including 16,071 patients who identified as Latino (21.3%). Latino patients were significantly less likely to undergo definitive surgical resection (marginal difference [MD] -0.72 percentage points, 95% CI -1.19,-0.26), have an operation in a timely fashion (MD -3.24 percentage points, 95% CI -4.16,-2.32), or have an adequate lymphadenectomy (MD -2.85 percentage points, 95% CI -3.59,-2.12) even after adjustment for clinical and sociodemographic factors. Latino patients treated at high-volume hospitals were significantly less likely to die and more likely to meet access and quality metrics. CONCLUSIONS Latino colon cancer patients experienced delays, segregation, and lower receipt of recommended care. Hospital-level colectomy volume appears to be strongly associated with access, quality, and survival--especially for patients who identify as Latino--suggesting that directing at-risk cancer patients to high-volume hospitals may improve health equity.
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Affiliation(s)
- Aaron J Dawes
- Section of Colon & Rectal Surgery, Department of Surgery, Stanford University School of Medicine, Stanford, CA
- Stanford-Surgery Policy Improvement Research and Education Center, Stanford, CA
| | - Ganesh Rajasekar
- Stanford-Surgery Policy Improvement Research and Education Center, Stanford, CA
| | - Katherine D Arnow
- Stanford-Surgery Policy Improvement Research and Education Center, Stanford, CA
| | - Amber W Trickey
- Stanford-Surgery Policy Improvement Research and Education Center, Stanford, CA
| | - Alex H S Harris
- Stanford-Surgery Policy Improvement Research and Education Center, Stanford, CA
- Center for Innovation to Implementation, VA Palo Alto Healthcare System, Palo Alto, CA
| | - Arden M Morris
- Section of Colon & Rectal Surgery, Department of Surgery, Stanford University School of Medicine, Stanford, CA
- Stanford-Surgery Policy Improvement Research and Education Center, Stanford, CA
| | - Todd H Wagner
- Stanford-Surgery Policy Improvement Research and Education Center, Stanford, CA
- Health Economics Resource Center, VA Palo Alto Health Care System, Menlo Park, CA
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Knowlton LM, Logan DS, Arnow K, Hendricks WD, Gibson AB, Tran LD, Wagner TH, Morris AM. Do hospital-based emergency Medicaid programs benefit trauma centers? A mixed-methods analysis. J Trauma Acute Care Surg 2024; 96:44-53. [PMID: 37828656 PMCID: PMC10841404 DOI: 10.1097/ta.0000000000004162] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/14/2023]
Abstract
INTRODUCTION Hospital Presumptive Eligibility (HPE) is a temporary Medicaid insurance at hospitalization, which can offset patient costs of care, increase access to postdischarge resources, and provide a path to sustain coverage through Medicaid. Less is known about the implications of HPE programs on trauma centers (TCs). We aimed to describe the association with HPE and hospital Medicaid reimbursement and characterize incentives for HPE participation among hospitals and TCs. We hypothesized that there would be financial, operational, and mission-based incentives. METHODS We performed a convergent mixed methods study of HPE hospitals in California (including all verified TCs). We analyzed Annual Financial Disclosure Reports from California's Department of Health Care Access and Information (2005-2021). Our primary outcome was Medicaid net revenue. We also conducted thematic analysis of semistructured interviews with hospital stakeholders to understand incentives for HPE participation (n = 8). RESULTS Among 367 California hospitals analyzed, 285 (77.7%) participate in HPE, 77 (21%) of which are TCs. As of early 2015, 100% of TCs had elected to enroll in HPE. There is a significant positive association between HPE participation and net Medicaid revenue. The highest Medicaid revenues are in HPE level I and level II TCs. Controlling for changes associated with the Affordable Care Act, HPE enrollment is associated with increased net patient Medicaid revenue ( b = 6.74, p < 0.001) and decreased uncompensated care costs ( b = -2.22, p < 0.05). Stakeholder interviewees' explanatory incentives for HPE participation included reduction of hospital bad debt, improved patient satisfaction, and community benefit in access to care. CONCLUSION Hospital Presumptive Eligibility programs not only are a promising pathway for long-term insurance coverage for trauma patients but also play a role in TC viability. Future interventions will target streamlining the HPE Medicaid enrollment process to reduce resource burden on participating hospitals and ensure ongoing patient engagement in the program. LEVEL OF EVIDENCE Economic And Value Based Evaluations; Level II.
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Affiliation(s)
- Lisa Marie Knowlton
- Stanford-Surgery Policy Improvement Research and Education Center (S-SPIRE)
- Department of Surgery, Stanford University School of Medicine, Stanford, CA
| | - Daniel S. Logan
- Stanford-Surgery Policy Improvement Research and Education Center (S-SPIRE)
| | - Katherine Arnow
- Stanford-Surgery Policy Improvement Research and Education Center (S-SPIRE)
| | | | | | - Linda D. Tran
- Stanford-Surgery Policy Improvement Research and Education Center (S-SPIRE)
| | - Todd H. Wagner
- Stanford-Surgery Policy Improvement Research and Education Center (S-SPIRE)
| | - Arden M. Morris
- Stanford-Surgery Policy Improvement Research and Education Center (S-SPIRE)
- Department of Surgery, Stanford University School of Medicine, Stanford, CA
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Wagner TH, Carrandi A. The Practical Realities of Local-Level Economic Evaluations: Toward Informed Decision Making in Health Care. MDM Policy Pract 2024; 9:23814683241247151. [PMID: 38638864 PMCID: PMC11025424 DOI: 10.1177/23814683241247151] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Accepted: 02/10/2024] [Indexed: 04/20/2024] Open
Affiliation(s)
- Todd H. Wagner
- VA Palo Alto Health Economics Resource Center, Stanford-Surgery Policy Improvement Research and Education Center (S-SPIRE), Stanford, CA, USA
| | - Alayna Carrandi
- Australian and New Zealand Intensive Care Research Centre, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
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Joyce VR, Oliva EM, Garcia CC, Trafton J, Asch SM, Wagner TH, Humphreys K, Owens DK, Bounthavong M. Healthcare costs and use before and after opioid overdose in Veterans Health Administration patients with opioid use disorder. Addiction 2023; 118:2203-2214. [PMID: 37465971 DOI: 10.1111/add.16289] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Accepted: 06/09/2023] [Indexed: 07/20/2023]
Abstract
AIMS To compare healthcare costs and use between United States (US) Veterans Health Administration (VHA) patients with opioid use disorder (OUD) who experienced an opioid overdose (OD cohort) and patients with OUD who did not experience an opioid overdose (non-OD cohort). DESIGN This is a retrospective cohort study of administrative and clinical data. SETTING The largest integrated national health-care system is the US Veterans Health Administration's healthcare systems. PARTICIPANTS We included VHA patients diagnosed with OUD from October 1, 2017 through September 30, 2018. We identified the index date of overdose for patients who had an overdose. Our control group, which included patients with OUD who did not have an overdose, was randomly assigned an index date. A total of 66 513 patients with OUD were included for analysis (OD cohort: n = 1413; non-OD cohort: n = 65 100). MEASUREMENTS Monthly adjusted healthcare-related costs and use in the year before and after the index date. We used generalized estimating equation models to compare patients with an opioid overdose and controls in a difference-in-differences framework. FINDINGS Compared with the non-OD cohort, an opioid overdose was associated with an increase of $16 890 [95% confidence interval (CI) = $15 611-18 169; P < 0.001] in healthcare costs for an estimated $23.9 million in direct costs to VHA (95% CI = $22.1 million, $25.7 million) within the 30 days following overdose after adjusting for baseline characteristics. Inpatient costs ($13 515; 95% CI = $12 378-14 652; P < 0.001) reflected most of this increase. Inpatient days (+6.15 days; 95% CI, = 5.33-6.97; P < 0.001), inpatient admissions (+1.01 admissions; 95% CI = 0.93-1.10; P < 0.001) and outpatient visits (+1.59 visits; 95% CI = 1.34-1.84; P < 0.001) also increased in the month after opioid overdose. Within the overdose cohort, healthcare costs and use remained higher in the year after overdose compared with pre-overdose trends. CONCLUSIONS The US Veterans Health Administration patients with opioid use disorder (OUD) who have experienced an opioid overdose have increased healthcare costs and use that remain significantly higher in the month and continuing through the year after overdose than OUD patients who have not experienced an overdose.
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Affiliation(s)
- Vilija R Joyce
- VA Health Economics Resource Center, US Department of Veterans Affairs, VA Palo Alto Health Care System, Palo Alto, CA, USA
| | - Elizabeth M Oliva
- VA Center for Innovation to Implementation, US Department of Veterans Affairs, VA Palo Alto Health Care System, Palo Alto, CA, USA
| | - Carla C Garcia
- VA Health Economics Resource Center, US Department of Veterans Affairs, VA Palo Alto Health Care System, Palo Alto, CA, USA
| | - Jodie Trafton
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
- VA Program Evaluation and Resource Center, Office of Mental Health and Suicide Prevention, VA Central Office, US Department of Veterans Affairs, Palo Alto, CA, USA
| | - Steven M Asch
- VA Center for Innovation to Implementation, US Department of Veterans Affairs, VA Palo Alto Health Care System, Palo Alto, CA, USA
- Department of Medicine, Stanford University, Stanford, CA, USA
| | - Todd H Wagner
- VA Health Economics Resource Center, US Department of Veterans Affairs, VA Palo Alto Health Care System, Palo Alto, CA, USA
| | - Keith Humphreys
- VA Center for Innovation to Implementation, US Department of Veterans Affairs, VA Palo Alto Health Care System, Palo Alto, CA, USA
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Douglas K Owens
- Stanford Health Policy, Department of Health Policy, Stanford University, Stanford, CA, USA
| | - Mark Bounthavong
- VA Health Economics Resource Center, US Department of Veterans Affairs, VA Palo Alto Health Care System, Palo Alto, CA, USA
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Gibson AB, Hendricks WD, Arnow K, Tran LD, Wagner TH, Knowlton LM. State-Level Variability in Hospital Presumptive Eligibility Programs. JAMA Netw Open 2023; 6:e2345244. [PMID: 38015508 PMCID: PMC10685880 DOI: 10.1001/jamanetworkopen.2023.45244] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Accepted: 10/17/2023] [Indexed: 11/29/2023] Open
Abstract
This cross-sectional study examines state-level variability in hospital presumptive eligibility programs to understand discrepancies in access by Medicaid expansion status.
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Affiliation(s)
- Alexander B. Gibson
- Stanford-Surgery Policy Improvement Research and Education Center (S-SPIRE), Stanford, California
| | - Wesley D. Hendricks
- Stanford-Surgery Policy Improvement Research and Education Center (S-SPIRE), Stanford, California
| | - Katherine Arnow
- Stanford-Surgery Policy Improvement Research and Education Center (S-SPIRE), Stanford, California
| | - Linda D. Tran
- Stanford-Surgery Policy Improvement Research and Education Center (S-SPIRE), Stanford, California
| | - Todd H. Wagner
- Stanford-Surgery Policy Improvement Research and Education Center (S-SPIRE), Stanford, California
| | - Lisa Marie Knowlton
- Stanford-Surgery Policy Improvement Research and Education Center (S-SPIRE), Stanford, California
- Section of Trauma, Surgical Critical Care and Acute Care Surgery, Stanford University School of Medicine, Stanford, California
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Sheckter CC, Rochlin DH, Rubenstein R, Shamsunder MG, Morris AM, Wagner TH, Matros E. Association of High-Deductible Health Plans and Time to Surgery for Breast and Colon Cancer. J Am Coll Surg 2023; 237:473-482. [PMID: 38085770 DOI: 10.1097/xcs.0000000000000737] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
BACKGROUND High-deductible health plans (HDHPs) have been shown to delay timing of breast and colon cancer screening, although the relationship to the timing of cancer surgery is unknown. The objective of this study was to characterize timing of surgery for breast and colon cancer patients undergoing cancer operations following routine screening. STUDY DESIGN Data from the IBM MarketScan Commercial Claims Database from 2007 to 2016 were queried to identify patients who underwent screening mammogram and/or colonoscopy. The calendar quarters of screening and surgery were analyzed with ordinal logistic regression. The time from screening to surgery (time to surgery, TTS) was evaluated using a Cox proportional hazard function. RESULTS Among 32,562,751 patients who had screening mammograms, 0.7% underwent breast cancer surgery within the following year. Among 9,325,238 patients who had screening colonoscopies, 0.9% were followed by colon cancer surgery within a year. The odds of screening (OR 1.146 for mammogram, 1.272 for colonoscopy; p < 0.001) and surgery (OR 1.120 for breast surgery, 1.219 for colon surgery; p < 0.001) increased each quarter for HDHPs compared to low-deductible health plans. Enrollment in an HDHP was not associated with a difference in TTS. Screening in Q3 or Q4 was associated with shorter TTS compared to screening in Q1 (hazard ratio 1.061 and 1.046, respectively; p < 0.001). CONCLUSIONS HDHPs were associated with delays in screening and surgery. However, HDHPs were not associated with delays in TTS. Interventions to improve cancer care outcomes in the HDHP population should concentrate on reducing barriers to timely screening.
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Affiliation(s)
- Clifford C Sheckter
- From the Division of Plastic and Reconstructive Surgery (Sheckter), Department of Surgery, Stanford University School of Medicine, Palo Alto, California
- S-SPIRE Center (Sheckter, Morris, Wagner), Department of Surgery, Stanford University School of Medicine, Palo Alto, California
| | - Danielle H Rochlin
- the Plastic and Reconstructive Surgery Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York (Rochlin, Rubenstein, Shamsunder, Matros)
| | - Robyn Rubenstein
- the Plastic and Reconstructive Surgery Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York (Rochlin, Rubenstein, Shamsunder, Matros)
| | - Meghana G Shamsunder
- the Plastic and Reconstructive Surgery Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York (Rochlin, Rubenstein, Shamsunder, Matros)
| | - Arden M Morris
- S-SPIRE Center (Sheckter, Morris, Wagner), Department of Surgery, Stanford University School of Medicine, Palo Alto, California
| | - Todd H Wagner
- S-SPIRE Center (Sheckter, Morris, Wagner), Department of Surgery, Stanford University School of Medicine, Palo Alto, California
| | - Evan Matros
- the Plastic and Reconstructive Surgery Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York (Rochlin, Rubenstein, Shamsunder, Matros)
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Richerson JT, Wagner TH, Abrams T, Skelton K, Biswas K, Illarmo S, McSherry F, Fallon MT, Frakt A, Pizer S, Magruder KM, Groer S, Dorn PA, Huang GD, Stock EM. Therapeutic and Economic Benefits of Service Dogs Versus Emotional Support Dogs for Veterans With PTSD. Psychiatr Serv 2023; 74:790-800. [PMID: 36718602 DOI: 10.1176/appi.ps.20220138] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
OBJECTIVE This work aimed to assess the therapeutic and economic benefits of service dogs versus emotional support dogs for veterans with posttraumatic stress disorder (PTSD). METHODS Veterans with PTSD (N=227) participating in a multicenter trial were randomly assigned to receive a service or emotional support dog; 181 veterans received a dog and were followed up for 18 months. Primary outcomes included overall functioning (assessed with World Health Organization Disability Assessment Scale II [WHODAS 2.0]) and quality of life (Veterans RAND 12-Item Health Survey [VR-12]). Secondary outcomes included PTSD symptoms (PTSD Checklist for DSM-5), suicidal ideation, depression, sleep quality, health care costs and utilization, medication adherence, employment, and productivity. RESULTS Participants paired with a dog had a mean±SD age of 50.6±13.6 years (range 22-79), and most were male (80%), White (66%), and non-Hispanic (91%). Adjusted linear mixed repeated-measures models indicated no difference between the two groups on WHODAS 2.0 or VR-12 scores. Participants with service dogs had a 3.7-point greater reduction in PTSD symptoms versus participants with emotional support dogs (p=0.036). No reduced health care utilization or cost was associated with receiving a service dog. Veterans with service dogs had an increase of 10 percentage points in antidepressant adherence compared with those with emotional support dogs (p<0.01). CONCLUSIONS Both groups appeared to benefit from having a service or emotional support dog. No significant differences in improved functioning or quality of life were observed between the groups. Those in the service dog group had a greater reduction in PTSD symptoms and better antidepressant adherence, improvements that should be explored further.
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Affiliation(s)
- Joan T Richerson
- U.S. Department of Veterans Affairs (VA) Tennessee Valley Health Care System, Nashville (Richerson); VA Health Economics Resource Center, Palo Alto Health Care System, Menlo Park, California (Wagner, Illarmo); Center for Access Delivery Research and Evaluation, VA Iowa City Healthcare System, and Department of Internal Medicine, Carver College of Medicine, University of Iowa, Iowa City (Abrams); Atlanta VA Medical Center, Atlanta (Skelton, Fallon); Perry Point/Baltimore Coordinating Center, Cooperative Studies Program, Office of Research and Development, VA, Perry Point, Maryland (Biswas, McSherry, Stock); Partnered Evidence-Based Policy Resource Center, Research and Development, VA Boston Healthcare System, and Department of Health Law, Policy and Management, School of Public Health, Boston University, Boston (Frakt, Pizer); Department of Psychiatry and Behavioral Sciences, Military Sciences Division, and Department of Public Health Sciences, Division of Epidemiology, Medical University of South Carolina, Charleston (Magruder); VA Office of Research and Development, Washington, D.C. (Groer, Dorn, Huang)
| | - Todd H Wagner
- U.S. Department of Veterans Affairs (VA) Tennessee Valley Health Care System, Nashville (Richerson); VA Health Economics Resource Center, Palo Alto Health Care System, Menlo Park, California (Wagner, Illarmo); Center for Access Delivery Research and Evaluation, VA Iowa City Healthcare System, and Department of Internal Medicine, Carver College of Medicine, University of Iowa, Iowa City (Abrams); Atlanta VA Medical Center, Atlanta (Skelton, Fallon); Perry Point/Baltimore Coordinating Center, Cooperative Studies Program, Office of Research and Development, VA, Perry Point, Maryland (Biswas, McSherry, Stock); Partnered Evidence-Based Policy Resource Center, Research and Development, VA Boston Healthcare System, and Department of Health Law, Policy and Management, School of Public Health, Boston University, Boston (Frakt, Pizer); Department of Psychiatry and Behavioral Sciences, Military Sciences Division, and Department of Public Health Sciences, Division of Epidemiology, Medical University of South Carolina, Charleston (Magruder); VA Office of Research and Development, Washington, D.C. (Groer, Dorn, Huang)
| | - Thad Abrams
- U.S. Department of Veterans Affairs (VA) Tennessee Valley Health Care System, Nashville (Richerson); VA Health Economics Resource Center, Palo Alto Health Care System, Menlo Park, California (Wagner, Illarmo); Center for Access Delivery Research and Evaluation, VA Iowa City Healthcare System, and Department of Internal Medicine, Carver College of Medicine, University of Iowa, Iowa City (Abrams); Atlanta VA Medical Center, Atlanta (Skelton, Fallon); Perry Point/Baltimore Coordinating Center, Cooperative Studies Program, Office of Research and Development, VA, Perry Point, Maryland (Biswas, McSherry, Stock); Partnered Evidence-Based Policy Resource Center, Research and Development, VA Boston Healthcare System, and Department of Health Law, Policy and Management, School of Public Health, Boston University, Boston (Frakt, Pizer); Department of Psychiatry and Behavioral Sciences, Military Sciences Division, and Department of Public Health Sciences, Division of Epidemiology, Medical University of South Carolina, Charleston (Magruder); VA Office of Research and Development, Washington, D.C. (Groer, Dorn, Huang)
| | - Kelly Skelton
- U.S. Department of Veterans Affairs (VA) Tennessee Valley Health Care System, Nashville (Richerson); VA Health Economics Resource Center, Palo Alto Health Care System, Menlo Park, California (Wagner, Illarmo); Center for Access Delivery Research and Evaluation, VA Iowa City Healthcare System, and Department of Internal Medicine, Carver College of Medicine, University of Iowa, Iowa City (Abrams); Atlanta VA Medical Center, Atlanta (Skelton, Fallon); Perry Point/Baltimore Coordinating Center, Cooperative Studies Program, Office of Research and Development, VA, Perry Point, Maryland (Biswas, McSherry, Stock); Partnered Evidence-Based Policy Resource Center, Research and Development, VA Boston Healthcare System, and Department of Health Law, Policy and Management, School of Public Health, Boston University, Boston (Frakt, Pizer); Department of Psychiatry and Behavioral Sciences, Military Sciences Division, and Department of Public Health Sciences, Division of Epidemiology, Medical University of South Carolina, Charleston (Magruder); VA Office of Research and Development, Washington, D.C. (Groer, Dorn, Huang)
| | - Kousick Biswas
- U.S. Department of Veterans Affairs (VA) Tennessee Valley Health Care System, Nashville (Richerson); VA Health Economics Resource Center, Palo Alto Health Care System, Menlo Park, California (Wagner, Illarmo); Center for Access Delivery Research and Evaluation, VA Iowa City Healthcare System, and Department of Internal Medicine, Carver College of Medicine, University of Iowa, Iowa City (Abrams); Atlanta VA Medical Center, Atlanta (Skelton, Fallon); Perry Point/Baltimore Coordinating Center, Cooperative Studies Program, Office of Research and Development, VA, Perry Point, Maryland (Biswas, McSherry, Stock); Partnered Evidence-Based Policy Resource Center, Research and Development, VA Boston Healthcare System, and Department of Health Law, Policy and Management, School of Public Health, Boston University, Boston (Frakt, Pizer); Department of Psychiatry and Behavioral Sciences, Military Sciences Division, and Department of Public Health Sciences, Division of Epidemiology, Medical University of South Carolina, Charleston (Magruder); VA Office of Research and Development, Washington, D.C. (Groer, Dorn, Huang)
| | - Samantha Illarmo
- U.S. Department of Veterans Affairs (VA) Tennessee Valley Health Care System, Nashville (Richerson); VA Health Economics Resource Center, Palo Alto Health Care System, Menlo Park, California (Wagner, Illarmo); Center for Access Delivery Research and Evaluation, VA Iowa City Healthcare System, and Department of Internal Medicine, Carver College of Medicine, University of Iowa, Iowa City (Abrams); Atlanta VA Medical Center, Atlanta (Skelton, Fallon); Perry Point/Baltimore Coordinating Center, Cooperative Studies Program, Office of Research and Development, VA, Perry Point, Maryland (Biswas, McSherry, Stock); Partnered Evidence-Based Policy Resource Center, Research and Development, VA Boston Healthcare System, and Department of Health Law, Policy and Management, School of Public Health, Boston University, Boston (Frakt, Pizer); Department of Psychiatry and Behavioral Sciences, Military Sciences Division, and Department of Public Health Sciences, Division of Epidemiology, Medical University of South Carolina, Charleston (Magruder); VA Office of Research and Development, Washington, D.C. (Groer, Dorn, Huang)
| | - Frances McSherry
- U.S. Department of Veterans Affairs (VA) Tennessee Valley Health Care System, Nashville (Richerson); VA Health Economics Resource Center, Palo Alto Health Care System, Menlo Park, California (Wagner, Illarmo); Center for Access Delivery Research and Evaluation, VA Iowa City Healthcare System, and Department of Internal Medicine, Carver College of Medicine, University of Iowa, Iowa City (Abrams); Atlanta VA Medical Center, Atlanta (Skelton, Fallon); Perry Point/Baltimore Coordinating Center, Cooperative Studies Program, Office of Research and Development, VA, Perry Point, Maryland (Biswas, McSherry, Stock); Partnered Evidence-Based Policy Resource Center, Research and Development, VA Boston Healthcare System, and Department of Health Law, Policy and Management, School of Public Health, Boston University, Boston (Frakt, Pizer); Department of Psychiatry and Behavioral Sciences, Military Sciences Division, and Department of Public Health Sciences, Division of Epidemiology, Medical University of South Carolina, Charleston (Magruder); VA Office of Research and Development, Washington, D.C. (Groer, Dorn, Huang)
| | - Michael T Fallon
- U.S. Department of Veterans Affairs (VA) Tennessee Valley Health Care System, Nashville (Richerson); VA Health Economics Resource Center, Palo Alto Health Care System, Menlo Park, California (Wagner, Illarmo); Center for Access Delivery Research and Evaluation, VA Iowa City Healthcare System, and Department of Internal Medicine, Carver College of Medicine, University of Iowa, Iowa City (Abrams); Atlanta VA Medical Center, Atlanta (Skelton, Fallon); Perry Point/Baltimore Coordinating Center, Cooperative Studies Program, Office of Research and Development, VA, Perry Point, Maryland (Biswas, McSherry, Stock); Partnered Evidence-Based Policy Resource Center, Research and Development, VA Boston Healthcare System, and Department of Health Law, Policy and Management, School of Public Health, Boston University, Boston (Frakt, Pizer); Department of Psychiatry and Behavioral Sciences, Military Sciences Division, and Department of Public Health Sciences, Division of Epidemiology, Medical University of South Carolina, Charleston (Magruder); VA Office of Research and Development, Washington, D.C. (Groer, Dorn, Huang)
| | - Austin Frakt
- U.S. Department of Veterans Affairs (VA) Tennessee Valley Health Care System, Nashville (Richerson); VA Health Economics Resource Center, Palo Alto Health Care System, Menlo Park, California (Wagner, Illarmo); Center for Access Delivery Research and Evaluation, VA Iowa City Healthcare System, and Department of Internal Medicine, Carver College of Medicine, University of Iowa, Iowa City (Abrams); Atlanta VA Medical Center, Atlanta (Skelton, Fallon); Perry Point/Baltimore Coordinating Center, Cooperative Studies Program, Office of Research and Development, VA, Perry Point, Maryland (Biswas, McSherry, Stock); Partnered Evidence-Based Policy Resource Center, Research and Development, VA Boston Healthcare System, and Department of Health Law, Policy and Management, School of Public Health, Boston University, Boston (Frakt, Pizer); Department of Psychiatry and Behavioral Sciences, Military Sciences Division, and Department of Public Health Sciences, Division of Epidemiology, Medical University of South Carolina, Charleston (Magruder); VA Office of Research and Development, Washington, D.C. (Groer, Dorn, Huang)
| | - Steven Pizer
- U.S. Department of Veterans Affairs (VA) Tennessee Valley Health Care System, Nashville (Richerson); VA Health Economics Resource Center, Palo Alto Health Care System, Menlo Park, California (Wagner, Illarmo); Center for Access Delivery Research and Evaluation, VA Iowa City Healthcare System, and Department of Internal Medicine, Carver College of Medicine, University of Iowa, Iowa City (Abrams); Atlanta VA Medical Center, Atlanta (Skelton, Fallon); Perry Point/Baltimore Coordinating Center, Cooperative Studies Program, Office of Research and Development, VA, Perry Point, Maryland (Biswas, McSherry, Stock); Partnered Evidence-Based Policy Resource Center, Research and Development, VA Boston Healthcare System, and Department of Health Law, Policy and Management, School of Public Health, Boston University, Boston (Frakt, Pizer); Department of Psychiatry and Behavioral Sciences, Military Sciences Division, and Department of Public Health Sciences, Division of Epidemiology, Medical University of South Carolina, Charleston (Magruder); VA Office of Research and Development, Washington, D.C. (Groer, Dorn, Huang)
| | - Kathryn M Magruder
- U.S. Department of Veterans Affairs (VA) Tennessee Valley Health Care System, Nashville (Richerson); VA Health Economics Resource Center, Palo Alto Health Care System, Menlo Park, California (Wagner, Illarmo); Center for Access Delivery Research and Evaluation, VA Iowa City Healthcare System, and Department of Internal Medicine, Carver College of Medicine, University of Iowa, Iowa City (Abrams); Atlanta VA Medical Center, Atlanta (Skelton, Fallon); Perry Point/Baltimore Coordinating Center, Cooperative Studies Program, Office of Research and Development, VA, Perry Point, Maryland (Biswas, McSherry, Stock); Partnered Evidence-Based Policy Resource Center, Research and Development, VA Boston Healthcare System, and Department of Health Law, Policy and Management, School of Public Health, Boston University, Boston (Frakt, Pizer); Department of Psychiatry and Behavioral Sciences, Military Sciences Division, and Department of Public Health Sciences, Division of Epidemiology, Medical University of South Carolina, Charleston (Magruder); VA Office of Research and Development, Washington, D.C. (Groer, Dorn, Huang)
| | - Shirley Groer
- U.S. Department of Veterans Affairs (VA) Tennessee Valley Health Care System, Nashville (Richerson); VA Health Economics Resource Center, Palo Alto Health Care System, Menlo Park, California (Wagner, Illarmo); Center for Access Delivery Research and Evaluation, VA Iowa City Healthcare System, and Department of Internal Medicine, Carver College of Medicine, University of Iowa, Iowa City (Abrams); Atlanta VA Medical Center, Atlanta (Skelton, Fallon); Perry Point/Baltimore Coordinating Center, Cooperative Studies Program, Office of Research and Development, VA, Perry Point, Maryland (Biswas, McSherry, Stock); Partnered Evidence-Based Policy Resource Center, Research and Development, VA Boston Healthcare System, and Department of Health Law, Policy and Management, School of Public Health, Boston University, Boston (Frakt, Pizer); Department of Psychiatry and Behavioral Sciences, Military Sciences Division, and Department of Public Health Sciences, Division of Epidemiology, Medical University of South Carolina, Charleston (Magruder); VA Office of Research and Development, Washington, D.C. (Groer, Dorn, Huang)
| | - Patricia A Dorn
- U.S. Department of Veterans Affairs (VA) Tennessee Valley Health Care System, Nashville (Richerson); VA Health Economics Resource Center, Palo Alto Health Care System, Menlo Park, California (Wagner, Illarmo); Center for Access Delivery Research and Evaluation, VA Iowa City Healthcare System, and Department of Internal Medicine, Carver College of Medicine, University of Iowa, Iowa City (Abrams); Atlanta VA Medical Center, Atlanta (Skelton, Fallon); Perry Point/Baltimore Coordinating Center, Cooperative Studies Program, Office of Research and Development, VA, Perry Point, Maryland (Biswas, McSherry, Stock); Partnered Evidence-Based Policy Resource Center, Research and Development, VA Boston Healthcare System, and Department of Health Law, Policy and Management, School of Public Health, Boston University, Boston (Frakt, Pizer); Department of Psychiatry and Behavioral Sciences, Military Sciences Division, and Department of Public Health Sciences, Division of Epidemiology, Medical University of South Carolina, Charleston (Magruder); VA Office of Research and Development, Washington, D.C. (Groer, Dorn, Huang)
| | - Grant D Huang
- U.S. Department of Veterans Affairs (VA) Tennessee Valley Health Care System, Nashville (Richerson); VA Health Economics Resource Center, Palo Alto Health Care System, Menlo Park, California (Wagner, Illarmo); Center for Access Delivery Research and Evaluation, VA Iowa City Healthcare System, and Department of Internal Medicine, Carver College of Medicine, University of Iowa, Iowa City (Abrams); Atlanta VA Medical Center, Atlanta (Skelton, Fallon); Perry Point/Baltimore Coordinating Center, Cooperative Studies Program, Office of Research and Development, VA, Perry Point, Maryland (Biswas, McSherry, Stock); Partnered Evidence-Based Policy Resource Center, Research and Development, VA Boston Healthcare System, and Department of Health Law, Policy and Management, School of Public Health, Boston University, Boston (Frakt, Pizer); Department of Psychiatry and Behavioral Sciences, Military Sciences Division, and Department of Public Health Sciences, Division of Epidemiology, Medical University of South Carolina, Charleston (Magruder); VA Office of Research and Development, Washington, D.C. (Groer, Dorn, Huang)
| | - Eileen M Stock
- U.S. Department of Veterans Affairs (VA) Tennessee Valley Health Care System, Nashville (Richerson); VA Health Economics Resource Center, Palo Alto Health Care System, Menlo Park, California (Wagner, Illarmo); Center for Access Delivery Research and Evaluation, VA Iowa City Healthcare System, and Department of Internal Medicine, Carver College of Medicine, University of Iowa, Iowa City (Abrams); Atlanta VA Medical Center, Atlanta (Skelton, Fallon); Perry Point/Baltimore Coordinating Center, Cooperative Studies Program, Office of Research and Development, VA, Perry Point, Maryland (Biswas, McSherry, Stock); Partnered Evidence-Based Policy Resource Center, Research and Development, VA Boston Healthcare System, and Department of Health Law, Policy and Management, School of Public Health, Boston University, Boston (Frakt, Pizer); Department of Psychiatry and Behavioral Sciences, Military Sciences Division, and Department of Public Health Sciences, Division of Epidemiology, Medical University of South Carolina, Charleston (Magruder); VA Office of Research and Development, Washington, D.C. (Groer, Dorn, Huang)
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12
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Rose L, Schmidt A, Gehlert E, Graham LA, Aouad M, Wagner TH. Association Between Self-Reported Health and Reliance on Veterans Affairs for Health Care Among Veterans Affairs Enrollees. JAMA Netw Open 2023; 6:e2323884. [PMID: 37459100 PMCID: PMC10352854 DOI: 10.1001/jamanetworkopen.2023.23884] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Accepted: 06/02/2023] [Indexed: 07/20/2023] Open
Abstract
This cross-sectional study using survey data investigates the association between level of reliance on the Department of Veterans Affairs for health care and self-reported health by type of insurance coverage among VA enrollees.
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Affiliation(s)
- Liam Rose
- Health Economics Resource Center, VA Palo Alto Health Care System, Menlo Park, California
- Stanford Surgery Policy Improvement and Education Center, Stanford Medicine, Stanford, California
| | - Anna Schmidt
- Health Economics Resource Center, VA Palo Alto Health Care System, Menlo Park, California
| | - Elizabeth Gehlert
- Health Economics Resource Center, VA Palo Alto Health Care System, Menlo Park, California
| | - Laura A. Graham
- Health Economics Resource Center, VA Palo Alto Health Care System, Menlo Park, California
- Stanford Surgery Policy Improvement and Education Center, Stanford Medicine, Stanford, California
| | - Marion Aouad
- Department of Economics, University of California, Irvine
| | - Todd H. Wagner
- Health Economics Resource Center, VA Palo Alto Health Care System, Menlo Park, California
- Stanford Surgery Policy Improvement and Education Center, Stanford Medicine, Stanford, California
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Donovan LM, Hoyos CM, Kimoff RJ, Morrell MJ, Bosch NA, Chooljian DM, McEvoy RD, Sawyer AM, Wagner TH, Al-Lamee RR, Bishop D, Carno MA, Epstein M, Hanson M, Ip MSM, Létourneau M, Pamidi S, Patel SR, Pépin JL, Punjabi NM, Redline S, Thornton JD, Patil SP. Strategies to Assess the Effect of Continuous Positive Airway Pressure on Long-Term Clinically Important Outcomes among Patients with Symptomatic Obstructive Sleep Apnea: An Official American Thoracic Society Workshop Report. Ann Am Thorac Soc 2023; 20:931-943. [PMID: 37387624 DOI: 10.1513/annalsats.202303-258st] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/01/2023] Open
Abstract
Continuous positive airway pressure (CPAP) is the first-line treatment for obstructive sleep apnea (OSA). Although CPAP improves symptoms (e.g., daytime sleepiness), there is a lack of high-quality evidence that CPAP prevents many long-term outcomes, including cognitive impairment, myocardial infarction, and stroke. Observational studies suggest that patients with symptoms may be particularly likely to experience these preventive benefits with CPAP, but ethical and practical concerns limited the participation of such patients in prior long-term randomized trials. As a result, there is uncertainty about the full benefits of CPAP, and resolving this uncertainty is a key priority for the field. This workshop assembled clinicians, researchers, ethicists, and patients to identify strategies to understand the causal effects of CPAP on long-term clinically important outcomes among patients with symptomatic OSA. Quasi-experimental designs can provide valuable information and are less time and resource intensive than trials. Under specific conditions and assumptions, quasi-experimental studies may be able to provide causal estimates of CPAP's effectiveness from generalizable observational cohorts. However, randomized trials represent the most reliable approach to understanding the causal effects of CPAP among patients with symptoms. Randomized trials of CPAP can ethically include patients with symptomatic OSA, as long as there is outcome-specific equipoise, adequate informed consent, and a plan to maximize safety while minimizing harm (e.g., monitoring for pathologic sleepiness). Furthermore, multiple strategies exist to ensure the generalizability and practicality of future randomized trials of CPAP. These strategies include reducing the burden of trial procedures, improving patient-centeredness, and engaging historically excluded and underserved populations.
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Richerson JT, Wagner TH. Service Dogs for Veterans With PTSD. Psychiatr Serv 2023; 74:668-669. [PMID: 37259586 DOI: 10.1176/appi.ps.20230164] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Key Words] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/02/2023]
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Graham LA, Gray C, Wagner TH, Illarmo S, Hawn MT, Wren SM, Iannuzzi J, Harris AHS. Applying cognitive task analysis to health services research. Health Serv Res 2023; 58:415-422. [PMID: 36421922 PMCID: PMC10012243 DOI: 10.1111/1475-6773.14106] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
Abstract
OBJECTIVE Designing practical decision support tools and other health care technology in health services research relies on a clear understanding of the cognitive processes that underlie the use of these tools. Unfortunately, methods to explore cognitive processes are rarely used in health services research. Thus, the objective of this manuscript is to introduce cognitive task analysis (CTA), a family of methods to study cognitive processes involved in completing a task, to a health services research audience. This methods article describes CTA procedures, proposes a framework for their use in health services research studies, and provides an example of its application in a pilot study. DATA SOURCES AND STUDY SETTING Observations and interviews of health care providers involved in discharge planning at six hospitals in the Veterans Health Administration. STUDY DESIGN Qualitative study of discharge planning using CTA. DATA COLLECTION/EXTRACTION METHODS Data were collected from structured observations and semi-structured interviews using the Critical Decision Method and analyzed using thematic analysis. PRINCIPAL FINDINGS We developed an adaptation of CTA that could be used in a clinical environment to describe clinical decision-making and other cognitive processes. The adapted CTA framework guides the user through four steps: (1) Planning, (2) Environmental Analysis, (3) Knowledge Elicitation, and (4) Analyses and Results. This adapted CTA framework provides an iterative and systematic approach to identifying and describing the knowledge, expertise, thought processes, procedures, actors, goals, and mental strategies that underlie completing a clinical task. CONCLUSIONS A better understanding of the cognitive processes that underly clinical tasks is key to developing health care technology and decision-support tools that will have a meaningful impact on processes of care and patient outcomes. Our adapted framework offers a more rigorous and detailed method for identifying task-related cognitive processes in implementation studies and quality improvement. Our adaptation of this underutilized qualitative research method may be helpful to other researchers and inform future research in health services research.
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Affiliation(s)
- Laura A. Graham
- Health Economics Resource Center, VA Palo Alto Health Care SystemMenlo ParkCaliforniaUSA
- Department of SurgeryStanford‐Surgery Policy Improvement Research and Education Center (S‐SPIRE), Stanford UniversityStanfordCaliforniaUSA
| | - Caroline Gray
- Center for Innovation to Implementation, VA Palo Alto Health Care SystemPalo AltoCaliforniaUSA
| | - Todd H. Wagner
- Health Economics Resource Center, VA Palo Alto Health Care SystemMenlo ParkCaliforniaUSA
- Department of SurgeryStanford‐Surgery Policy Improvement Research and Education Center (S‐SPIRE), Stanford UniversityStanfordCaliforniaUSA
| | - Samantha Illarmo
- Health Economics Resource Center, VA Palo Alto Health Care SystemMenlo ParkCaliforniaUSA
| | - Mary T. Hawn
- Department of General SurgeryVA Palo Alto Health Care SystemPalo AltoCaliforniaUSA
- Department of SurgeryStanford UniversityStanfordCaliforniaUSA
| | - Sherry M. Wren
- Department of General SurgeryVA Palo Alto Health Care SystemPalo AltoCaliforniaUSA
- Department of SurgeryStanford UniversityStanfordCaliforniaUSA
| | - James Iannuzzi
- Department of SurgerySan Francisco Veterans Affairs Healthcare SystemSan FranciscoCaliforniaUSA
- Division of Vascular Surgery, Department of SurgeryUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Alex H. S. Harris
- Department of SurgeryStanford‐Surgery Policy Improvement Research and Education Center (S‐SPIRE), Stanford UniversityStanfordCaliforniaUSA
- Center for Innovation to Implementation, VA Palo Alto Health Care SystemPalo AltoCaliforniaUSA
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Ferguson JM, Wray CM, Jacobs J, Greene L, Wagner TH, Odden MC, Freese J, Van Campen J, Asch SM, Heyworth L, Zulman DM. Variation in initial and continued use of primary, mental health, and specialty video care among Veterans. Health Serv Res 2023; 58:402-414. [PMID: 36345235 PMCID: PMC10012228 DOI: 10.1111/1475-6773.14098] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
OBJECTIVE To identify which Veteran populations are routinely accessing video-based care. DATA SOURCES AND STUDY SETTING National, secondary administrative data from electronic health records at the Veterans Health Administration (VHA), 2019-2021. STUDY DESIGN This retrospective cohort analysis identified patient characteristics associated with the odds of using any video care; and then, among those with a previous video visit, the annual rate of video care utilization. Video care use was reported overall and stratified into care type (e.g., primary, mental health, and specialty video care) between March 10, 2020 and February 28, 2021. DATA COLLECTION Veterans active in VA health care (>1 outpatient visit between March 11, 2019 and March 10, 2020) were included in this study. PRINCIPAL FINDINGS Among 5,389,129 Veterans in this evaluation, approximately 27.4% of Veterans had at least one video visit. We found differences in video care utilization by type of video care: 14.7% of Veterans had at least one primary care video visit, 10.6% a mental health video visit, and 5.9% a specialty care video visit. Veterans with a history of housing instability had a higher overall rate of video care driven by their higher usage of video for mental health care compared with Veterans in stable housing. American Indian/Alaska Native Veterans had reduced odds of video visits, yet similar rates of video care when compared to White Veterans. Low-income Veterans had lower odds of using primary video care yet slightly elevated rates of primary video care among those with at least one video visit when compared to Veterans enrolled at VA without special considerations. CONCLUSIONS Variation in video care utilization patterns by type of care identified Veteran populations that might require greater resources and support to initiate and sustain video care use. Our data support service specific outreach to homeless and American Indian/Alaska Native Veterans.
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Affiliation(s)
- Jacqueline M. Ferguson
- Center for Innovation to ImplementationVeterans Affairs Palo Alto Health Care SystemMenlo ParkCaliforniaUSA
- Division of Primary Care and Population HealthStanford University School of MedicineStanfordCaliforniaUSA
| | - Charlie M. Wray
- Department of MedicineUniversity of California San FranciscoSan FranciscoCaliforniaUSA
- Section of Hospital MedicineVeterans Affairs San Francisco Health Care SystemSan FranciscoCaliforniaUSA
| | - Josephine Jacobs
- Health Economics Resource CenterVeterans Affairs Palo Alto Health Care SystemMenlo ParkCaliforniaUSA
| | - Liberty Greene
- Center for Innovation to ImplementationVeterans Affairs Palo Alto Health Care SystemMenlo ParkCaliforniaUSA
- Division of Primary Care and Population HealthStanford University School of MedicineStanfordCaliforniaUSA
| | - Todd H. Wagner
- Center for Innovation to ImplementationVeterans Affairs Palo Alto Health Care SystemMenlo ParkCaliforniaUSA
- Health Economics Resource CenterVeterans Affairs Palo Alto Health Care SystemMenlo ParkCaliforniaUSA
| | - Michelle C. Odden
- Geriatric Research, Education, and Clinical CenterVeterans Affairs Palo Alto Health Care SystemPalo AltoCaliforniaUSA
- Department of Epidemiology and Population HealthStanford University School of MedicineStanfordCaliforniaUSA
| | - Jeremy Freese
- Department of SociologyStanford UniversityStanfordCaliforniaUSA
| | - James Van Campen
- Center for Innovation to ImplementationVeterans Affairs Palo Alto Health Care SystemMenlo ParkCaliforniaUSA
| | - Steven M. Asch
- Center for Innovation to ImplementationVeterans Affairs Palo Alto Health Care SystemMenlo ParkCaliforniaUSA
- Division of Primary Care and Population HealthStanford University School of MedicineStanfordCaliforniaUSA
| | - Leonie Heyworth
- Office of Connected Care/TelehealthDepartment of Veterans Affairs Central OfficeWashingtonDCUSA
- Department of MedicineUniversity of California, San Diego School of MedicineSan DiegoCaliforniaUSA
| | - Donna M. Zulman
- Center for Innovation to ImplementationVeterans Affairs Palo Alto Health Care SystemMenlo ParkCaliforniaUSA
- Division of Primary Care and Population HealthStanford University School of MedicineStanfordCaliforniaUSA
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Abstract
Importance Breast reconstruction is costly, and negotiated commercial rates have been hidden from public view. The Hospital Price Transparency Rule was enacted in 2021 to facilitate market competition and lower health care costs. Breast reconstruction pricing should be analyzed to evaluate for market effectiveness and opportunities to lower the cost of health care. Objective To evaluate the extent of commercial price variation for breast reconstruction. The secondary objective was to characterize the price of breast reconstruction in relation to market concentration and payer mix. Design, Setting, and Participants This was a cross-sectional study conducted from January to April 2022 using 2021 pricing data made available after the Hospital Price Transparency Rule. National data were obtained from Turquoise Health, a data service platform that aggregates price disclosures from hospital websites. Participants were included from all hospitals with disclosed pricing data for breast reconstructive procedures, identified by Current Procedural Terminology (CPT) code. Main Outcomes and Measures Price variation was measured via within- and across-hospital ratios. A mixed-effects linear model evaluated commercial rates relative to governmental rates and the Herfindahl-Hirschman Index (health care market concentration) at the facility level. Linear regression was used to evaluate commercial rates as a function of facility characteristics. Results A total of 69 834 unique commercial rates were extracted from 978 facilities across 335 metropolitan areas. Commercial rates increased as health care markets became less competitive (coefficient, $4037.52; 95% CI, $700.12 to $7374.92; P = .02; for Herfindahl-Hirschman Index [HHI] 1501-2500, coefficient $3290.21; 95% CI, $878.08 to $5702.34; P = .01; both compared with HHI ≤1500). Commercial rates demonstrated economically insignificant associations with Medicare and Medicaid rates (Medicare coefficient, -$0.05; 95% CI, -$0.14 to $0.03; P = .23; Medicaid coefficient, $0.14; 95% CI, $0.07 to $0.22; P < .001). Safety-net and nonprofit hospitals reported lower commercial rates (coefficient, -$3269.58; 95% CI, -$3815.42 to -$2723.74; P < .001 and coefficient, -$1892.79; -$2519.61 to -$1265.97; P < .001, respectively). Extra-large hospitals (400+ beds) reported higher commercial rates compared with their smaller counterparts (coefficient, $1036.07; 95% CI, $198.29 to $1873.85, P = .02). Conclusions and Relevance Study results suggest that commercial rates for breast reconstruction demonstrated large nationwide variation. Higher commercial rates were associated with less competitive markets and facilities that were large, for-profit, and nonsafety net. Privately insured patients with breast cancer may experience higher premiums and deductibles as US hospital market consolidation and for-profit hospitals continue to grow. Transparency policies should be continued along with actions that facilitate greater health care market competition. There was no evidence that facilities increase commercial rates in response to lower governmental rates.
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Affiliation(s)
- Danielle H. Rochlin
- Division of Plastic and Reconstructive Surgery, Stanford University Medical Center, Palo Alto, California,Plastic and Reconstructive Surgery Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Nada M. Rizk
- Division of Plastic and Reconstructive Surgery, Stanford University Medical Center, Palo Alto, California
| | - Evan Matros
- Plastic and Reconstructive Surgery Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Todd H. Wagner
- S-SPIRE, Department of Surgery, Stanford University, Palo Alto, California
| | - Clifford C. Sheckter
- Division of Plastic and Reconstructive Surgery, Stanford University Medical Center, Palo Alto, California,S-SPIRE, Department of Surgery, Stanford University, Palo Alto, California
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18
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Vanneman ME, Rosen AK, Wagner TH, Shwartz M, Gordon SH, Greenberg G, Zheng T, Cook J, Beilstein-Wedel E, Greene T, Kelley AT. Differences Between VHA-Delivered and VHA-Purchased Behavioral Health Care in Service and Patient Characteristics. Psychiatr Serv 2023; 74:148-157. [PMID: 36039555 PMCID: PMC10069743 DOI: 10.1176/appi.ps.202100730] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
OBJECTIVE Federal legislation has expanded Veterans Health Administration (VHA) enrollees' access to VHA-purchased "community care." This study examined differences in the amount and type of behavioral health care delivered in VHA and purchased in the community, along with patient characteristics and area supply and demand factors. METHODS This retrospective cross-sectional study examined data for 204,094 VHA enrollees with 448,648 inpatient behavioral health stays and 3,467,010 enrollees with 55,043,607 outpatient behavioral health visits from fiscal years 2016 to 2019. Standardized mean differences (SMDs) were calculated for patient and provider characteristics at the outpatient-visit level for VHA and community care. Linear probability models assessed the association between severity of behavioral health condition and site of care. RESULTS Twenty percent of inpatient stays were purchased through community care, with severe behavioral health conditions more likely to be treated in VHA inpatient care. In the outpatient setting, community care accounted for 3% of behavioral health care visits, with increasing use over time. For outpatient care, veterans receiving community care were more likely than those receiving VHA care to see clinicians with fewer years of training (SMD=1.06). CONCLUSIONS With a large portion of inpatient behavioral health care occurring in the community and increased use of outpatient behavioral health care with less highly trained community providers, coordination between VHA and the community is essential to provide appropriate inpatient follow-up care and address outpatient needs. This is especially critical given VHA's expertise in providing behavioral health care to veterans and its legislative responsibility to ensure integrated care.
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Affiliation(s)
- Megan E Vanneman
- Informatics, Decision-Enhancement and Analytic Sciences Center, Department of Veterans Affairs (VA) Salt Lake City Health Care System (Vanneman, Zheng, Kelley), and Department of Internal Medicine (Vanneman, Greene, Kelley) and Department of Population Health Sciences (Zheng, Greene), University of Utah School of Medicine, Salt Lake City; Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System (Rosen, Shwartz, Beilstein-Wedel), and Department of Surgery, Boston University School of Medicine, Boston (Rosen); Department of Operations and Technology Management, Boston University Questrom School of Business, Boston (Shwartz); Health Economics Resource Center, VA Palo Alto Health Care System, Menlo Park, California, and Department of Surgery, Stanford University School of Medicine, Stanford, California (Wagner); Partnered Evidence-Based Policy Resource Center, VA Boston Healthcare System, and Department of Health Law, Policy, and Management, Boston University School of Public Health, Boston (Gordon); Northeast Program Evaluation Center, VA Connecticut Healthcare System, West Haven, and Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut (Greenberg); Health Catalyst, Salt Lake City (Cook)
| | - Amy K Rosen
- Informatics, Decision-Enhancement and Analytic Sciences Center, Department of Veterans Affairs (VA) Salt Lake City Health Care System (Vanneman, Zheng, Kelley), and Department of Internal Medicine (Vanneman, Greene, Kelley) and Department of Population Health Sciences (Zheng, Greene), University of Utah School of Medicine, Salt Lake City; Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System (Rosen, Shwartz, Beilstein-Wedel), and Department of Surgery, Boston University School of Medicine, Boston (Rosen); Department of Operations and Technology Management, Boston University Questrom School of Business, Boston (Shwartz); Health Economics Resource Center, VA Palo Alto Health Care System, Menlo Park, California, and Department of Surgery, Stanford University School of Medicine, Stanford, California (Wagner); Partnered Evidence-Based Policy Resource Center, VA Boston Healthcare System, and Department of Health Law, Policy, and Management, Boston University School of Public Health, Boston (Gordon); Northeast Program Evaluation Center, VA Connecticut Healthcare System, West Haven, and Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut (Greenberg); Health Catalyst, Salt Lake City (Cook)
| | - Todd H Wagner
- Informatics, Decision-Enhancement and Analytic Sciences Center, Department of Veterans Affairs (VA) Salt Lake City Health Care System (Vanneman, Zheng, Kelley), and Department of Internal Medicine (Vanneman, Greene, Kelley) and Department of Population Health Sciences (Zheng, Greene), University of Utah School of Medicine, Salt Lake City; Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System (Rosen, Shwartz, Beilstein-Wedel), and Department of Surgery, Boston University School of Medicine, Boston (Rosen); Department of Operations and Technology Management, Boston University Questrom School of Business, Boston (Shwartz); Health Economics Resource Center, VA Palo Alto Health Care System, Menlo Park, California, and Department of Surgery, Stanford University School of Medicine, Stanford, California (Wagner); Partnered Evidence-Based Policy Resource Center, VA Boston Healthcare System, and Department of Health Law, Policy, and Management, Boston University School of Public Health, Boston (Gordon); Northeast Program Evaluation Center, VA Connecticut Healthcare System, West Haven, and Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut (Greenberg); Health Catalyst, Salt Lake City (Cook)
| | - Michael Shwartz
- Informatics, Decision-Enhancement and Analytic Sciences Center, Department of Veterans Affairs (VA) Salt Lake City Health Care System (Vanneman, Zheng, Kelley), and Department of Internal Medicine (Vanneman, Greene, Kelley) and Department of Population Health Sciences (Zheng, Greene), University of Utah School of Medicine, Salt Lake City; Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System (Rosen, Shwartz, Beilstein-Wedel), and Department of Surgery, Boston University School of Medicine, Boston (Rosen); Department of Operations and Technology Management, Boston University Questrom School of Business, Boston (Shwartz); Health Economics Resource Center, VA Palo Alto Health Care System, Menlo Park, California, and Department of Surgery, Stanford University School of Medicine, Stanford, California (Wagner); Partnered Evidence-Based Policy Resource Center, VA Boston Healthcare System, and Department of Health Law, Policy, and Management, Boston University School of Public Health, Boston (Gordon); Northeast Program Evaluation Center, VA Connecticut Healthcare System, West Haven, and Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut (Greenberg); Health Catalyst, Salt Lake City (Cook)
| | - Sarah H Gordon
- Informatics, Decision-Enhancement and Analytic Sciences Center, Department of Veterans Affairs (VA) Salt Lake City Health Care System (Vanneman, Zheng, Kelley), and Department of Internal Medicine (Vanneman, Greene, Kelley) and Department of Population Health Sciences (Zheng, Greene), University of Utah School of Medicine, Salt Lake City; Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System (Rosen, Shwartz, Beilstein-Wedel), and Department of Surgery, Boston University School of Medicine, Boston (Rosen); Department of Operations and Technology Management, Boston University Questrom School of Business, Boston (Shwartz); Health Economics Resource Center, VA Palo Alto Health Care System, Menlo Park, California, and Department of Surgery, Stanford University School of Medicine, Stanford, California (Wagner); Partnered Evidence-Based Policy Resource Center, VA Boston Healthcare System, and Department of Health Law, Policy, and Management, Boston University School of Public Health, Boston (Gordon); Northeast Program Evaluation Center, VA Connecticut Healthcare System, West Haven, and Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut (Greenberg); Health Catalyst, Salt Lake City (Cook)
| | - Greg Greenberg
- Informatics, Decision-Enhancement and Analytic Sciences Center, Department of Veterans Affairs (VA) Salt Lake City Health Care System (Vanneman, Zheng, Kelley), and Department of Internal Medicine (Vanneman, Greene, Kelley) and Department of Population Health Sciences (Zheng, Greene), University of Utah School of Medicine, Salt Lake City; Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System (Rosen, Shwartz, Beilstein-Wedel), and Department of Surgery, Boston University School of Medicine, Boston (Rosen); Department of Operations and Technology Management, Boston University Questrom School of Business, Boston (Shwartz); Health Economics Resource Center, VA Palo Alto Health Care System, Menlo Park, California, and Department of Surgery, Stanford University School of Medicine, Stanford, California (Wagner); Partnered Evidence-Based Policy Resource Center, VA Boston Healthcare System, and Department of Health Law, Policy, and Management, Boston University School of Public Health, Boston (Gordon); Northeast Program Evaluation Center, VA Connecticut Healthcare System, West Haven, and Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut (Greenberg); Health Catalyst, Salt Lake City (Cook)
| | - Tianyu Zheng
- Informatics, Decision-Enhancement and Analytic Sciences Center, Department of Veterans Affairs (VA) Salt Lake City Health Care System (Vanneman, Zheng, Kelley), and Department of Internal Medicine (Vanneman, Greene, Kelley) and Department of Population Health Sciences (Zheng, Greene), University of Utah School of Medicine, Salt Lake City; Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System (Rosen, Shwartz, Beilstein-Wedel), and Department of Surgery, Boston University School of Medicine, Boston (Rosen); Department of Operations and Technology Management, Boston University Questrom School of Business, Boston (Shwartz); Health Economics Resource Center, VA Palo Alto Health Care System, Menlo Park, California, and Department of Surgery, Stanford University School of Medicine, Stanford, California (Wagner); Partnered Evidence-Based Policy Resource Center, VA Boston Healthcare System, and Department of Health Law, Policy, and Management, Boston University School of Public Health, Boston (Gordon); Northeast Program Evaluation Center, VA Connecticut Healthcare System, West Haven, and Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut (Greenberg); Health Catalyst, Salt Lake City (Cook)
| | - James Cook
- Informatics, Decision-Enhancement and Analytic Sciences Center, Department of Veterans Affairs (VA) Salt Lake City Health Care System (Vanneman, Zheng, Kelley), and Department of Internal Medicine (Vanneman, Greene, Kelley) and Department of Population Health Sciences (Zheng, Greene), University of Utah School of Medicine, Salt Lake City; Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System (Rosen, Shwartz, Beilstein-Wedel), and Department of Surgery, Boston University School of Medicine, Boston (Rosen); Department of Operations and Technology Management, Boston University Questrom School of Business, Boston (Shwartz); Health Economics Resource Center, VA Palo Alto Health Care System, Menlo Park, California, and Department of Surgery, Stanford University School of Medicine, Stanford, California (Wagner); Partnered Evidence-Based Policy Resource Center, VA Boston Healthcare System, and Department of Health Law, Policy, and Management, Boston University School of Public Health, Boston (Gordon); Northeast Program Evaluation Center, VA Connecticut Healthcare System, West Haven, and Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut (Greenberg); Health Catalyst, Salt Lake City (Cook)
| | - Erin Beilstein-Wedel
- Informatics, Decision-Enhancement and Analytic Sciences Center, Department of Veterans Affairs (VA) Salt Lake City Health Care System (Vanneman, Zheng, Kelley), and Department of Internal Medicine (Vanneman, Greene, Kelley) and Department of Population Health Sciences (Zheng, Greene), University of Utah School of Medicine, Salt Lake City; Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System (Rosen, Shwartz, Beilstein-Wedel), and Department of Surgery, Boston University School of Medicine, Boston (Rosen); Department of Operations and Technology Management, Boston University Questrom School of Business, Boston (Shwartz); Health Economics Resource Center, VA Palo Alto Health Care System, Menlo Park, California, and Department of Surgery, Stanford University School of Medicine, Stanford, California (Wagner); Partnered Evidence-Based Policy Resource Center, VA Boston Healthcare System, and Department of Health Law, Policy, and Management, Boston University School of Public Health, Boston (Gordon); Northeast Program Evaluation Center, VA Connecticut Healthcare System, West Haven, and Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut (Greenberg); Health Catalyst, Salt Lake City (Cook)
| | - Tom Greene
- Informatics, Decision-Enhancement and Analytic Sciences Center, Department of Veterans Affairs (VA) Salt Lake City Health Care System (Vanneman, Zheng, Kelley), and Department of Internal Medicine (Vanneman, Greene, Kelley) and Department of Population Health Sciences (Zheng, Greene), University of Utah School of Medicine, Salt Lake City; Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System (Rosen, Shwartz, Beilstein-Wedel), and Department of Surgery, Boston University School of Medicine, Boston (Rosen); Department of Operations and Technology Management, Boston University Questrom School of Business, Boston (Shwartz); Health Economics Resource Center, VA Palo Alto Health Care System, Menlo Park, California, and Department of Surgery, Stanford University School of Medicine, Stanford, California (Wagner); Partnered Evidence-Based Policy Resource Center, VA Boston Healthcare System, and Department of Health Law, Policy, and Management, Boston University School of Public Health, Boston (Gordon); Northeast Program Evaluation Center, VA Connecticut Healthcare System, West Haven, and Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut (Greenberg); Health Catalyst, Salt Lake City (Cook)
| | - A Taylor Kelley
- Informatics, Decision-Enhancement and Analytic Sciences Center, Department of Veterans Affairs (VA) Salt Lake City Health Care System (Vanneman, Zheng, Kelley), and Department of Internal Medicine (Vanneman, Greene, Kelley) and Department of Population Health Sciences (Zheng, Greene), University of Utah School of Medicine, Salt Lake City; Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System (Rosen, Shwartz, Beilstein-Wedel), and Department of Surgery, Boston University School of Medicine, Boston (Rosen); Department of Operations and Technology Management, Boston University Questrom School of Business, Boston (Shwartz); Health Economics Resource Center, VA Palo Alto Health Care System, Menlo Park, California, and Department of Surgery, Stanford University School of Medicine, Stanford, California (Wagner); Partnered Evidence-Based Policy Resource Center, VA Boston Healthcare System, and Department of Health Law, Policy, and Management, Boston University School of Public Health, Boston (Gordon); Northeast Program Evaluation Center, VA Connecticut Healthcare System, West Haven, and Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut (Greenberg); Health Catalyst, Salt Lake City (Cook)
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Knowlton LM, Tran LD, Arnow K, Trickey AW, Morris AM, Spain DA, Wagner TH. Emergency Medicaid programs may be an effective means of providing sustained insurance among trauma patients: A statewide longitudinal analysis. J Trauma Acute Care Surg 2023; 94:53-60. [PMID: 36138539 PMCID: PMC9805493 DOI: 10.1097/ta.0000000000003796] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
BACKGROUND Hospital Presumptive Eligibility (HPE) is a temporary Medicaid insurance at hospitalization that offsets costs of care, increases access to postdischarge resources, and provides patients with a path to sustain coverage through Medicaid. Because HPE only lasts up to 60 days, we aimed to determine Medicaid insurance status 6 months after injury among HPE-approved trauma patients and identify factors associated with successful sustainment. METHODS Using a customized longitudinal claims data set for HPE-approved patients from the California Department of Health Care Services, we analyzed adults with a primary trauma diagnosis (International Classification of Diseases version 10) who were HPE approved in 2016 and 2017. Our primary outcome was Medicaid sustainment at 6 months. Univariate and multivariate analyses were performed. RESULTS A total of 9,749 trauma patients with HPE were analyzed; 6,795 (69.7%) sustained Medicaid at 6 months. Compared with patients who did not sustain, those who sustained had higher Injury Severity Score (ISS > 15: 73.5% vs. 68.7%, p < 0.001), more frequent surgical intervention (74.8% vs. 64.5%, p < 0.001), and were more likely to be discharged to postacute services (23.9% vs. 10.4%, p < 0.001). Medicaid sustainment was high among patients who identified as White (86.7%), Hispanic (86.7%), Black (84.3%), and Asian (83.7%). Medicaid sustainment was low among the 2,505 patients (25.7%) who declined to report race, ethnicity, or preferred language (14.8% sustainment). In adjusted analyses, major injuries (ISS > 16) (vs. ISS < 15: adjusted odds ratio [aOR], 1.51; p = 0.02) and surgery (aOR, 1.85; p < 0.001) were associated with increased likelihood of Medicaid sustainment. Declining to disclose race, ethnicity, or language (aOR, 0.05; p < 0.001) decreased the likelihood of Medicaid sustainment. CONCLUSION Hospital Presumptive Eligibility programs are a promising pathway for securing long-term insurance coverage for trauma patients, particularly among the severely injured who likely require ongoing access to health care services. Patient and provider interviews would help to elucidate barriers for patients who do not sustain. LEVEL OF EVIDENCE Prognostic and Epidemiological; Level IV.
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Affiliation(s)
- Lisa Marie Knowlton
- Department of Surgery, Stanford University School of Medicine, Stanford, CA
- Stanford-Surgery Policy Improvement Research and Education Center (S-SPIRE)
| | - Linda D. Tran
- Stanford-Surgery Policy Improvement Research and Education Center (S-SPIRE)
| | - Katherine Arnow
- Stanford-Surgery Policy Improvement Research and Education Center (S-SPIRE)
| | - Amber W. Trickey
- Stanford-Surgery Policy Improvement Research and Education Center (S-SPIRE)
| | - Arden M. Morris
- Department of Surgery, Stanford University School of Medicine, Stanford, CA
- Stanford-Surgery Policy Improvement Research and Education Center (S-SPIRE)
| | - David A. Spain
- Department of Surgery, Stanford University School of Medicine, Stanford, CA
| | - Todd H. Wagner
- Stanford-Surgery Policy Improvement Research and Education Center (S-SPIRE)
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Gujral K, Bahraini N, Brenner LA, Van Campen J, Zulman DM, Illarmo S, Wagner TH. VA's implementation of universal screening and evaluation for the suicide risk identification program in November 2020 -Implications for Veterans with prior mental health needs. PLoS One 2023; 18:e0283633. [PMID: 37040367 PMCID: PMC10089346 DOI: 10.1371/journal.pone.0283633] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Accepted: 03/13/2023] [Indexed: 04/12/2023] Open
Abstract
IMPORTANCE United States Veterans are at higher risk for suicide than non-Veterans. Veterans in rural areas are at higher risk than their urban counterparts. The coronavirus pandemic intensified risk factors for suicide, especially in rural areas. OBJECTIVE To examine associations between Veterans Health Administration's (VA's) universal suicide risk screening, implemented November 2020, and likelihood of Veterans being screened, and receiving follow-up evaluations, as well as post-screening suicidal behavior among patients who used VA mental health services in 2019. METHODS VA's Suicide Risk Identification Strategy (Risk ID), implemented October 2018, is a national, standardized process for suicide risk screening and evaluation. In November 2020, VA expanded Risk ID, requiring annual universal suicide screening. As such, we are evaluating outcomes of interest before and after the start of the policy among Veterans who had ≥1 VA mental health care visit in 2019 (n = 1,654,180; rural n = 485,592, urban n = 1,168,588). Regression-adjusted outcomes were compared 6 months pre-universal screening and 6, 12 and 13 months post-universal screening implementation. MEASURES Item-9 on the Patient Health Questionnaire (I-9, VA's historic suicide screener), Columbia- Suicide Severity Risk Scale (C-SSRS) Screener, VA's Comprehensive Suicide Risk Evaluation (CSRE), and Suicide Behavior and Overdose Report (SBOR). RESULTS 12 months post-universal screening implementation, 1.3 million Veterans (80% of the study cohort) were screened or evaluated for suicide risk, with 91% the sub-cohort who had at least one mental health visit in the 12 months post-universal screening implementation period were screened or evaluated. At least 20% of the study cohort was screened outside of mental health care settings. Among Veterans with positive screens, 80% received follow-up CSREs. Covariate-adjusted models indicated that an additional 89,160 Veterans were screened per month via the C-SSRS and an additional 30,106 Veterans/month screened via either C-SSRS or I-9 post-universal screening implementation. Compared to their urban counterparts, 7,720 additional rural Veterans/month were screened via the C-SSRS and 9,226 additional rural Veterans/month were screened via either the C-SSRS or I-9. CONCLUSION VA's universal screening requirement via VA's Risk ID program increased screening for suicide risk among Veterans with mental health care needs. A universal approach to screening may be particularly advantageous for rural Veterans, who are typically at higher risk for suicide but have fewer interactions with the health care system, particularly within specialty care settings, due to higher barriers to accessing care. Insights from this program offer valuable insights for health systems nationwide.
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Affiliation(s)
- Kritee Gujral
- Health Economics Resource Center, VA Palo Alto Health Care System, Menlo Park, California, United States of America
- Center for Innovation to Implementation, VA Palo Alto Health Care System, Menlo Park, California, United States of America
| | - Nazanin Bahraini
- Rocky Mountain Mental Illness Research, Education and Clinical Center, Rocky Mountain Regional VA Medical Center, Aurora, Colorado, United States of America
- Department of Psychiatry, University of Colorado, Anschutz School of Medicine, Aurora, CO, United States of America
- Department of Physical Medicine and Rehabilitation, University of Colorado, Anschutz School of Medicine, Aurora, Colorado, United States of America
| | - Lisa A Brenner
- Rocky Mountain Mental Illness Research, Education and Clinical Center, Rocky Mountain Regional VA Medical Center, Aurora, Colorado, United States of America
- Department of Psychiatry, University of Colorado, Anschutz School of Medicine, Aurora, CO, United States of America
- Department of Physical Medicine and Rehabilitation, University of Colorado, Anschutz School of Medicine, Aurora, Colorado, United States of America
- Department of Neurology, University of Colorado, Anschutz School of Medicine, Aurora, Colorado, United States of America
| | - James Van Campen
- Center for Innovation to Implementation, VA Palo Alto Health Care System, Menlo Park, California, United States of America
- Department of Medicine, Division of Primary Care and Population Health, Stanford University School of Medicine, Stanford, California, United States of America
| | - Donna M Zulman
- Center for Innovation to Implementation, VA Palo Alto Health Care System, Menlo Park, California, United States of America
- Department of Medicine, Division of Primary Care and Population Health, Stanford University School of Medicine, Stanford, California, United States of America
| | - Samantha Illarmo
- Health Economics Resource Center, VA Palo Alto Health Care System, Menlo Park, California, United States of America
| | - Todd H Wagner
- Health Economics Resource Center, VA Palo Alto Health Care System, Menlo Park, California, United States of America
- Center for Innovation to Implementation, VA Palo Alto Health Care System, Menlo Park, California, United States of America
- Department of Surgery, Stanford University School of Medicine, Stanford, California, United States of America
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21
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Graham LA, Schoemaker L, Rose L, Morris AM, Aouad M, Wagner TH. Expansion of the Veterans Health Administration Network and Surgical Outcomes. JAMA Surg 2022; 157:1115-1123. [PMID: 36223115 PMCID: PMC9558067 DOI: 10.1001/jamasurg.2022.4978] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Accepted: 07/16/2022] [Indexed: 01/11/2023]
Abstract
Importance The US Department of Veterans Affairs (VA) Veterans Choice Program (VCP) expanded health care access to community settings outside the VA for eligible patients. Little is known about the effect of VCP on access to surgery and postoperative outcomes. Since its initiation, care coordination issues, which are often associated with adverse postoperative outcomes, have been reported. Research findings on the association of VCP and postoperative outcomes are limited to only a few select procedures and have been mixed, potentially due to bias from unmeasured confounding. Objective To investigate the association of the VCP with access to surgery and postoperative outcomes using a nonrandomized controlled regression discontinuity design (RDD) to reduce the impact of unmeasured confounders. Design, Setting, and Participants This was a nonrandomized RDD study of the Veterans Health Administration (VHA). Participants included veterans enrolled in the VHA who required surgery between October 1, 2014, and June 1, 2019. Interventions The VCP, which expanded access to VA-paid community care for eligible veterans living 40 miles or more from their closest VA hospital. Main Outcomes and Measures Postoperative emergency department visits, inpatient readmissions, and mortality at 30 and 90 days. Results A total of 615 473 unique surgical procedures among 498 427 patients (mean [SD] age, 63.0 [12.9] years; 450 366 male [90.4%]) were identified. Overall, 94 783 procedures (15.4%) were paid by the VHA, and the proportion of VHA-paid procedures varied by procedure type. Patients who underwent VA-paid procedures were more likely to be women (9209 [12.7%] vs men, 38 771 [9.1%]), White race (VA paid, 54 544 [74.4%] vs VA provided, 310 077 [73.0%]), and younger than 65 years (VA paid, 36 054 [49.1%] vs 229 411 [46.0%] VA provided), with a significantly lower comorbidity burden (mean [SD], 1.8 [2.2] vs 2.6 [2.7]). The nonrandomized RDD revealed that VCP was associated with a slight increase of 0.03 in the proportion of VA-paid surgical procedures among eligible veterans (95% CI, 0.01-0.05; P = .01). However, there was no difference in postoperative mortality, readmissions, or emergency department visits. Conclusions and Relevance Expanded access to health care in the VHA was associated with a shift in the performance of surgical procedures in the private sector but had no measurable association with surgical outcomes. These findings may assuage concerns of worsened patient outcomes resulting from care coordination issues when care is expanded outside of a single health care system, although it remains unclear whether these additional procedures were appropriate or improved patient outcomes.
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Affiliation(s)
- Laura A. Graham
- Health Economics Resource Center, Veterans Affairs Palo Alto Health Care System, Menlo Park, California
- Stanford Surgery Policy Improvement Research and Education Center, Stanford School of Medicine, Stanford, California
| | - Lena Schoemaker
- Health Economics Resource Center, Veterans Affairs Palo Alto Health Care System, Menlo Park, California
| | - Liam Rose
- Health Economics Resource Center, Veterans Affairs Palo Alto Health Care System, Menlo Park, California
- Stanford Surgery Policy Improvement Research and Education Center, Stanford School of Medicine, Stanford, California
| | - Arden M. Morris
- Stanford Surgery Policy Improvement Research and Education Center, Stanford School of Medicine, Stanford, California
| | - Marion Aouad
- Department of Economics, University of California, Irvine
| | - Todd H. Wagner
- Health Economics Resource Center, Veterans Affairs Palo Alto Health Care System, Menlo Park, California
- Stanford Surgery Policy Improvement Research and Education Center, Stanford School of Medicine, Stanford, California
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22
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George EL, Wagner TH, Arya S. Atherectomy Overuse: Do Policy Solutions Exist? J Am Heart Assoc 2022; 11:e027422. [DOI: 10.1161/jaha.122.027422] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Affiliation(s)
- Elizabeth L. George
- Department of Surgery, Division of Vascular Surgery Stanford University School of Medicine Stanford CA
- VA Palo Alto Health Care System, Surgical Service Line Palo Alto CA
| | - Todd H. Wagner
- Veterans Affairs Health Economic Resource Center Palo Alto CA
| | - Shipra Arya
- Department of Surgery, Division of Vascular Surgery Stanford University School of Medicine Stanford CA
- VA Palo Alto Health Care System, Surgical Service Line Palo Alto CA
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Goldman S, McCarren M, Sethi GK, Holman W, Bakaeen FG, Wagner TH, Wang Y, Shih MC, Edson R. Long-Term Mortality Follow-Up of Radial Artery Versus Saphenous Vein in Coronary Artery Bypass Grafting: A Multicenter, Randomized Trial. Circulation 2022; 146:1323-1325. [PMID: 36279414 DOI: 10.1161/circulationaha.122.062343] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Affiliation(s)
- Steven Goldman
- Sarver Heart Center (S.G.), University of Arizona, Tucson
| | | | | | - William Holman
- University of Alabama, Birmingham VA Medical Center (W.H.)
| | - Faisal G Bakaeen
- Department of Thoracic and Cardiovascular Surgery, Cleveland Clinic, OH (F.G.B.)
| | - Todd H Wagner
- VA Health Economics Resource Center, Palo Alto VA, CA (T.H.W.).,Department of Surgery, Stanford University, Palo Alto, CA (T.H.W.)
| | - Yajie Wang
- Department of Surgery, Stanford University, Palo Alto, CA (T.H.W.)
| | - Mei-Chung Shih
- Department of Surgery, Stanford University, Palo Alto, CA (T.H.W.)
| | - Robert Edson
- Department of Surgery, Stanford University, Palo Alto, CA (T.H.W.)
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24
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Salloum RG, Wagner TH, Midboe AM, Daniels SI, Quanbeck A, Chambers DA. The economics of adaptations to evidence-based practices. Implement Sci Commun 2022; 3:100. [PMID: 36153575 PMCID: PMC9509646 DOI: 10.1186/s43058-022-00345-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Accepted: 09/15/2022] [Indexed: 11/10/2022] Open
Abstract
Background Evidence-based practices (EBPs) are frequently adapted in response to the dynamic contexts in which they are implemented. Adaptation is defined as the degree to which an EBP is altered to fit the setting or to improve fit to local context and can be planned or unplanned. Although adaptations are common and necessary to maximizing the marginal impact of EBPs, little attention has been given to the economic consequences and how adaptations affect marginal costs. Discussion In assessing the economic consequences of adaptation, one should consider its impact on core components, the planned adaptive periphery, and the unplanned adaptive periphery. Guided by implementation science frameworks, we examine how various economic evaluation approaches accommodate the influence of adaptations and discuss the pros and cons of these approaches. Using the Framework for Reporting Adaptations and Modifications to Evidence-based interventions (FRAME), mixed methods can elucidate the economic reasons driving the adaptations. Micro-costing approaches are applied in research that integrates the adaptation of EBPs at the planning stage using innovative, adaptive study designs. In contrast, evaluation of unplanned adaptation is subject to confounding and requires sensitivity analysis to address unobservable measures and other uncertainties. A case study is presented using the RE-AIM framework to illustrate the costing of adaptations. In addition to empirical approaches to evaluating adaptation, simulation modeling approaches can be used to overcome limited follow-up in implementation studies. Conclusions As implementation science evolves to improve our understanding of the mechanisms and implications of adaptations, it is increasingly important to understand the economic implications of such adaptations, in addition to their impact on clinical effectiveness. Therefore, explicit consideration is warranted of how costs can be evaluated as outcomes of adaptations to the delivery of EBPs.
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25
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Giori NJ, Beilstein-Wedel EE, Shwartz M, Harris AHS, Vanneman ME, Wagner TH, Rosen AK. Association of Quality of Care With Where Veterans Choose to Get Knee Replacement Surgery. JAMA Netw Open 2022; 5:e2233259. [PMID: 36178687 PMCID: PMC9526089 DOI: 10.1001/jamanetworkopen.2022.33259] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Accepted: 08/08/2022] [Indexed: 11/14/2022] Open
Abstract
Importance Recent legislation expanded veterans' access to Veterans Health Administration (VA)-purchased care. Quality should be considered when choosing where to get total knee arthroplasty (TKA), but currently available quality metrics provide little guidance. Objective To determine whether an association exists between the proportion of TKAs performed (vs purchased) at each VA facility and the quality of care provided (as measured by short-term complication rates). Design, Setting, and Participants This 3-year cohort study used VA and community care data (fiscal year 2017 to fiscal year 2019) from the VA's Corporate Data Warehouse. Complications were defined following the Centers for Medicare and Medicaid Services' methodology. The setting included 140 VA health care facilities performing or purchasing TKAs. Participants included veterans who had 43 371 primary TKA procedures that were either VA-performed or VA-purchased during the study period. Exposures Of the 43 371 primary TKA procedures, 18 964 (43.7%) were VA-purchased. Main Outcomes and Measures The primary outcome was risk-standardized short-term complication rates of VA-performed or VA-purchased TKAs. The association between the proportion of TKAs performed at each VA facility and quality of VA-performed and VA-purchased care was examined using a regression model. Subgroups were also identified for facilities that had complication rates above or below the overall mean complication rate and for facilities that performed more or less than half of the facility's TKAs. Results Among the study sample's 41 775 veterans who underwent 43 371 TKAs, 38 725 (89.3%) were male, 6406 (14.8%) were Black, 33 211 (76.6%) were White, and 1367 (3.2%) had other race or ethnicity (including American Indian or Alaska Native, Asian, and Native Hawaiian or other Pacific Islander); mean (SD) age was 66.9 (8.5) years. VA-performed and VA-purchased TKAs had a mean (SD) raw overall short-term complication rate of 2.97% (0.08%). There was no association between the proportion of TKAs performed in VA facilities and risk-standardized complication rates for VA-performed TKAs, and no association for VA-purchased TKAs. Conclusions and Relevance In this cohort study, surgical quality did not have an association with where veterans had TKA, possibly because meaningful comparative data are lacking. Reporting local and community risk-standardized complication rates may inform veterans' decisions and improve care. Combining these data with the proportion of TKAs performed at each site could facilitate administrative decisions on where resources should be allocated to improve care.
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Affiliation(s)
- Nicholas J. Giori
- Center for Innovation to Implementation, VA Palo Alto Health Care System, Palo Alto, California
- Department of Orthopedic Surgery, Stanford University, Redwood City, California
| | - Erin E. Beilstein-Wedel
- Center for Health Care Organization and Implementation Research, VA Boston Health Care System, Boston, Massachusetts
| | - Michael Shwartz
- Center for Health Care Organization and Implementation Research, VA Boston Health Care System, Boston, Massachusetts
| | - Alex H. S. Harris
- Center for Innovation to Implementation, VA Palo Alto Health Care System, Palo Alto, California
- Department of Surgery, Stanford University, Stanford, California
| | - Megan E. Vanneman
- Informatics, Decision-Enhancement and Analytic Sciences Center (IDEAS), VA Salt Lake City Health Care System, Salt Lake City, Utah
- Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City
- Department of Population Health Sciences, University of Utah School of Medicine, Salt Lake City
| | - Todd H. Wagner
- Center for Innovation to Implementation, VA Palo Alto Health Care System, Palo Alto, California
| | - Amy K. Rosen
- Center for Health Care Organization and Implementation Research, VA Boston Health Care System, Boston, Massachusetts
- Department of Surgery, Boston University School of Medicine, Boston, Massachusetts
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Wagner TH, Schoemaker L, Gehlert E, Nelson RE, Murphy K, Martini S, Graham GD, Govindarajan P, Williams LS. One-Year Costs Associated With the Veterans Affairs National TeleStroke Program. Value Health 2022; 25:937-943. [PMID: 35346590 DOI: 10.1016/j.jval.2022.02.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/21/2021] [Revised: 02/16/2022] [Accepted: 02/18/2022] [Indexed: 06/14/2023]
Abstract
OBJECTIVES Access to timely care is important for patients with stroke, where rapid diagnosis and treatment affect functional status, disability, and mortality. Telestroke programs connect stroke specialists with emergency department staff at facilities without on-site stroke expertise. The objective of this study was to examine healthcare costs for patients with stroke who sought care before and after implementation of the US Department of Veterans Affairs National TeleStroke Program (NTSP). METHODS We identified 471 patients who had a stroke and sought care at a telestroke site and compared them to 529 patients with stroke who received stroke care at the same sites before telestroke implementation. We examined patient costs for 12 months before and after stroke, using a linear model with a patient-level fixed effect. RESULTS NTSP was associated with significantly higher rates of patients receiving guideline concordant care. Compared with control patients, those treated by NTSP were 14.3 percentage points more likely to receive tissue plasminogen activator and 4.3 percentage points more likely to receive a thrombectomy (all P < .0001). NTSP was associated with $4821 increased costs for patients with stroke in the first 30 days after the program (2019 dollars). There were no observed savings over 12 months, and the added costs of care were attributable to higher rates of guideline concordant care. CONCLUSIONS Telestroke programs are unlikely to yield short-term savings because optimal stroke care is expensive. Healthcare organizations should expect increases in healthcare costs for patients treated for stroke in the first year after implementing a telestroke program.
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Affiliation(s)
- Todd H Wagner
- Health Economics Resource Center, VA Palo Alto Health Care System, Palo Alto, CA, USA; Center for Innovation to Implementation, VA Palo Alto Health Care System, Palo Alto, CA, USA; Department of Surgery, Stanford University, Stanford, CA, USA.
| | - Lena Schoemaker
- Health Economics Resource Center, VA Palo Alto Health Care System, Palo Alto, CA, USA
| | - Elizabeth Gehlert
- Health Economics Resource Center, VA Palo Alto Health Care System, Palo Alto, CA, USA
| | - Richard E Nelson
- Informatics, Decision-Enhancement and Analytic Sciences Center, VA Salt Lake City Health Care System, Salt Lake City, UT, USA; Department of Internal Medicine, University of Utah, Salt Lake City, UT, USA
| | | | - Sharyl Martini
- VA National TeleStroke Program and VA Office of Specialty Care Services, Washington, DC, USA; Department of Neurology, Baylor College of Medicine, Houston, TX, USA
| | - Glenn D Graham
- VA National TeleStroke Program and VA Office of Specialty Care Services, Washington, DC, USA; Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | | | - Linda S Williams
- VA HSR&D EXTEND QUERI and the Center for Health Information and Communication, Indianapolis VA Medical Center, Indianapolis, IN, USA; Department of Neurology, Indiana University, Indianapolis, IN, USA; Regenstrief Institute, Inc, Indianapolis, IN, USA
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27
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Wagner TH, Hattler B, Stock EM, Biswas K, Bhatt DL, Bakaeen FG, Gujral K, Zenati MA. Costs of Endoscopic vs Open Vein Harvesting for Coronary Artery Bypass Grafting: A Secondary Analysis of the REGROUP Trial. JAMA Netw Open 2022; 5:e2217686. [PMID: 35727582 PMCID: PMC9214587 DOI: 10.1001/jamanetworkopen.2022.17686] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
IMPORTANCE Value-based purchasing creates pressure to examine whether newer technologies and care processes, including new surgical techniques, yield any economic advantage. OBJECTIVE To compare health care costs and utilization between participants randomized to receive endoscopic vein harvesting (EVH) or open vein harvesting (OVH) during a coronary artery bypass grafting (CABG) procedure. DESIGN, SETTING, AND PARTICIPANTS This secondary economic analysis was conducted alongside the 16-site Randomized Endo-Vein Graft Prospective (REGROUP) clinical trial funded by the Department of Veterans Affairs (VA) Cooperative Studies Program. Adults scheduled for urgent or elective bypass involving a vein graft were eligible. The first participant was enrolled in September 2013, with most sites completing enrollment by March 2014. The last participant was enrolled in April 2017. A total of 1150 participants were randomized, with 574 participants receiving OVH and 576 receiving EVH. For this secondary analysis, cost and utilization data were extracted through September 30, 2020. Participants were linked to administrative data in the VA Corporate Data Warehouse and activity-based cost data starting with the index procedure. INTERVENTIONS EVH vs OVH, with comparisons based on intention to treat. MAIN OUTCOMES AND MEASURES Discharge costs for the index procedure as well as follow-up costs (including intended and unintended events; mean [SD] follow-up time, 33.0 [19.9] months) were analyzed, with results from different statistical models compared to test for robustness (ie, lack of variation across models). All costs represented care provided or paid by the VA, standardized to 2020 US dollars. RESULTS Among 1150 participants, the mean (SD) age was 66.4 (6.9) years; most participants (1144 [99.5%] were male. With regard to race and ethnicity, 6 participants (0.5%) self-reported as American Indian or Alaska Native, 10 (0.9%) as Asian or Pacific Islander, 91 (7.9%) as Black, 62 (5.4%) as Hispanic, 974 (84.7%) as non-Hispanic White, and 6 (0.5%) as other race and/or ethnicity; data were missing for 1 participant (0.1%). The unadjusted mean (SD) costs for the index CABG procedure were $76 607 ($43 883) among patients who received EVH and $75 368 ($45 900) among those who received OVH, including facility costs, insurance costs, and physician-related costs (commonly referred to as provider costs in Centers for Medicare and Medicaid and insurance data). No significant differences were found in follow-up costs; per 90-day follow-up period, EVH was associated with a mean (SE) added cost of $302 ($225) per patient. The results were highly robust to the statistical model. CONCLUSIONS AND RELEVANCE In this study, EVH was not associated with a reduction in costs for the index CABG procedure or follow-up care. Therefore, the choice to provide EVH may be based on surgeon and patient preferences. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT01850082.
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Affiliation(s)
- Todd H. Wagner
- Health Economics Resource Center, Veterans Affairs Palo Alto Health Care System, Menlo Park, California
- Department of Surgery, Stanford University, Stanford, California
| | - Brack Hattler
- Rocky Mountain Regional Veterans Affairs Medical Center, Aurora, Colorado
- Division of Cardiology, University of Colorado, Denver
| | - Eileen M. Stock
- Office of Research and Development, VA Cooperative Studies Program Coordinating Center, Perry Point, Maryland
| | - Kousick Biswas
- Office of Research and Development, VA Cooperative Studies Program Coordinating Center, Perry Point, Maryland
| | - Deepak L. Bhatt
- Division of Cardiovascular Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts
| | - Faisal G. Bakaeen
- Department of Thoracic and Cardiovascular Surgery, Cleveland Clinic, Cleveland, Ohio
| | - Kritee Gujral
- Health Economics Resource Center, Veterans Affairs Palo Alto Health Care System, Menlo Park, California
| | - Marco A. Zenati
- Division of Cardiac Surgery, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts
- Veterans Affairs Boston Healthcare System, Boston, Massachusetts
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Hagedorn HJ, Wisdom JP, Gerould H, Pinsker E, Brown R, Dawes M, Dieperink E, Myrick DH, Oliva EM, Wagner TH, Harris AHS. Alcohol use disorder pharmacotherapy and treatment in primary care (ADaPT-PC) trial: Impact on identified barriers to implementation. Subst Abus 2022; 43:1043-1050. [PMID: 35467489 DOI: 10.1080/08897077.2022.2060444] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
Background: A minority of individuals meeting diagnostic criteria for alcohol use disorders (AUD) receive any type of formal treatment. Developing options for AUD treatment within primary care settings is imperative to increase treatment access. A multi-faceted implementation intervention including provider and patient education, clinician reminders, development of local champions and ongoing facilitation was designed to enhance access to AUD pharmacotherapy in primary care settings at three large Veterans Health Administration (VHA) facilities. This qualitative study compared pre-implementation barriers to post-implementation barriers identified via provider interviews to identify those barriers addressed and not addressed by the intervention to better understand the limited impact of the intervention. Methods: Following the nine-month implementation period, primary care providers at the three participating facilities took part in qualitative interviews to collect perceptions regarding which pre-implementation barriers had and had not been successfully addressed by the intervention. Participants included 20 primary care providers from three large VHA facilities. Interviews were coded using common coding techniques for qualitative data using the Consolidated Framework for Implementation Research (CFIR) codebook. Summary reports were created for each CFIR construct for each facility and the impact of each CFIR construct on implementation was coded as positive, neutral, or negative. Results: Some barriers identified during pre-implementation interviews were no longer identified as barriers in the post-implementation interviews. These included Relative Advantage, Relative Priority, and Knowledge & Beliefs about the Innovation. However, Compatibility, Design Quality & Packaging, and Available Resources remained barriers at the end of the implementation period. No substantial new barriers were identified. Conclusions: The implementation intervention appears to have been successful at addressing barriers that could be mitigated with traditional educational approaches. However, the intervention did not adequately address structural and organizational barriers to implementation. Recommendations for enhancing future interventions are provided.
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Affiliation(s)
- Hildi J Hagedorn
- Veterans Affairs Health Services Research and Development Center for Care Delivery & Outcomes Research, Minneapolis Veterans Affairs Health Care System, Minneapolis, MN, USA.,Department of Psychiatry, University of Minnesota School of Medicine, Minneapolis, MN, USA
| | | | - Heather Gerould
- Veterans Affairs Health Services Research and Development Center for Care Delivery & Outcomes Research, Minneapolis Veterans Affairs Health Care System, Minneapolis, MN, USA
| | - Erika Pinsker
- Veterans Affairs Health Services Research and Development Center for Care Delivery & Outcomes Research, Minneapolis Veterans Affairs Health Care System, Minneapolis, MN, USA
| | - Randall Brown
- William S. Middleton Memorial Veterans Hospital, Madison, WI, USA.,Department of Family Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Michael Dawes
- VA Boston Healthcare System, Brockton, MA, USA.,Boston University Medical School, Boston, MA, USA
| | - Eric Dieperink
- Veterans Affairs Health Services Research and Development Center for Care Delivery & Outcomes Research, Minneapolis Veterans Affairs Health Care System, Minneapolis, MN, USA.,Department of Psychiatry, University of Minnesota School of Medicine, Minneapolis, MN, USA
| | - Donald Hugh Myrick
- Center for Drug and Alcohol Problems, Ralph H. Johnson Veterans Affairs Medical Center, Charleston, SC, USA.,Department of Psychiatry and Behavioral Services, Medical University of South Carolina, Charleston, SC, USA
| | - Elizabeth M Oliva
- Veterans Affairs Health Services Research and Development Center for Innovation to Implementation, Palo Alto Veterans Affairs Health Care System, Menlo Park, CA, USA
| | - Todd H Wagner
- Health Economics Resource Center, Palo Alto Veterans Affairs Health Care System, Menlo Park, CA, USA
| | - Alex H S Harris
- Veterans Affairs Health Services Research and Development Center for Innovation to Implementation, Palo Alto Veterans Affairs Health Care System, Menlo Park, CA, USA
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Quin JA, Wagner TH, Hattler B, Carr BM, Collins J, Almassi GH, Grover FL, Shroyer AL. Ten-Year Outcomes of Off-Pump vs On-Pump Coronary Artery Bypass Grafting in the Department of Veterans Affairs: A Randomized Clinical Trial. JAMA Surg 2022; 157:303-310. [PMID: 35171210 PMCID: PMC8851363 DOI: 10.1001/jamasurg.2021.7578] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
IMPORTANCE The long-term benefits of off-pump ("beating heart") vs on-pump coronary artery bypass grafting (CABG) remain controversial. OBJECTIVE To evaluate the 10-year outcomes and costs of off-pump vs on-pump CABG in the Department of Veterans Affairs (VA) Randomized On/Off Bypass (ROOBY) trial. DESIGN, SETTING, AND PARTICIPANTS From February 27, 2002, to May 7, 2007, 2203 veterans in the ROOBY trial were randomly assigned to off-pump or on-pump CABG procedures at 18 participating VA medical centers. Per protocol, the veterans were observed for 10 years; the 10-year, post-CABG clinical outcomes and costs were assessed via centralized abstraction of electronic medical records combined with merges to VA and non-VA databases. With the use of an intention-to-treat approach, analyses were performed from May 7, 2017, to December 9, 2021. INTERVENTIONS On-pump and off-pump CABG procedures. MAIN OUTCOMES AND MEASURES The 10-year coprimary end points included all-cause death and a composite end point identifying patients who had died or had undergone subsequent revascularization (ie, percutaneous coronary intervention [PCI] or repeated CABG); these 2 end points were measured dichotomously and as time-to-event variables (ie, time to death and time to composite end points). Secondary 10-year end points included PCIs, repeated CABG procedures, changes in cardiac symptoms, and 2018-adjusted VA estimated costs. Changes from baseline to 10 years in post-CABG, clinically relevant cardiac symptoms were evaluated for New York Heart Association functional class, Canadian Cardiovascular Society angina class, and atrial fibrillation. Outcome differences were adjudicated by an end points committee. Given that pre-CABG risks were balanced, the protocol-driven primary and secondary hypotheses directly compared 10-year treatment-related effects. RESULTS A total of 1104 patients (1097 men [99.4%]; mean [SD] age, 63.0 [8.5] years) were enrolled in the off-pump group, and 1099 patients (1092 men [99.5%]; mean [SD] age, 62.5 [8.5] years) were enrolled in the on-pump group. The 10-year death rates were 34.2% (n = 378) for the off-pump group and 31.1% (n = 342) for the on-pump group (relative risk, 1.05; 95% CI, 0.99-1.11; P = .12). The median time to composite end point for the off-pump group (4.6 years; IQR, 1.4-7.5 years) was approximately 4.3 months shorter than that for the on-pump group (5.0 years; IQR, 1.8-7.9 years; P = .03). No significant 10-year treatment-related differences were documented for any other primary or secondary end points. After the removal of conversions, sensitivity analyses reconfirmed these findings. CONCLUSIONS AND RELEVANCE No off-pump CABG advantages were found for 10-year death or revascularization end points; the time to composite end point was lower in the off-pump group than in the on-pump group. For veterans, in the absence of on-pump contraindications, a case cannot be made for supplanting the traditional on-pump CABG technique with an off-pump approach. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT01924442.
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Affiliation(s)
- Jacquelyn A. Quin
- Department of Surgery, Veterans Affairs Boston Healthcare System, West Roxbury, Massachusetts
| | - Todd H. Wagner
- Research Office, Veterans Affairs Health Economics and Research Center, Palo Alto, California,Department of Surgery, Stanford University, Palo Alto, California
| | - Brack Hattler
- Department of Medicine, Rocky Mountain Regional Veterans Affairs Medical Center, Aurora, Colorado,Division of Cardiology, Department of Medicine, University of Colorado School of Medicine, Aurora
| | - Brendan M. Carr
- Department of Emergency Medicine, Mayo Clinic, Rochester, Minnesota
| | - Joseph Collins
- Research Office, Veterans Affairs Cooperative Studies Program, Perry Point, Maryland
| | - G. Hossein Almassi
- Department of Surgery, Clement J. Zablocki Veterans Affairs Medical Center, Milwaukee, Wisconsin,Division of Cardiothoracic Surgery, Department of Surgery, Medical College of Wisconsin, Milwaukee
| | - Frederick L. Grover
- Division of Cardiothoracic Surgery, Department of Surgery, University of Colorado School of Medicine, Aurora,Department of Surgery, Rocky Mountain Regional Veterans Affairs Medical Center, Aurora, Colorado
| | - A. Laurie Shroyer
- Research and Development Office, Northport Veterans Affairs Medical Center, Northport, New York,Department of Surgery, Stony Brook University Renaissance School of Medicine, Stony Brook, New York
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Vanneman ME, Yoon J, Singer SJ, Wagner TH, Goldstein MK, Hu J, Boothroyd D, Greene L, Zulman DM. Anticipating VA/non-VA care coordination demand for Veterans at high risk for hospitalization. Medicine (Baltimore) 2022; 101:e28864. [PMID: 35363189 PMCID: PMC9281999 DOI: 10.1097/md.0000000000028864] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Accepted: 01/31/2022] [Indexed: 01/09/2023] Open
Abstract
U.S. Veterans Affairs (VA) patients' multi-system use can create challenges for VA clinicians who are responsible for coordinating Veterans' use of non-VA care, including VA-purchased care ("Community Care") and Medicare.To examine the relationship between drive distance and time-key eligibility criteria for Community Care-and VA reliance (proportion of care received in VA versus Medicare and Community Care) among Veterans at high risk for hospitalization. We used prepolicy data to anticipate the impact of the 2014 Choice Act and 2018 Maintaining Internal Systems and Strengthening Integrated Outside Networks Act (MISSION Act), which expanded access to Community Care.Cross-sectional analysis using fractional logistic regressions to examine the relationship between a Veteran's reliance on VA for outpatient primary, mental health, and other specialty care and their drive distance/time to a VA facility.Thirteen thousand seven hundred three Veterans over the age of 65 years enrolled in VA and fee-for-service Medicare in federal fiscal year 2014 who were in the top 10th percentile for hospitalization risk.Key explanatory variables were patients' drive distance to VA > 40 miles (Choice Act criteria) and drive time to VA ≥ 30 minutes for primary and mental health care and ≥60 minutes for specialty care (MISSION Act criteria).Veterans at high risk for hospitalization with drive distance eligibility had increased odds of an outpatient specialty care visit taking place in VA when compared to Veterans who did not meet Choice Act eligibility criteria (odds ratio = 1.10, 95% confidence interval 1.05-1.15). However, drive time eligibility (MISSION Act criteria) was associated with significantly lower odds of an outpatient specialty care visit taking place in VA (odds ratio = 0.69, 95% confidence interval 0.67, 0.71). Neither drive distance nor drive time were associated with reliance for outpatient primary care or mental health care.VA patients who are at high risk for hospitalization may continue to rely on VA for outpatient primary care and mental health care despite access to outside services, but may increase use of outpatient specialty care in the community in the MISSION era, increasing demand for multi-system care coordination.
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Affiliation(s)
- Megan E. Vanneman
- Informatics, Decision-Enhancement and Analytic Sciences Center, VA Salt Lake City Health Care System, 500 Foothill Drive, Salt Lake City, UT
- Division of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT
- Division of Health System Innovation and Research, Department of Population Health Sciences, University of Utah School of Medicine, Salt Lake City, UT
| | - Jean Yoon
- Health Economics Resource Center, VA Palo Alto Health Care System, 795 Willow Road, Menlo Park, CA
- Department of General Internal Medicine, UCSF School of Medicine, 4150 Clement St., 111A, San Francisco, CA
| | - Sara J. Singer
- VA Palo Alto Health Care System, 795 Willow Road, Menlo Park, CA
- Department of Medicine, Stanford University School of Medicine, 1265 Welch Road, Medical School Office Building, Room 328, Stanford, CA
- Stanford Graduate School of Business, 655 Knight Way, Stanford, CA
| | - Todd H. Wagner
- Health Economics Resource Center, VA Palo Alto Health Care System, 795 Willow Road, Menlo Park, CA
- Department of Surgery, Stanford University School of Medicine, 1070 Arastradero Road, Stanford, CA
| | - Mary K. Goldstein
- Data Analytics, Quality Improvement, and Research, Office of Geriatrics and Extended Care, Veterans Health Administration, Department of Veterans Affairs, VA Palo Alto Health Care System, 3801 Miranda Avenue (GRECC 182B), Palo Alto, CA
- Center for Primary Care and Outcomes Research, Stanford University School of Medicine, 117 Encina Commons, Stanford, CA
| | - Jiaqi Hu
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe Street, Baltimore, MD
| | - Derek Boothroyd
- Quantitative Sciences Unit, Stanford University School of Medicine, 1701 Page Mill Road, Palo Alto, CA
- Center for Innovation to Implementation, VA Palo Alto Health Care System, 795 Willow Road, Menlo Park, CA
| | - Liberty Greene
- Center for Innovation to Implementation, VA Palo Alto Health Care System, 795 Willow Road, Menlo Park, CA
| | - Donna M. Zulman
- Center for Innovation to Implementation, VA Palo Alto Health Care System, 795 Willow Road, Menlo Park, CA
- Division of Primary Care and Population Health, Department of Medicine, Stanford University School of Medicine, Stanford, CA
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Rosen AK, Beilstein-Wedel EE, Harris AHS, Shwartz M, Vanneman ME, Wagner TH, Giori NJ. Comparing Postoperative Readmission Rates Between Veterans Receiving Total Knee Arthroplasty in the Veterans Health Administration Versus Community Care. Med Care 2022; 60:178-186. [PMID: 35030566 DOI: 10.1097/mlr.0000000000001678] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
BACKGROUND There are growing concerns that Veterans' increased use of Veterans Health Administration (VA)-purchased care in the community may lead to lower quality of care. OBJECTIVE We compared rates of hospital readmissions following elective total knee arthroplasties (TKAs) that were either performed in VA or purchased by VA through community care (CC) at both the national and facility levels. METHODS Three-year cohort study using VA and CC administrative data from the VA's Corporate Data Warehouse (October 1, 2016-September 30, 2019). We obtained Medicare data to capture readmissions that were paid by Medicare. We used the Centers for Medicare and Medicaid Services (CMS) methods to identify unplanned, 30-day, all-cause readmissions. A secondary outcome, TKA-related readmissions, identified readmissions resulting from complications of the index surgery. We ran mixed-effects logistic regression models to compare the risk-adjusted odds of all-cause and TKA-related readmissions between TKAs performed in VA versus CC, adjusting for patients' sociodemographic and clinical characteristics. PRINCIPAL FINDINGS Nationally, the odds of experiencing an all-cause or TKA-related readmission were significantly lower for TKAs performed in VA versus CC (eg, the odds of experiencing an all-cause readmission in VA were 35% of those in CC. At the facility level, most VA facilities performed similarly to their corresponding CC providers, although there were 3 VA facilities that performed worse than their corresponding CC providers. CONCLUSIONS Given VA's history in providing high-quality surgical care to Veterans, it is important to closely monitor and track whether the shift to CC for surgical care will impact quality in both settings over time.
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Affiliation(s)
- Amy K Rosen
- Center for Healthcare Organization and Implementation Research (CHOIR), VA Boston Healthcare System
- Department of Surgery, Boston University School of Medicine, Boston, MA
| | - Erin E Beilstein-Wedel
- Center for Healthcare Organization and Implementation Research (CHOIR), VA Boston Healthcare System
| | - Alex H S Harris
- Center for Innovation to Implementation (Ci2i), VA Palo Alto Health Care System, Livermore
- Department of Surgery, Stanford University School of Medicine, Stanford, CA
| | - Michael Shwartz
- Center for Healthcare Organization and Implementation Research (CHOIR), VA Boston Healthcare System
| | - Megan E Vanneman
- Informatics, Decision-Enhancement and Analytic Sciences Center (IDEAS), VA Salt Lake City Health Care System
- Departments of Internal Medicine and Population Health Sciences, University of Utah School of Medicine, Salt Lake City, UT
| | - Todd H Wagner
- Center for Innovation to Implementation (Ci2i), VA Palo Alto Health Care System, Livermore
- Department of Surgery, Stanford University School of Medicine, Stanford, CA
- VA Health Economics Resource Center (HERC), Menlo Park, CA
| | - Nicholas J Giori
- Center for Innovation to Implementation (Ci2i), VA Palo Alto Health Care System, Livermore
- Department of Orthopedic Surgery, Stanford University School of Medicine, Stanford, CA
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Gold HT, McDermott C, Hoomans T, Wagner TH. Cost data in implementation science: categories and approaches to costing. Implement Sci 2022; 17:11. [PMID: 35090508 PMCID: PMC8796347 DOI: 10.1186/s13012-021-01172-6] [Citation(s) in RCA: 34] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2021] [Accepted: 11/03/2021] [Indexed: 12/14/2022] Open
Abstract
A lack of cost information has been cited as a barrier to implementation and a limitation of implementation research. This paper explains how implementation researchers might optimize their measurement and inclusion of costs, building on traditional economic evaluations comparing costs and effectiveness of health interventions. The objective of all economic evaluation is to inform decision-making for resource allocation and to measure costs that reflect opportunity costs—the value of resource inputs in their next best alternative use, which generally vary by decision-maker perspective(s) and time horizon(s). Analyses that examine different perspectives or time horizons must consider cost estimation accuracy, because over longer time horizons, all costs are variable; however, with shorter time horizons and narrower perspectives, one must differentiate the fixed and variable costs, with fixed costs generally excluded from the evaluation. This paper defines relevant costs, identifies sources of cost data, and discusses cost relevance to potential decision-makers contemplating or implementing evidence-based interventions. Costs may come from the healthcare sector, informal healthcare sector, patient, participant or caregiver, and other sectors such as housing, criminal justice, social services, and education. Finally, we define and consider the relevance of costs by phase of implementation and time horizon, including pre-implementation and planning, implementation, intervention, downstream, and adaptation, and through replication, sustainment, de-implementation, or spread.
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Jacobs JC, Maciejeweski ML, Wagner TH, Van Houtven CH, Lo J, Greene L, Zulman DM. Improving Prediction of Long-Term Care Utilization Through Patient-Reported Measures: Cross-Sectional Analysis of High-Need U.S. Veterans Affairs Patients. Med Care Res Rev 2021; 79:676-686. [PMID: 34906010 DOI: 10.1177/10775587211062403] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
This article examines the relative merit of augmenting an electronic health record (EHR)-derived predictive model of institutional long-term care (LTC) use with patient-reported measures not commonly found in EHRs. We used survey and administrative data from 3,478 high-risk Veterans aged ≥65 in the U.S. Department of Veterans Affairs, comparing a model based on a Veterans Health Administration (VA) geriatrics dashboard, a model with additional EHR-derived variables, and a model that added survey-based measures (i.e., activities of daily living [ADL] limitations, social support, and finances). Model performance was assessed via Akaike information criteria, C-statistics, sensitivity, and specificity. Age, a dementia diagnosis, Nosos risk score, social support, and ADL limitations were consistent predictors of institutional LTC use. Survey-based variables significantly improved model performance. Although demographic and clinical characteristics found in many EHRs are predictive of institutional LTC, patient-reported function and partnership status improve identification of patients who may benefit from home- and community-based services.
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Affiliation(s)
- Josephine C Jacobs
- VA Palo Alto Health Care System, Menlo Park, CA, USA.,Stanford University School of Medicine, Stanford, CA, USA
| | | | - Todd H Wagner
- VA Palo Alto Health Care System, Menlo Park, CA, USA.,Stanford University School of Medicine, Stanford, CA, USA
| | | | - Jeanie Lo
- VA Palo Alto Health Care System, Menlo Park, CA, USA
| | - Liberty Greene
- VA Palo Alto Health Care System, Menlo Park, CA, USA.,Stanford University School of Medicine, Stanford, CA, USA
| | - Donna M Zulman
- VA Palo Alto Health Care System, Menlo Park, CA, USA.,Stanford University School of Medicine, Stanford, CA, USA
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Abstract
BACKGROUND More than 50% of postoperative wound complications occur after discharge. They are the most common postoperative complication and the most common reason for readmission after a surgical procedure. Little is known about the long-term costs of postdischarge wound complications after surgery. OBJECTIVE We sought to understand the differences in costs and characteristics of wound complications identified after hospital discharge for patients undergoing colorectal surgery in comparison with in-hospital complications. DESIGN This is an observational cohort study using Veterans Health Administration Surgical Quality Improvement Program data. SETTING This study was conducted at a Veterans Affairs medical center. SETTING Patients undergoing colorectal resection between October 1, 2007 and September 30, 2014. MAIN OUTCOME MEASURES The primary outcomes measured were adjusted costs of care at discharge, 30 days, and 90 days after surgery. RESULTS Of 20,146 procedures, 11.9% had a wound complication within 30 days of surgery (49.2% index-hospital, 50.8% postdischarge). In comparison with patients with index-hospital complications, patients with postdischarge complications had fewer superficial infections (65.0% vs 72.2%, p < 0.01), more organ/space surgical site infections (14.3% vs 10.1%, p < 0.01), and higher rates of diabetes (29.1% vs 25.0%, p = 0.02), and they were to have had a laparoscopic approach for their surgery (24.7% vs 18.2%, p < 0.01). The average cost including surgery at 30 days was $37,315 (SD = $29,319). Compared with index-hospital wound complications, postdischarge wound complications were $9500 (22%, p < 0.001) less expensive at 30 days and $9736 (15%, p < 0.001) less expensive at 90 days. Patients with an index-hospital wound complication were 40% less likely to require readmission at 30 days, but their readmissions were $12,518 more expensive than readmissions among patients with a newly identified postdischarge wound complication (p < 0.001). LIMITATIONS This study was limited to patient characteristics and costs accrued only within the Veterans Affairs system. CONCLUSIONS Patients with postdischarge wound complications have lower 30- and 90-day postoperative costs than those with wound complications identified during their index hospitalization and almost half were managed as an outpatient. TIEMPO Y COSTO DE LAS COMPLICACIONES LA HERIDA DESPUS DE LA RESECCIN COLORRECTAL ANTECEDENTES:Más del 50% de complicaciones postoperatorias de la herida ocurren después del alta. Es la complicación postoperatoria más común y el motivo más frecuente de reingreso después del procedimiento quirúrgico. Poco se sabe sobre los costos a largo plazo de las complicaciones de la herida después del alta quirúrgica.OBJETIVO:Intentar en comprender las diferencias en los costos y las características de las complicaciones de la herida, identificadas después del alta hospitalaria, en pacientes sometidos a cirugía colorrectal, en comparación con las complicaciones intrahospitalarias.DISEÑO:Estudio de cohorte observacional utilizando datos del Programa de Mejora de la Calidad Quirúrgica de la Administración de Salud de Veteranos.ENTORNO CLÍNICO:Administración de Veteranos.PACIENTES:Pacientes sometidos a resección colorrectal entre el 1/10/2007 y el 30/9/2014.PRINCIPALES MEDIDAS DE VALORACIÓN:Costos de atención ajustados al alta, 30 días y 90 días después de la cirugía.RESULTADOS:De 20146 procedimientos, el 11,9% tuvo una complicación de la herida dentro de los 30 días de la cirugía. (49,2% índice hospitalario, 50,8% después del alta). En comparación con los pacientes, del índice de complicaciones hospitalarias, los pacientes con complicaciones posteriores al alta, tuvieron menos infecciones superficiales (65,0% frente a 72,2%, p <0,01), más infecciones de órganos/espacios quirúrgicos (14,3% frente a 10,1%, p <0,01), tasas más altas de diabetes (29,1% versus 25,0%, p = 0,02), y deberían de haber tenido un abordaje laparoscópico para su cirugía (24,7% versus 18,2%, p <0,01). El costo promedio, incluida la cirugía a los 30 días, fue de $ 37,315 (desviación estándar = $ 29,319). En comparación con el índice de complicaciones de las herida hospitalaria, las complicaciones de la herida después del alta fueron $ 9,500 (22%, p <0,001) menor costo a los 30 días y $ 9,736 (15%, p<0,001) y menor costo a los 90 días. Los pacientes con índice de complicación de la herida hospitalaria, tenían un 40% menos de probabilidades de requerir reingreso a los 30 días, pero sus reingresos eran $ 12,518 más costosos que los reingresos entre los pacientes presentando complicación de la herida recién identificada después del alta (p <0,001).LIMITACIONES:Limitado a las características del paciente y los costos acumulados solo dentro del sistema VA.CONCLUSIONES:Pacientes con complicaciones de la herida post alta, tienen menores costos postoperatorios a los 30 y 90 días, que aquellos con complicaciones de la herida identificadas durante su índice de hospitalización y aproximadamente la mitad fueron tratados de forma ambulatoria.
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Affiliation(s)
- Laura A Graham
- Health Economics Resource Center (HERC), VA Palo Alto Health Care System, Palo Alto, California
- Stanford-Surgery Policy Improvement Research and Education Center (S-SPIRE), Department of Surgery, Stanford University, Stanford, California
| | - Todd H Wagner
- Health Economics Resource Center (HERC), VA Palo Alto Health Care System, Palo Alto, California
- Stanford-Surgery Policy Improvement Research and Education Center (S-SPIRE), Department of Surgery, Stanford University, Stanford, California
| | - Tanmaya D Sambare
- Stanford-Surgery Policy Improvement Research and Education Center (S-SPIRE), Department of Surgery, Stanford University, Stanford, California
| | - Mary T Hawn
- Stanford-Surgery Policy Improvement Research and Education Center (S-SPIRE), Department of Surgery, Stanford University, Stanford, California
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Jacobs JC, Wagner TH, Trivedi R, Lorenz K, Van Houtven CH. Long-term care service mix in the Veterans Health Administration after home care expansion. Health Serv Res 2021; 56:1126-1136. [PMID: 34085283 PMCID: PMC8586480 DOI: 10.1111/1475-6773.13687] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Revised: 02/02/2021] [Accepted: 05/07/2021] [Indexed: 11/30/2022] Open
Abstract
OBJECTIVE To determine whether the Veterans Health Administration's (VHA) efforts to expand access to home- and community-based services (HCBS) after the 2001 Millennium Act significantly changed Veterans' utilization of institutional, paid home, and unpaid home care relative to a non-VHA user Medicare population that was not exposed to HCBS expansion efforts. DATA SOURCES We used linkages between the Health and Retirement Study and VHA administrative data from 1998 until 2012. STUDY DESIGN We conducted a retrospective-matched cohort study using coarsened exact matching to ensure balance on observable characteristics for VHA users (n = 943) and nonusers (n = 6106). We used a difference-in-differences approach with a person fixed-effects estimator. DATA COLLECTION/EXTRACTION METHODS Individuals were eligible for inclusion in the analysis if they were age 65 or older and indicated that they were covered by Medicare insurance in 1998. Individuals were excluded if they were covered by Medicaid insurance at baseline. Individuals were considered exposed to VHA HCBS expansion efforts if they were enrolled in the VHA and used VHA services. PRINCIPAL FINDINGS Theory predicts that an increase in the public allocation of HCBS will decrease the utilization of its substitutes (e.g., institutional care and unpaid caregiving). We found that after the Millennium Act was passed, there were no observed differences between VHA users and nonusers in the probability of using institutional long-term care (0.7% points, 95% CI: -0.009, 0.022) or in receiving paid help with activities of daily living (0.06% points, 95% CI: -0.011, 0.0125). VHA users received more hours of unpaid care post-Millennium Act (1.48, 95% CI: -0.232, 3.187), though this effect was not significant once we introduced controls for mental health. CONCLUSIONS Our findings indicate that mandating access to HCBS services does not necessarily imply that access to these services will follow suit.
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Affiliation(s)
- Josephine C. Jacobs
- Health Economics Resource CenterVA Palo Alto Health Care SystemMenlo ParkCaliforniaUSA
- Center for Innovation to Implementation, VA Palo Alto Health Care SystemMenlo ParkCaliforniaUSA
- Division of Primary Care and Outcomes ResearchStanford University School of MedicineStanfordCaliforniaUSA
| | - Todd H. Wagner
- Health Economics Resource CenterVA Palo Alto Health Care SystemMenlo ParkCaliforniaUSA
- Center for Innovation to Implementation, VA Palo Alto Health Care SystemMenlo ParkCaliforniaUSA
- Departments of SurgeryStanford University School of MedicineStanfordCaliforniaUSA
| | - Ranak Trivedi
- Center for Innovation to Implementation, VA Palo Alto Health Care SystemMenlo ParkCaliforniaUSA
- Department of Psychiatry and Behavioral SciencesStanford University School of MedicineStanfordCaliforniaUSA
| | - Karl Lorenz
- Center for Innovation to Implementation, VA Palo Alto Health Care SystemMenlo ParkCaliforniaUSA
- Section of Palliative Care, Division of Primary Care and Population HealthStanford University School of MedicineStanfordCaliforniaUSA
| | - Courtney H. Van Houtven
- Center of Innovation to Accelerate Discovery and Practice TransformationDurham Veterans Affairs Health Care SystemDurhamNorth CarolinaUSA
- Department of Population Health SciencesDuke University School of MedicineDurhamNorth CarolinaUSA
- Duke‐Margolis Center for Health PolicyDuke UniversityDurhamNorth CarolinaUSA
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Elwy AR, Maguire EM, Gallagher TH, Asch SM, Durfee JM, Martinello RA, Bokhour BG, Gifford AL, Taylor TJ, Wagner TH. Risk Communication After Health Care Exposures: An Experimental Vignette Survey With Patients. MDM Policy Pract 2021; 6:23814683211045659. [PMID: 34553068 PMCID: PMC8451260 DOI: 10.1177/23814683211045659] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Accepted: 08/24/2021] [Indexed: 11/19/2022] Open
Abstract
Purpose. We investigated how health care systems should communicate with patients about possible exposures to blood-borne pathogens that may have occurred during their care. Our goal was to determine how best to communicate uncertain risk information in a way that would minimize harm to patients, maintain their trust, and encourage patients to seek follow-up treatment. Methods. Participants (N = 1103) were randomized to receive one of six vignette surveys; 997 (98.4%) responded. All vignettes described the same event, but differed by risk level and recommendations (lower risk v. higher risk) and by communication mode (telephone, letter, social media). We measured participants’ perceived risk of blood-borne infection, trust in the health care system, and shared decision making about next clinical steps. Open-ended questions were analyzed using grounded thematic analysis. Results. When the vignette requested patients to undergo testing and practice certain health behaviors (higher risk), participants’ likelihood of seeking follow-up testing for blood-borne pathogens and their understanding of health issues increased. Perceived trust was unaffected by risk level or communication processes. Qualitative data indicated a desire for telephone communication from providers known to the patient. Limitations. It is not clear whether higher risk language or objective risk levels in vignettes motivated patients’ behavioral intentions. Conclusion. Using higher risk language when disclosing large-scale adverse events increased participants’ willingness to seek follow-up care. Implications. Health care organizations’ disclosures should focus on the next steps to take after health care exposures. This communication should involve helping patients to understand their personal health issues better, make them feel that they know which steps to take following the receipt of this information, and encouraging them to seek follow-up infectious disease testing in order to better take care of themselves.
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Affiliation(s)
- A Rani Elwy
- Center for Healthcare Organization and Implementation Research, VA Bedford Healthcare System, Bedford, Massachusetts
| | - Elizabeth M Maguire
- Center for Healthcare Organization and Implementation Research, VA Bedford Healthcare System, Bedford, Massachusetts
| | - Thomas H Gallagher
- Division of General Internal Medicine, University of Washington, Seattle, Washington
| | - Steven M Asch
- Center for Innovation to Implementation, VA Palo Alto Healthcare System, Menlo Park, California
| | - Janet M Durfee
- Department of Veterans Affairs, Veterans Health Administration, Office of Patient Care Services, Washington, DC
| | - Richard A Martinello
- Yale-New Haven Hospital Departments of Medicine (Infectious Diseases) and Pediatrics, Yale University School of Medicine, New Haven, Connecticut
| | - Barbara G Bokhour
- Center for Healthcare Organization and Implementation Research, VA Bedford Healthcare System, Bedford, Massachusetts
| | - Allen L Gifford
- Center for Healthcare Organization and Implementation Research, VA Boston Health Care System, Jamaica Plain, Massachusetts
| | - Thomas J Taylor
- Center for Innovation to Implementation, VA Palo Alto Healthcare System, Menlo Park, California
| | - Todd H Wagner
- Center for Innovation to Implementation, VA Palo Alto Healthcare System, Menlo Park, California
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Jaramillo JD, Arnow K, Trickey AW, Dickerson K, Wagner TH, Harris AHS, Tran LD, Bereknyei S, Morris AM, Spain DA, Knowlton LM. Acquisition of Medicaid at the time of injury: An opportunity for sustainable insurance coverage. J Trauma Acute Care Surg 2021; 91:249-259. [PMID: 33783416 DOI: 10.1097/ta.0000000000003195] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
INTRODUCTION Uninsured trauma patients are at higher risk of mortality, limited access to postdischarge resources, and catastrophic health expenditure. Hospital Presumptive Eligibility (HPE), enacted with the 2014 Affordable Care Act, enables uninsured patients to be screened and acquired emergency Medicaid at the time of hospitalization. We sought to identify factors associated with successful acquisition of HPE insurance at the time of injury, hypothesizing that patients with higher Injury Severity Score (ISS) (ISS >15) would be more likely to be approved for HPE. METHODS We identified Medicaid and uninsured patients aged 18 to 64 years with a primary trauma diagnosis (International Classification of Diseases, Tenth Revision) in a large level I trauma center between 2015 and 2019. We combined trauma registry data with review of electronic medical records, to determine our primary outcome, HPE acquisition. Descriptive and multivariate analyses were performed. RESULTS Among 2,320 trauma patients, 1,374 (59%) were already enrolled in Medicaid at the time of hospitalization. Among those uninsured at arrival, 386 (40.8%) acquired HPE before discharge, and 560 (59.2%) remained uninsured. Hospital Presumptive Eligibility patients had higher ISS (ISS >15, 14.8% vs. 5.7%; p < 0.001), longer median length of stay (2 days [interquartile range, 0-5 days] vs. 0 [0-1] days, p < 0.001), were more frequently admitted as inpatients (64.5% vs. 33.6%, p < 0.001), and discharged to postacute services (11.9% vs. 0.9%, p < 0.001). Patient, hospital, and policy factors contributed to HPE nonapproval. In adjusted analyses, Hispanic ethnicity (vs. non-Hispanic Whites: aOR, 1.58; p = 0.02) and increasing ISS (p ≤ 0.001) were associated with increased likelihood of HPE approval. CONCLUSION The time of hospitalization due to injury is an underused opportunity for intervention, whereby uninsured patients can acquire sustainable insurance coverage. Opportunities to increase HPE acquisition merit further study nationally across trauma centers. As administrative and trauma registries do not capture information to compare HPE and traditional Medicaid patients, prospective insurance data collection would help to identify targets for intervention. LEVEL OF EVIDENCE Economic, level IV.
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Affiliation(s)
- Joshua D Jaramillo
- From the Division of General Surgery, Department of Surgery (J.D.J., K.D.), Stanford University School of Medicine; Department of Surgery, (K.A., A.W.T., T.H.W., A.H.S.H., L.D.T., S.B., A.M.M., L.M.K.), Stanford-Surgery Policy Improvement Research and Education Center, Stanford University School of Medicine; and Department of Surgery (D.A.S., L.M.K.), Section of Trauma, Surgical Critical Care and Acute Care Surgery (L.M.K.), Stanford University, Stanford, California
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Harris AHS, Beilstein-Wedel EE, Rosen AK, Shwartz M, Wagner TH, Vanneman ME, Giori NJ. Comparing Complication Rates After Elective Total Knee Arthroplasty Delivered Or Purchased By The VA. Health Aff (Millwood) 2021; 40:1312-1320. [PMID: 34339235 DOI: 10.1377/hlthaff.2020.01679] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
The Department of Veterans Affairs (VA) both delivers health care in its own facilities and, increasingly, purchases care for veterans in the community. Policy makers, administrators, health care providers, and veterans frequently face decisions about which services should be delivered versus purchased by the VA. Comparisons of quality across settings are essential if veterans are to receive care that is consistently accessible, patient centered, effective, and safe. We compared risk-adjusted major postoperative complication rates for total knee arthroplasties that were delivered in VA facilities versus purchased from community providers. Overall, adjusted complication rates were significantly lower for arthroplasties delivered by the VA compared with those that were purchased. However, hospital-level comparisons revealed five locations where VA-purchased care outperformed VA-delivered care. As the amount of VA-purchased care continues to increase under the Veterans Access, Choice, and Accountability Act of 2014 and the VA Maintaining Internal Systems and Strengthening Integrated Outside Networks Act of 2018, these results support VA monitoring of overall and local comparative hospital performance to improve the quality of the care that the VA delivers while ensuring optimal outcomes in VA-purchased care.
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Affiliation(s)
- Alex H S Harris
- Alex H. S. Harris is a research career scientist at the Veterans Affairs (VA) Palo Alto Health Care System's Center for Innovation to Implementation, in Menlo Park, California
| | - Erin E Beilstein-Wedel
- Erin E. Beilstein-Wedel is a research scientist at the VA Boston Healthcare System's Center for Healthcare Organization and Implementation Research, in Boston, Massachusetts
| | - Amy K Rosen
- Amy K. Rosen is a senior research career scientist at the VA Boston Healthcare System's Center for Healthcare Organization and Implementation Research
| | - Michael Shwartz
- Michael Shwartz is a research scientist at the VA Boston Healthcare System's Center for Healthcare Organization and Implementation Research
| | - Todd H Wagner
- Todd H. Wagner is the director of the Health Economics Resource Center and assistant director and research career scientist at the VA Palo Alto Health Care System's Center for Innovation to Implementation
| | - Megan E Vanneman
- Megan E. Vanneman is a research scientist at the VA Salt Lake City's Informatics, Decision-Enhancement and Analytic Sciences Center, in Salt Lake City, Utah
| | - Nicholas J Giori
- Nicholas J. Giori is the chief of orthopedic surgery at the VA Palo Alto Health Care System
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Wagner TH, Lo J, Beilstein-Wedel E, Vanneman ME, Shwartz M, Rosen AK. Estimating the Cost of Surgical Care Purchased in the Community by the Veterans Health Administration. MDM Policy Pract 2021; 6:23814683211057902. [PMID: 34820527 PMCID: PMC8606928 DOI: 10.1177/23814683211057902] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Accepted: 10/18/2021] [Indexed: 11/29/2022] Open
Abstract
Background. Veterans' access to Veterans Affairs (VA)-purchased community care expanded due to large increases in funding provided in the 2014 Veterans Choice Act. Objectives. To compare costs between VA-delivered care and VA payments for purchased care for two commonly performed surgeries: total knee arthroplasties (TKAs) and cataract surgeries. Research Design. Descriptive statistics and regressions examining costs in VA-delivered and VA-purchased care (fiscal year [FY] 2018 [October 2017 to September 2018]). Subjects. A total of 13,718 TKAs, of which 6,293 (46%) were performed in VA. A total of 91,659 cataract surgeries, of which 65,799 (72%) were performed in VA. Measures. Costs of VA-delivered care based on activity-based cost estimates; costs of VA-purchased care based on approved and paid claims. Results. Ninety-eight percent of VA-delivered TKAs occurred in inpatient hospitals, with an average cost of $28,969 (SD $10,778). The majority (86%) of VA-purchased TKAs were also performed at inpatient hospitals, with an average payment of $13,339 (SD $23,698). VA-delivered cataract surgeries were performed at hospitals as outpatient procedures, with an average cost of $4,301 (SD $2,835). VA-purchased cataract surgeries performed at hospitals averaged $1,585 (SD $629); those performed at ambulatory surgical centers cost an average of $1,346 (SD $463). We also found significantly higher Nosos risk scores for patients who used VA-delivered versus VA-purchased care. Conclusions. Costs of VA-delivered care were higher than payments for VA-purchased care, but this partly reflects legislative caps limiting VA payments to community providers to Medicare amounts. Higher patient risk scores in the VA could indicate that community providers are reluctant to accept high-risk patients because of Medicare reimbursements, or that VA providers prefer to keep the more complex patients in VA.
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Affiliation(s)
- Todd H. Wagner
- Health Economics Resource Center, VA Palo Alto Health Care System, Menlo Park, California
- Department of Surgery, Stanford University, Stanford, California
| | - Jeanie Lo
- Health Economics Resource Center, VA Palo Alto Health Care System, Menlo Park, California
| | - Erin Beilstein-Wedel
- Center for Healthcare Organization and Implementation Research (CHOIR), VA Boston Healthcare System, Boston, Massachusetts
| | - Megan E. Vanneman
- Informatics, Decision-Enhancement and Analytic Sciences Center, VA Salt Lake City Health Care System, Salt Lake City, Utah
- Division of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, Utah
- Division of Health System Innovation and Research, Department of Population Health Sciences, University of Utah School of Medicine, Salt Lake City, Utah
| | - Michael Shwartz
- Center for Healthcare Organization and Implementation Research (CHOIR), VA Boston Healthcare System, Boston, Massachusetts
| | - Amy K. Rosen
- Center for Healthcare Organization and Implementation Research (CHOIR), VA Boston Healthcare System, Boston, Massachusetts
- Department of Surgery, Boston University School of Medicine, Boston, Massachusetts
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Elwy AR, Maguire EM, McCullough M, George J, Bokhour BG, Durfee JM, Martinello RA, Wagner TH, Asch SM, Gifford AL, Gallagher TH, Walker Y, Sharpe VA, Geppert C, Holodniy M, West G. From implementation to sustainment: A large-scale adverse event disclosure support program generated through embedded research in the Veterans Health Administration. Healthc (Amst) 2021; 8 Suppl 1:100496. [PMID: 34175102 DOI: 10.1016/j.hjdsi.2020.100496] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Received: 10/28/2019] [Revised: 10/25/2020] [Accepted: 11/03/2020] [Indexed: 10/21/2022]
Abstract
In 2008, the Veterans Health Administration published a groundbreaking policy on disclosing large-scale adverse events to patients in order to promote transparent communication in cases where harm may not be obvious or even certain. Without embedded research, the evidence on whether or not implementation of this policy was generating more harm than good among Veteran patients was unknown. Through an embedded research-operations partnership, we conducted four research projects that led to the development of an evidence-based large-scale disclosure toolkit and disclosure support program, and its implementation across VA healthcare. Guided by the Consolidated Framework for Implementation Research, we identified specific activities corresponding to planning, engaging, executing, reflecting and evaluating phases in the process of implementation. These activities included planning with operational leaders to establish a shared research agenda; engaging with stakeholders to discuss early results, establishing buy-in of our efforts and receiving feedback; joining existing operational teams to execute the toolkit implementation; partnering with clinical operations to evaluate the toolkit during real-time disclosures; and redesigning the toolkit to meet stakeholders' needs. Critical lessons learned for implementation success included a need for stakeholder collaboration and engagement, an organizational culture involving a strong belief in evidence, a willingness to embed researchers in clinical operation activities, allowing for testing and evaluation of innovative practices, and researchers open to constructive feedback. At the conclusion of the research, VA operations worked with the researchers to continue to support efforts to spread, scale-up and sustain toolkit use across the VA healthcare system, with the final goal to establish long-term sustainability.
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Affiliation(s)
- A Rani Elwy
- Center for Healthcare Organization and Implementation Research, VA Bedford Healthcare System, Bedford, MA, 01730, USA; Department of Psychiatry and Human Behavior, Warren Alpert Medical School, Brown University, Providence, RI, 02912, USA; Department of Health Law, Policy, and Management, Boston University School of Public Health, Boston, MA, 02118, USA.
| | - Elizabeth M Maguire
- Center for Healthcare Organization and Implementation Research, VA Bedford Healthcare System, Bedford, MA, 01730, USA
| | - Megan McCullough
- Center for Healthcare Organization and Implementation Research, VA Bedford Healthcare System, Bedford, MA, 01730, USA
| | - Judy George
- Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System, Jamaica Plain, MA, 02130, USA
| | - Barbara G Bokhour
- Center for Healthcare Organization and Implementation Research, VA Bedford Healthcare System, Bedford, MA, 01730, USA; Department of Population and Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, MA, 01605, USA
| | - Janet M Durfee
- Department of Veterans Affairs, Veterans Health Administration, Office of Patient Care Services, Washington, DC, USA
| | - Richard A Martinello
- Departments of Medicine (Infectious Diseases) and Pediatrics, Yale University School of Medicine, New Haven, CT, 06510, USA; Yale New Haven Hospital and Yale New Haven Health, Quality and Safety, New Haven, CT, 06510, USA
| | - Todd H Wagner
- Center for Innovation to Implementation, VA Palo Alto Healthcare System, Menlo Park, CA, 94025, USA; Department of Surgery, Stanford University Medical School, Palo Alto, CA, 94305, USA
| | - Steven M Asch
- Center for Innovation to Implementation, VA Palo Alto Healthcare System, Menlo Park, CA, 94025, USA; Department of Primary Care and Population Health, Stanford University School of Medicine, Palo Alto, CA, 94305, USA
| | - Allen L Gifford
- Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System, Jamaica Plain, MA, 02130, USA; Section of General Internal Medicine, Boston University School of Medicine, Boston, MA, 02118, USA
| | - Thomas H Gallagher
- Division of General Internal Medicine, University of Washington, Seattle, WA, 98104, USA
| | - Yuri Walker
- Department of Veterans Affairs, Veterans Health Administration, Office of Quality and Safety, Risk Management Service, Washington, DC. 20420, USA
| | - Virginia A Sharpe
- Department of Veterans Affairs, Veterans Health Administration, National Center for Ethics in Healthcare, Office of Ethics Policy, Washington, DC. 20420, USA
| | - Cynthia Geppert
- Department of Veterans Affairs, Veterans Health Administration, National Center for Ethics in Healthcare, Office of Ethics Policy, Washington, DC. 20420, USA
| | - Mark Holodniy
- Public Health Surveillance & Research Program and Public Health Reference Laboratory, VA Palo Alto Health Care System, Palo Alto, CA, 94304, USA; Department of Medicine (Infectious Diseases), Stanford University School of Medicine, Palo Alto, CA, 94305, USA
| | - Gavin West
- VA Salt Lake City Health Care System, Salt Lake, UT, 84148, USA
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Gordon SH, Beilstein-Wedel E, Rosen AK, Zheng T, Kelley AT, Cook J, Zahakos SS, Wagner TH, Vanneman ME. County-level Predictors of Growth in Community-based Primary Care Use Among Veterans. Med Care 2021; 59:S301-S306. [PMID: 33976080 PMCID: PMC8132896 DOI: 10.1097/mlr.0000000000001555] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Abstract
BACKGROUND The 2014 Choice Act expanded the Veterans Health Administration's (VA) capacity to purchase services for VA enrollees from community providers, yet little is known regarding the growth of Veterans' primary care use in community settings. OBJECTIVES The aim was to measure county-level growth in VA community-based primary care (CBPC) penetration following the Choice Act and to assess whether CBPC penetration increased in rural counties with limited access to VA facilities. DATA AND SAMPLE A total of 3132 counties from VA administrative data from 2015 to 2018, Area Health Resources Files, and County Health Rankings. ANALYSIS We defined the county-level CBPC penetration rate as the proportion of VA-purchased primary care out of all VA-purchased primary care (ie, within and outside VA). We estimated county-level multivariate linear regression models to assess whether rurality and supply of primary care providers and health care facilities were significantly associated with CBPC growth. RESULTS Nationally, CBPC penetration rates increased from 2.7% in 2015 to 7.3% in 2018. The rurality of the county was associated with a 2-3 percentage point (pp) increase in CBPC penetration growth (P<0.001). The presence of a VA facility was associated with a 1.7 pp decrease in CBPC penetration growth (P<0.001), while lower primary care provider supply was associated with a 0.6 pp increase in CBPC growth (P<0.001). CONCLUSION CBPC as a proportion of all VA-purchased primary care was small but increased nearly 3-fold between 2015 and 2018. Greater increases in CBPC penetration were concentrated in rural counties and counties without a VA facility, suggesting that community care may enhance primary care access in rural areas with less VA presence.
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Affiliation(s)
- Sarah H. Gordon
- Partnered Evidence-Based Policy Resource Center, VA Boston Medical Center
- Department of Health Law, Policy, and Management, Boston University School of Public Health
| | - Erin Beilstein-Wedel
- Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System
| | - Amy K. Rosen
- Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System
- Department of Surgery, Boston University School of Medicine, Boston, MA
| | - Tianyu Zheng
- Informatics, Decision-Enhancement and Analytic Sciences Center, VA Salt Lake City Health Care System
- Department of Population Health Sciences, Division of Health System Innovation and Research, University of Utah School of Medicine
| | - Alan Taylor Kelley
- Informatics, Decision-Enhancement and Analytic Sciences Center, VA Salt Lake City Health Care System
- Department of Internal Medicine, Division of General Internal Medicine
| | - James Cook
- Informatics, Decision-Enhancement and Analytic Sciences Center, VA Salt Lake City Health Care System
- Department of Internal Medicine, Division of Epidemiology, University of Utah School of Medicine, Salt Lake City, UT
| | - Sarah S. Zahakos
- Department of Health Law, Policy, and Management, Boston University School of Public Health
| | - Todd H. Wagner
- Health Economics Resource Center, VA Palo Alto Health Care System, Menlo Park CA
- Stanford University Department of Surgery, Palo Alto CA
| | - Megan E. Vanneman
- Informatics, Decision-Enhancement and Analytic Sciences Center, VA Salt Lake City Health Care System
- Department of Population Health Sciences, Division of Health System Innovation and Research, University of Utah School of Medicine
- Department of Internal Medicine, Division of Epidemiology, University of Utah School of Medicine, Salt Lake City, UT
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Pettey WB, Wagner TH, Rosen AK, Beilstein-Wedel E, Shwartz M, Vanneman ME. Comparing Driving Miles for Department of Veterans Affairs-delivered Versus Department of Veterans Affairs-purchased Cataract Surgery. Med Care 2021; 59:S307-S313. [PMID: 33976081 PMCID: PMC8132907 DOI: 10.1097/mlr.0000000000001491] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
BACKGROUND The Veterans Choice Act of 2014 increased the number of Veterans eligible for Department of Veterans Affairs (VA)-purchased care delivered in non-VA community care (CC) facilities. Driving >40 miles from home to a VA facility is a key eligibility criterion for CC. It remains unclear whether this policy change improved geographical access by reducing drive distance for Veterans. OBJECTIVES Describe the driving distance for Veterans receiving cataract surgery in VA and CC facilities, and if they visited the closest-to-home facility or if they drove to farther facilities. SUBJECTS Veterans who had cataract surgery in federal fiscal year 2015. MEASURES We calculated driving miles to the Closest VA and CC facilities that performed cataract surgeries, and to the location where Veterans received care. RESULTS A total of 61,746 Veterans received 83,875 cataract surgeries. More than 50% of CC surgeries occurred farther than the Closest CC facility providing cataract surgery (median Closest CC facility 8.7 miles vs. Actual CC facility, 19.7 miles). Most (57%) Veterans receiving cataract surgery at a VA facility used the Closest VA facility (median Closest VA facility 28.1 miles vs. Actual VA facility at 31.2 miles). In all, 26.1% of CC procedures occurred in facilities farther away than the Closest VA facility. CONCLUSIONS Although many Veterans drove farther than needed to get cataract surgery in CC, this was not true for obtaining care in the VA. Our findings suggest that there may be additional reasons, besides driving distance, that affect whether Veterans choose CC and, if they do, where they seek CC.
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Affiliation(s)
- Warren B.P. Pettey
- Informatics, Decision-Enhancement and Analytic Sciences Center (IDEAS), VA Salt Lake City Health Care System
- Department of Internal Medicine, Division of Epidemiology, University of Utah School of Medicine, Salt Lake City, UT
| | - Todd H. Wagner
- Health Economics Resource Center (HERC), VA Palo Alto Health Care System
- Center for Innovation to Implementation, VA Palo Alto Health Care System, Menlo Park
- Department of Surgery, Stanford University School of Medicine, Palo Alto, CA
| | - Amy K. Rosen
- Center for Healthcare Organization and Implementation Research (CHOIR), VA Boston Healthcare System
- Department of Surgery, Boston University School of Medicine, Boston, MA
| | - Erin Beilstein-Wedel
- Center for Healthcare Organization and Implementation Research (CHOIR), VA Boston Healthcare System
| | - Michael Shwartz
- Center for Healthcare Organization and Implementation Research (CHOIR), VA Boston Healthcare System
| | - Megan E. Vanneman
- Informatics, Decision-Enhancement and Analytic Sciences Center (IDEAS), VA Salt Lake City Health Care System
- Department of Internal Medicine, Division of Epidemiology, University of Utah School of Medicine, Salt Lake City, UT
- Department of Population Health Sciences, Division of Health System Innovation and Research, University of Utah School of Medicine, Salt Lake City, UT
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Rose L, Graham L, Koenecke A, Powell M, Xiong R, Shen Z, Mench B, Kinzler KW, Bettegowda C, Vogelstein B, Athey S, Vogelstein JT, Konig MF, Wagner TH. The Association Between Alpha-1 Adrenergic Receptor Antagonists and In-Hospital Mortality From COVID-19. Front Med (Lausanne) 2021; 8:637647. [PMID: 33869251 PMCID: PMC8048524 DOI: 10.3389/fmed.2021.637647] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Accepted: 02/25/2021] [Indexed: 12/15/2022] Open
Abstract
Effective therapies for coronavirus disease 2019 (COVID-19) are urgently needed, and pre-clinical data suggest alpha-1 adrenergic receptor antagonists (α1-AR antagonists) may be effective in reducing mortality related to hyperinflammation independent of etiology. Using a retrospective cohort design with patients in the Department of Veterans Affairs healthcare system, we use doubly robust regression and matching to estimate the association between baseline use of α1-AR antagonists and likelihood of death due to COVID-19 during hospitalization. Having an active prescription for any α1-AR antagonist (tamsulosin, silodosin, prazosin, terazosin, doxazosin, or alfuzosin) at the time of admission had a significant negative association with in-hospital mortality (relative risk reduction 18%; odds ratio 0.73; 95% CI 0.63–0.85; p ≤ 0.001) and death within 28 days of admission (relative risk reduction 17%; odds ratio 0.74; 95% CI 0.65–0.84; p ≤ 0.001). In a subset of patients on doxazosin specifically, an inhibitor of all three alpha-1 adrenergic receptors, we observed a relative risk reduction for death of 74% (odds ratio 0.23; 95% CI 0.03–0.94; p = 0.028) compared to matched controls not on any α1-AR antagonist at the time of admission. These findings suggest that use of α1-AR antagonists may reduce mortality in COVID-19, supporting the need for randomized, placebo-controlled clinical trials in patients with early symptomatic infection.
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Affiliation(s)
- Liam Rose
- Department of Veterans Affairs Health Economics Resource Center, Palo Alto VA, Menlo Park, CA, United States
| | - Laura Graham
- Department of Veterans Affairs Health Economics Resource Center, Palo Alto VA, Menlo Park, CA, United States
| | - Allison Koenecke
- Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA, United States
| | - Michael Powell
- Department of Biomedical Engineering, Institute for Computational Medicine, The Johns Hopkins University, Baltimore, MD, United States
| | - Ruoxuan Xiong
- Department of Management Science and Engineering, Stanford University, Stanford, CA, United States
| | - Zhu Shen
- Department of Statistics, Stanford University, Stanford, CA, United States
| | - Brett Mench
- Department of Biomedical Engineering, Institute for Computational Medicine, The Johns Hopkins University, Baltimore, MD, United States
| | - Kenneth W Kinzler
- Lustgarten Laboratory, Ludwig Center, Howard Hughes Medical Institute at The Johns Hopkins Kimmel Cancer Center, Baltimore, MD, United States
| | - Chetan Bettegowda
- Lustgarten Laboratory, Ludwig Center, Howard Hughes Medical Institute at The Johns Hopkins Kimmel Cancer Center, Baltimore, MD, United States.,Department of Neurosurgery and Oncology, The Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Bert Vogelstein
- Lustgarten Laboratory, Ludwig Center, Howard Hughes Medical Institute at The Johns Hopkins Kimmel Cancer Center, Baltimore, MD, United States
| | - Susan Athey
- Stanford Graduate School of Business, Stanford University, Stanford, CA, United States
| | - Joshua T Vogelstein
- Department of Biomedical Engineering, Institute for Computational Medicine, The Johns Hopkins University, Baltimore, MD, United States.,Department of Biostatistics, The Johns Hopkins Bloomberg School of Public Health at The Johns Hopkins University, Baltimore, MD, United States
| | - Maximilian F Konig
- Lustgarten Laboratory, Ludwig Center, Howard Hughes Medical Institute at The Johns Hopkins Kimmel Cancer Center, Baltimore, MD, United States.,Division of Rheumatology, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Todd H Wagner
- Department of Veterans Affairs Health Economics Resource Center, Palo Alto VA, Menlo Park, CA, United States.,Department of Surgery, Stanford University, Stanford, CA, United States
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Zenati MA, Bhatt DL, Stock EM, Hattler B, Wagner TH, Bakaeen FG, Biswas K. Intermediate-Term Outcomes of Endoscopic or Open Vein Harvesting for Coronary Artery Bypass Grafting: The REGROUP Randomized Clinical Trial. JAMA Netw Open 2021; 4:e211439. [PMID: 33720367 PMCID: PMC7961312 DOI: 10.1001/jamanetworkopen.2021.1439] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/03/2023] Open
Abstract
This randomized clinical trial examines intermediate-term outcomes of endoscopic vs open vein harvesting for coronary artery bypass grafting as part of the Randomized Endo-Vein Graft Perspective (REGROUP) trial.
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Affiliation(s)
- Marco A. Zenati
- Division of Cardiac Surgery, Department of Surgery, Veterans Affairs Boston Healthcare System, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
| | - Deepak L. Bhatt
- Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
| | - Eileen M. Stock
- Cooperative Studies Program, Perry Point/Baltimore Coordinating Center, Office of Research and Development, US Department of Veterans Affairs, Perry Point, Maryland
| | | | - Todd H. Wagner
- VA Health Economics Resource Center, Department of Surgery, Stanford University, Palo Alto, California
| | | | - Kousick Biswas
- Perry Point Cooperative Studies Program Coordinating Center, Office of Research and Development, US Department of Veterans Affairs, Perry Point, Maryland
- Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore
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Rose L, Graham L, Koenecke A, Powell M, Xiong R, Shen Z, Kinzler KW, Bettegowda C, Vogelstein B, Athey S, Vogelstein JT, Konig MF, Wagner TH. The Association Between Alpha-1 Adrenergic Receptor Antagonists and In-Hospital Mortality from COVID-19. medRxiv 2021. [PMID: 33398294 PMCID: PMC7781337 DOI: 10.1101/2020.12.18.20248346] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Effective therapies for coronavirus disease 2019 (COVID-19) are urgently needed, and preclinical data suggest alpha-1 adrenergic receptor antagonists (α1-AR antagonists) may be effective in reducing mortality related to hyperinflammation independent of etiology. Using a retrospective cohort design with patients in the Department of Veterans Affairs healthcare system, we use doubly robust regression and matching to estimate the association between baseline use of α1-AR antagonists and likelihood of death due to COVID-19 during hospitalization. Having an active prescription for any α1-AR antagonist (tamsulosin, silodosin, prazosin, terazosin, doxazosin, or alfuzosin) at the time of admission had a significant negative association with in-hospital mortality (relative risk reduction 18%; odds ratio 0.73; 95% CI 0.63 to 0.85; p ≤ 0.001) and death within 28 days of admission (relative risk reduction 17%; odds ratio 0.74; 95% CI 0.65 to 0.84; p ≤ 0.001). In a subset of patients on doxazosin specifically, an inhibitor of all three alpha-1 adrenergic receptors, we observed a relative risk reduction for death of 74% (odds ratio 0.23; 95% CI 0.03 to 0.94; p = 0.028) compared to matched controls not on any α1-AR antagonist at the time of admission. These findings suggest that use of α1-AR antagonists may reduce mortality in COVID-19, supporting the need for randomized, placebo-controlled clinical trials in patients with early symptomatic infection.
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Affiliation(s)
- Liam Rose
- VA Health Economics Resource Center, Palo Alto VA, Menlo Park, CA, USA
| | - Laura Graham
- VA Health Economics Resource Center, Palo Alto VA, Menlo Park, CA, USA
| | - Allison Koenecke
- Institute for Computational & Mathematical Engineering, Stanford University, Stanford, CA, USA
| | - Michael Powell
- Department of Biomedical Engineering, Institute for Computational Medicine, The Johns Hopkins University, Baltimore, MD, USA
| | - Ruoxuan Xiong
- Management Science & Engineering, Stanford University, Stanford, CA, USA
| | - Zhu Shen
- Department of Statistics, Stanford University, Stanford, CA, USA
| | - Kenneth W Kinzler
- Ludwig Center, Lustgarten Laboratory, and the Howard Hughes Medical Institute at The Johns Hopkins Kimmel Cancer Center, Baltimore, MD, USA
| | - Chetan Bettegowda
- Ludwig Center, Lustgarten Laboratory, and the Howard Hughes Medical Institute at The Johns Hopkins Kimmel Cancer Center, Baltimore, MD, USA.,The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Bert Vogelstein
- Ludwig Center, Lustgarten Laboratory, and the Howard Hughes Medical Institute at The Johns Hopkins Kimmel Cancer Center, Baltimore, MD, USA
| | - Susan Athey
- Stanford Graduate School of Business, Stanford University, Stanford, CA, USA
| | - Joshua T Vogelstein
- Department of Biomedical Engineering, Institute for Computational Medicine, The Johns Hopkins University, Baltimore, MD, USA.,Department of Biostatistics, The Johns Hopkins Bloomberg School of Public Health at The Johns Hopkins University, Baltimore, MD, USA
| | - Maximilian F Konig
- Ludwig Center, Lustgarten Laboratory, and the Howard Hughes Medical Institute at The Johns Hopkins Kimmel Cancer Center, Baltimore, MD, USA.,Division of Rheumatology, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, MD, US
| | - Todd H Wagner
- VA Health Economics Resource Center, Palo Alto VA, Menlo Park, CA, USA.,Department of Surgery, Stanford University, Stanford, CA, USA
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Mudumbai SC, Chung P, Nguyen N, Harris B, Clark JD, Wagner TH, Giori NJ, Stafford RS, Mariano ER. Perioperative Opioid Prescribing Patterns and Readmissions After Total Knee Arthroplasty in a National Cohort of Veterans Health Administration Patients. Pain Med 2021; 21:595-603. [PMID: 31309970 DOI: 10.1093/pm/pnz154] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
OBJECTIVE Among Veterans Health Administration (VHA) patients who undergo total knee arthroplasty (TKA) nationally, what are the underlying readmission rates and associations with perioperative opioid use, and are there associations with other factors such as preoperative health care utilization? METHODS We retrospectively examined the records of 5,514 TKA patients (primary N = 4,955, 89.9%; revision N = 559, 10.1%) over one fiscal year (October 1, 2010-September 30, 2011) across VHA hospitals nationwide. Opioid use was classified into no opioids, tramadol only, short-acting only, or any long-acting. We measured readmission within 30 days and the number of days to readmission within 30 days. Extended Cox regression models were developed. RESULTS The overall 30-day hospital readmission rate was 9.6% (N = 531; primary 9.5%, revision 11.1%). Both readmitted patients and the overall sample were similar on types of preoperative opioid use. Relative to patients without opioids, patients in the short-acting opioids only tier had the highest risk for 30-day hospital readmission (hazard ratio = 1.38, 95% confidence interval = 1.14-1.67). Preoperative opioid status was not associated with 30-day readmission. Other risk factors for 30-day readmission included older age (≥66 years), higher comorbidity and diagnosis-related group weights, greater preoperative health care utilization, an urban location, and use of preoperative anticonvulsants. CONCLUSIONS Given the current opioid epidemic, the routine prescribing of short-acting opioids after surgery should be carefully considered to avoid increasing risks of 30-day hospital readmissions and other negative outcomes, particularly in the context of other predisposing factors.
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Affiliation(s)
- Seshadri C Mudumbai
- Anesthesiology and Perioperative Care Service, Veterans Affairs Palo Alto Health Care System, Palo Alto, California.,Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, California
| | | | | | | | - J David Clark
- Anesthesiology and Perioperative Care Service, Veterans Affairs Palo Alto Health Care System, Palo Alto, California.,Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, California
| | - Todd H Wagner
- Center for Innovation to Implementation.,Health Economics Resource Center, Veterans Affairs Palo Alto Health Care System, Menlo Park, California.,Department of Surgery, Stanford University School of Medicine, Stanford, California
| | - Nicholas J Giori
- Orthopaedic Surgery Section, Surgical Service, Veterans Affairs Palo Alto Health Care System, Palo Alto, California.,Departments of Orthopaedic Surgery
| | - Randall S Stafford
- Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Edward R Mariano
- Anesthesiology and Perioperative Care Service, Veterans Affairs Palo Alto Health Care System, Palo Alto, California.,Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, California
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Gidwani R, Asch SM, Needleman J, Faricy-Anderson K, Boothroyd DB, Illarmo S, Lorenz KA, Patel MI, Hsin G, Ramchandran K, Wagner TH. End-of-Life Cost Trajectories in Cancer Patients Treated by Medicare versus the Veterans Health Administration. J Am Geriatr Soc 2020; 69:916-923. [PMID: 33368171 DOI: 10.1111/jgs.16941] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2020] [Revised: 09/29/2020] [Accepted: 10/13/2020] [Indexed: 11/29/2022]
Abstract
BACKGROUND/OBJECTIVES To evaluate differences in end-of-life cost trajectories for cancer patients treated through Medicare versus by the Veterans Health Administration (VA). DESIGN A retrospective analysis of VA and Medicare administrative data from FY 2010 to 2014. We employed three-level generalized estimating equations to evaluate monthly cost trajectories experienced by patients in their last year of life, with patients nested within hospital referral region. SETTING Care received at VA facilities or by Medicare-reimbursed providers nationwide. PARTICIPANTS A total of 36,401 patients dying from cancer and dually enrolled in VA and Medicare. MEASUREMENTS We evaluated trajectories for total, inpatient, outpatient, and drug costs, using the last 12 months of life. Cost trajectories were prioritized as costs are not directly comparable across Medicare and VA. Patients were assigned to be VA-reliant, Medicare-reliant or Mixed-reliant based on their healthcare utilization in the last year of life. RESULTS All three groups experienced significantly different cost trajectories for total costs in the last year of life. Inpatient cost trajectories were significantly different between Medicare-reliant and VA-reliant patients, but did not differ between VA-reliant and Mixed-reliant patients. Outpatient and drug cost trajectories exhibited the inverse pattern: they were significantly different between VA-reliant and Mixed-reliant patients, but not between VA-reliant and Medicare-reliant patients. However, visual examination of cost trajectories revealed similar cost patterns in the last year of life among all three groups; there was a sharp rise in costs as patients approach death, largely due to inpatient care. CONCLUSION Despite substantially different financial incentives and organization, VA- and Medicare-treated patients exhibit similar patterns of increasing end-of-life costs, largely driven by inpatient costs. Both systems require improvement to ensure quality of end-of-life care is aligned with recommended practice.
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Affiliation(s)
- Risha Gidwani
- Health Economics Resource Center, VA Palo Alto Health Care System, Palo Alto, California, USA.,Center for Innovation to Implementation, VA Palo Alto Health Care System, Palo Alto, California, USA.,Department of Health Policy and Management, UCLA Fielding School of Public Health, University of California, Los Angeles, California, USA
| | - Steven M Asch
- Center for Innovation to Implementation, VA Palo Alto Health Care System, Palo Alto, California, USA.,Division of Primary Care and Population Health, Stanford University School of Medicine, Stanford, California, USA
| | - Jack Needleman
- Department of Health Policy and Management, UCLA Fielding School of Public Health, University of California, Los Angeles, California, USA
| | - Katherine Faricy-Anderson
- Providence VA Medical Center, Providence, Rhode Island, USA.,Alpert Medical School, Brown University, Providence, Rhode Island, USA
| | - Derek B Boothroyd
- Quantitative Sciences Unit, Department of Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Samantha Illarmo
- Health Economics Resource Center, VA Palo Alto Health Care System, Palo Alto, California, USA
| | - Karl A Lorenz
- Center for Innovation to Implementation, VA Palo Alto Health Care System, Palo Alto, California, USA.,Division of Primary Care and Population Health, Stanford University School of Medicine, Stanford, California, USA
| | - Manali I Patel
- Center for Health Policy/Center for Primary Care and Outcomes Research, Stanford University School of Medicine, Stanford, California, USA.,VA Palo Alto Health Care System, Palo Alto, California, USA.,Division of Oncology, Stanford University School of Medicine, Stanford, California, USA
| | - Gary Hsin
- Division of Primary Care and Population Health, Stanford University School of Medicine, Stanford, California, USA.,VA Palo Alto Health Care System, Palo Alto, California, USA
| | - Kavitha Ramchandran
- Division of Oncology, Stanford University School of Medicine, Stanford, California, USA
| | - Todd H Wagner
- Health Economics Resource Center, VA Palo Alto Health Care System, Palo Alto, California, USA.,Center for Innovation to Implementation, VA Palo Alto Health Care System, Palo Alto, California, USA.,Department of Surgery, Stanford University, Stanford, California, USA
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Sohlberg EM, Thomas IC, Yang J, Kapphahn K, Velaer KN, Goldstein MK, Wagner TH, Chertow GM, Brooks JD, Patel CJ, Desai M, Leppert JT. Laboratory-wide association study of survival with prostate cancer. Cancer 2020; 127:1102-1113. [PMID: 33237577 DOI: 10.1002/cncr.33341] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2020] [Revised: 08/27/2020] [Accepted: 10/13/2020] [Indexed: 12/13/2022]
Abstract
BACKGROUND Estimates of overall patient health are essential to inform treatment decisions for patients diagnosed with cancer. The authors applied XWAS methods, herein referred to as "laboratory-wide association study (LWAS)", to evaluate associations between routinely collected laboratory tests and survival in veterans with prostate cancer. METHODS The authors identified 133,878 patients who were diagnosed with prostate cancer between 2000 and 2013 in the Veterans Health Administration using any laboratory tests collected within 6 months of diagnosis (3,345,083 results). Using the LWAS framework, the false-discovery rate was used to test the association between multiple laboratory tests and survival, and these results were validated using training, testing, and validation cohorts. RESULTS A total of 31 laboratory tests associated with survival met stringent LWAS criteria. LWAS confirmed markers of prostate cancer biology (prostate-specific antigen: hazard ratio [HR], 1.07 [95% confidence interval (95% CI), 1.06-1.08]; and alkaline phosphatase: HR, 1.22 [95% CI, 1.20-1.24]) as well laboratory tests of general health (eg, serum albumin: HR, 0.78 [95% CI, 0.76-0.80]; and creatinine: HR, 1.05 [95% CI, 1.03-1.07]) and inflammation (leukocyte count: HR, 1.23 [95% CI, 1.98-1.26]; and erythrocyte sedimentation rate: HR, 1.33 [95% CI, 1.09-1.61]). In addition, the authors derived and validated separate models for patients with localized and advanced disease, identifying 28 laboratory markers and 15 laboratory markers, respectively, in each cohort. CONCLUSIONS The authors identified routinely collected laboratory data associated with survival for patients with prostate cancer using LWAS methodologies, including markers of prostate cancer biology, overall health, and inflammation. Broadening consideration of determinants of survival beyond those related to cancer itself could help to inform the design of clinical trials and aid in shared decision making. LAY SUMMARY This article examined routine laboratory tests associated with survival among veterans with prostate cancer. Using laboratory-wide association studies, the authors identified 31 laboratory tests associated with survival that can be used to inform the design of clinical trials and aid patients in shared decision making.
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Affiliation(s)
- Ericka M Sohlberg
- Department of Urology, Stanford University School of Medicine, Stanford, California
| | - I-Chun Thomas
- Veterans Affairs Palo Alto Health Care System, Palo Alto, California
| | - Jaden Yang
- Quantitative Sciences Unit, Department of Medicine, Stanford University School of Medicine, Stanford, California
| | - Kristopher Kapphahn
- Quantitative Sciences Unit, Department of Medicine, Stanford University School of Medicine, Stanford, California
| | - Kyla N Velaer
- Department of Urology, Stanford University School of Medicine, Stanford, California
| | - Mary K Goldstein
- Veterans Affairs Palo Alto Health Care System, Palo Alto, California.,Department of Medicine, Stanford University School of Medicine, Stanford, California
| | - Todd H Wagner
- Veterans Affairs Palo Alto Health Care System, Palo Alto, California.,Department of Surgery, Stanford University School of Medicine, Stanford, California
| | - Glenn M Chertow
- Department of Medicine, Stanford University School of Medicine, Stanford, California
| | - James D Brooks
- Department of Urology, Stanford University School of Medicine, Stanford, California
| | - Chirag J Patel
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts
| | - Manisha Desai
- Quantitative Sciences Unit, Department of Medicine, Stanford University School of Medicine, Stanford, California
| | - John T Leppert
- Department of Urology, Stanford University School of Medicine, Stanford, California.,Veterans Affairs Palo Alto Health Care System, Palo Alto, California.,Department of Medicine, Stanford University School of Medicine, Stanford, California
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Abstract
BACKGROUND Hospitals and other health care delivery organizations are sometimes resistant to implementing evidence-based programs, citing unknown budgetary implications. OBJECTIVE In this paper, I discuss challenges when estimating health care costs in implementation research. DESIGN A case study with intensive care units highlights how including fixed costs can cloud a short-term analysis. PARTICIPANTS None. INTERVENTIONS None. MAIN MEASURES Health care costs, charges and payments. KEY RESULTS Cost data should accurately reflect the opportunity costs for the organization(s) providing care. Opportunity costs are defined as the benefits foregone because the resources were not used in the next best alternative. Because there is no database of opportunity costs, cost studies rely on accounting data, charges, or payments as proxies. Unfortunately, these proxies may not reflect the organization's opportunity costs, especially if the goal is to understand the budgetary impact in the next few years. CONCLUSIONS Implementation researchers should exclude costs that are fixed in the time period of observation because these assets (e.g., space) cannot be used in the next best alternative. In addition, it is common to use costs from accounting databases where we implicitly assume health care providers are uniformly efficient. If providers are not operating efficiently, especially if there is variation in their efficiency, then this can create further problems. Implementation scientists should be judicious in their use of cost estimates from accounting data, otherwise research results can misguide decision makers.
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Affiliation(s)
- Todd H Wagner
- VA Health Economics Resource Center, 795 Willow Rd., 152-MPD, Menlo Park, CA, 94025, USA.
- Stanford-Surgery Policy Improvement Research and Education Center, Department of Surgery, Stanford School of Medicine , Stanford, CA, USA.
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Abstract
Health care systems frequently have to decide whether to implement interventions designed to reduce gaps in the quality of care. A lack of information on the cost of these interventions is often cited as a barrier to implementation. In this article, we describe methods for estimating the cost of implementing a complex intervention. We review methods related to the direct measurement of labor, supplies and space, information technology, and research costs. We also discuss several issues that affect cost estimates in implementation studies, including factor prices, fidelity, efficiency and scale of production, distribution, and sunk costs. We examine case studies for stroke and depression, where evidence-based treatments exist and yet gaps in the quality of care remain. Understanding the costs for implementing strategies to reduce these gaps and measuring them consistently will better inform decision makers about an intervention's likely effect on their budget and the expected costs to implement new interventions.
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Affiliation(s)
- Todd H Wagner
- Health Economics Resource Center, US Department of Veterans Affairs (VA) Palo Alto Health Care System, Menlo Park, CA, USA.,Department of Surgery, Stanford University, Stanford, CA, USA
| | - Jean Yoon
- Health Economics Resource Center, US Department of Veterans Affairs (VA) Palo Alto Health Care System, Menlo Park, CA, USA
| | - Josephine C Jacobs
- Health Economics Resource Center, US Department of Veterans Affairs (VA) Palo Alto Health Care System, Menlo Park, CA, USA
| | - Angela So
- Health Economics Resource Center, US Department of Veterans Affairs (VA) Palo Alto Health Care System, Menlo Park, CA, USA
| | - Amy M Kilbourne
- US Department of Veterans Affairs (VA) Quality Enhancement Research Initiative, Washington, DC, USA.,University of Michigan Medical School, Department of Learning Health Sciences, Ann Arbor, MI, USA
| | - Wei Yu
- Health Economics Resource Center, US Department of Veterans Affairs (VA) Palo Alto Health Care System, Menlo Park, CA, USA
| | - David E Goodrich
- Center for Evaluation and Implementation Resources, US Department of Veterans Affairs (VA), Ann Arbor, MI, USA.,Center for Clinical Management Research, US Department of Veterans Affairs (VA) Ann Arbor Healthcare System, Ann Arbor, MI, USA
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