Perioperative Opioid Prescribing Patterns and Readmissions After Total Knee Arthroplasty in a National Cohort of Veterans Health Administration Patients

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.

End-of-Life Cost Trajectories in Cancer Patients Treated by Medicare versus the Veterans Health Administration

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.

Laboratory-wide association study of survival with prostate cancer

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.

Rethinking How We Measure Costs in Implementation Research

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.

Estimating Costs of an Implementation Intervention

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.

Comparing cataract surgery complication rates in veterans receiving VA and community care

OBJECTIVES

To compare 90-day postoperative complication rates between Veterans receiving cataract surgery in VA vs Community Care (CC) during the first year of implementation of the Veterans Choice Act.

DATA SOURCES

Fiscal Year (FY) 2015 VA and CC outpatient data from VA's Corporate Data Warehouse (CDW) 10/01/14-9/30/15). FY14 data were used to obtain baseline clinical information prior to surgery.

STUDY DESIGN

Retrospective one-year study using secondary data to compare 90-day complication rates following cataract surgery (measured using National Quality Forum (NQF) criteria) in VA vs CC. NQF defines major complications from a specified list of Current Procedural Terminology (CPT) codes. We ran a series of logistic regression models to predict 90-day complication rates, adjusting for Veterans' sociodemographic characteristics, comorbidities, preoperative ocular conditions, eye risk group, and type of cataract surgery (classified as routine vs complex).

DATA COLLECTION

We linked VA and CC users through patient identifiers obtained from the CDW files. Our sample included all enrolled Veterans who received outpatient cataract surgery either in the VA or through CC during FY15. Cataract surgeries were identified through CPT codes 66 984 (routine) and 66 982 (complex).

PRINCIPAL FINDINGS

Of the 83,879 cataract surgeries performed in FY15, 31 percent occurred through CC. Undergoing complex surgery and having a high-risk eye (based on preoperative ocular conditions) were the strongest clinical predictors of 90-day postoperative complications. Overall, we found low complication rates, ranging from 1.1 percent in low-risk eyes to 3.6 percent in high-risk eyes. After adjustment for important confounders (eg, race, rurality, and preoperative ocular conditions), there were no statistically significant differences in 90-day complication rates between Veterans receiving cataract surgery in VA vs CC.

CONCLUSIONS

As more Veterans seek care through CC, future studies should continue to monitor quality of care across the two care settings to help inform VA's "make vs buy decisions."

Impact of 12 step mutual help groups on drug use disorder patients across six clinical trials

BACKGROUND

12 step mutual help groups are widely accessed by people with drug use disorder but infrequently subjected to rigorous evaluation. Pooling randomized trials containing a condition in which mutual help group attendance is actively facilitated presents an opportunity to assess the effectiveness of 12 step groups in large, diverse samples of drug use disorder patients.

METHODS

Data from six federally-funded randomized trials were pooled (n = 1730) and subjected to two-stage instrumental variables modelling, and, fixed and random effects regression models. All trials included a 12 step group facilitation condition and employed the Addiction Severity Index as a core measure.

RESULTS

The ability of 12 step facilitation to increase mutual help group participation among drug use disorder patients was minimal, limiting ability to employ two-stage instrumental variable models that correct for selection bias. However, traditional fixed and random effect regression models found that greater 12 step mutual help group attendance by drug use disorder patients predicted reduced use of and problems with illicit drugs and also with alcohol.

CONCLUSION

Facilitating significant and lasting involvement in 12 step groups may be more challenging for drug use disorder patients than for alcohol use disorder patients, which has important implications for clinical work and for effectiveness evaluations. Though selection bias could explain part of the results of traditional regression models, the finding that participation in 12 step mutual help groups predicts lower illicit drug and alcohol use and problems in a large, diverse, sample of drug use disorder patients is encouraging.

Estimating Downstream Budget Impacts in Implementation Research

Health care decision makers often request information showing how a new treatment or intervention will affect their budget (i.e., a budget impact analysis; BIA). In this article, we present key topics for considering how to measure downstream health care costs, a key component of the BIA, when implementing an evidence-based program designed to reduce a quality gap. Tracking health care utilization can be done with administrative or self-reported data, but estimating costs for these utilization data raises 2 issues that are often overlooked in implementation science. The first issue has to do with applicability: are the cost estimates applicable to the health care system that is implementing the quality improvement program? We often use national cost estimates or average payments, without considering whether these cost estimates are appropriate. Second, we need to determine the decision maker's time horizon to identify the costs that vary in that time horizon. If the BIA takes a short-term time horizon, then we should focus on costs that vary in the short run and exclude costs that are fixed over this time. BIA is an increasingly popular tool for health care decision makers interested in understanding the financial effect of implementing an evidence-based program. Without careful consideration of some key conceptual issues, we run the risk of misleading decision makers when presenting results from implementation studies.

Are EMS bypass policies effective implementation strategies for intravenous alteplase for stroke?

Background

Stroke is a leading cause of disability and the fifth leading cause of death in the USA. Intravenous alteplase is a highly effective clot-dissolving stroke treatment that must be given in a hospital setting within a time-sensitive window. To increase the use of intravenous alteplase in stroke patients, many US counties enacted policies mandating emergency medical service (EMS) paramedics to bypass local emergency departments and instead directly transport patients to specially equipped stroke centers. The objective of this mixed-methods study is to evaluate the effectiveness of policy enactment as an implementation strategy, how differences in policy structures and processes impact effectiveness, and to explore how the county, hospital, and policy factors explain variation in implementation and clinical outcomes. This paper provides a detailed description of an Agency for Healthcare Quality and Research (AHRQ)-funded protocol, including the use of the Consolidated Framework for Implementation Research (CFIR) in the qualitative design.

Methods/design

We will construct the largest-ever national stroke database of Medicare enrollees (~ 1.5 million stroke patients) representing 896 policy counties paired with 1792 non-policy counties, then integrate patient-, hospital-, county-, and state-level covariates from eight different data sources. We will use a difference-in-differences analysis to estimate the overall effect of the policy enactment on intravenous alteplase use (implementation outcome) as well as key patient outcomes. We will also quantitatively examine if variation in the context (urban/rural status) and variation in policy features affect outcomes. Finally, a CFIR-informed multiple case study design will be used to interview informants in 72 stakeholders in 24 counties to identify and validate factors that enable policy effects.

Discussion

Policies can be potent implementation strategies. However, the effects of EMS bypass policies to increase intravenous alteplase use have not been rigorously evaluated. By learning how context and policy structures impact alteplase implementation, as well as the barriers and facilitators experienced by stakeholders responsible for policy enactment, the results of this study will inform decisions regarding if and how EMS bypass policies should spread to non-policy counties, and if indicated, creation of a "best practices" toolkit.

Acute pain after breast surgery and reconstruction: A two-institution study of surgical factors influencing short-term pain outcomes

BACKGROUND AND OBJECTIVES

Acute postoperative pain following surgery is known to be associated with chronic pain development and lower quality of life. We sought to analyze the relationship between differing breast cancer excisional procedures, reconstruction, and short-term pain outcomes.

METHODS

Women undergoing breast cancer excisional procedures with or without reconstruction at two systems: an academic hospital (AH) and Veterans Health Administration (VHA) were included. Average pain scores at the time of discharge and at 30-day follow-up were analyzed across demographic and clinical characteristics. Linear mixed effects modeling was used to assess the relationship between patient/clinical characteristics and interval pain scores with a random slope to account for differences in baseline pain.

RESULTS

Our study included 1402 patients at AH and 1435 at VHA, of which 426 AH and 165 patients with VHA underwent reconstruction. Pain scores improved over time and were found to be highest at discharge. Time at discharge, 30-day follow-up, and preoperative opioid use were the strongest predictors of high pain scores. Younger age and longer length of stay were independently associated with worse pain scores.

CONCLUSIONS

Younger age, preoperative opioid use, and longer length of stay were associated with higher levels of postoperative pain across both sites.

Veterans' Experiences With Outpatient Care: Comparing The Veterans Affairs System With Community-Based Care

Timely access to outpatient care was a primary driver behind the Department of Veterans Affairs' (VA's) increased purchase of community-based care under the Veterans Access, Choice, and Accountability Act of 2014, known as the Choice Act. To compare veterans' experiences in VA-delivered and community-based outpatient care after implementation of the act, we assessed veterans' scores on four dimensions of experience-access, communication, coordination, and provider rating-for outpatient specialty, primary, and mental health care received during 2016-17. Patient experiences were better for VA than for community care in all respects except access. For specialty care, access scores were better in the community; for primary and mental health care, access scores were similar in the two settings. Although all specialty care scores and the primary care coordination score improved over time, the gaps between settings did not shrink. As purchased care further expands under the VA Maintaining Internal Systems and Strengthening Integrated Outside Networks Act of 2018, which replaced the Choice Act in 2019, monitoring of meaningful differences between settings should continue, with the results used to inform both VA purchasing decisions and patients' care choices.

Life expectancy estimates for patients diagnosed with prostate cancer in the Veterans Health Administration

PURPOSE

Accurate life expectancy estimates are required to inform prostate cancer treatment decisions. However, few models are specific to the population served or easily implemented in a clinical setting. We sought to create life expectancy estimates specific to Veterans diagnosed with prostate cancer.

MATERIALS AND METHODS

Using national Veterans Health Administration electronic health records, we identified Veterans diagnosed with prostate cancer between 2000 and 2015. We abstracted demographics, comorbidities, oncologic staging, and treatment information. We fit Cox Proportional Hazards models to determine the impact of age, comorbidity, cancer risk, and race on survival. We stratified life expectancy estimates by age, comorbidity and cancer stage.

RESULTS

Our analytic cohort included 145,678 patients. Survival modeling demonstrated the importance of age and comorbidity across all cancer risk categories. Life expectancy estimates generated from age and comorbidity data were predictive of overall survival (C-index 0.676, 95% CI 0.674-0.679) and visualized using Kaplan-Meier plots and heatmaps stratified by age and comorbidity. Separate life expectancy estimates were generated for patients with localized or advanced disease. These life expectancy estimates calibrate well across prostate cancer risk categories.

CONCLUSIONS

Life expectancy estimates are essential to providing patient-centered prostate cancer care. We developed accessible life expectancy estimation tools for Veterans diagnosed with prostate cancer that can be used in routine clinical practice to inform medical-decision making.

Association of Expanded VA Hospice Care With Aggressive Care and Cost for Veterans With Advanced Lung Cancer

Importance

Medicare hospice beneficiaries discontinue disease-modifying treatments because the hospice benefit limits access. While veterans have concurrent access to hospice care and Veterans Affairs (VA) Medical Center (VAMC)-provided treatments, the association of this with changes in treatment and costs of veterans' end-of-life care is unknown.

Objective

To determine whether increasing availability of hospice care, without restrictions on disease-modifying treatments, is associated with reduced aggressive treatments and medical care costs at the end of life.

Design, Setting, and Participants

A modified difference-in-differences study design, using facility fixed effects, compared patient outcomes during years with relatively high vs lower hospice use. This study evaluated 13 085 veterans newly diagnosed with stage IV non-small cell lung cancer (NSCLC) from 113 VAMCs with a minimum of 5 veterans diagnosed with stage IV NSCLC per year, between 2006 and 2012. Data analyses were conducted between January 2017 and July 2018.

Exposures

Using VA inpatient, outpatient, pharmacy claims, and similar Medicare data, we created VAMC-level annual aggregates of all patients who died of cancer for hospice use, cancer treatment, and/or concurrent receipt of both in the last month of life, dividing all VAMC years into quintiles of exposure to hospice availability.

Main Outcomes and Measures

Receipt of aggressive treatments (2 or more hospital admissions within 30 days, tube feeding, mechanical ventilation, intensive care unit [ICU] admission) and total costs in the first 6 months after diagnosis.

Results

Of the 13 085 veterans included in the study, 12 858 (98%) were men; 10 531 (81%) were white, and 5949 (46%) were older than 65 years. Veterans with NSCLC treated in a VAMC in the top hospice quintile (79% hospice users), relative to the bottom quintile (55% hospice users), were more than twice as likely to have concurrent cancer treatment after initiating hospice care (adjusted odds ratio [AOR], 2.28; 95% CI, 1.67-3.31). Nonetheless, for veterans with NSCLC seen in VAMCs in the top hospice quintile, the AOR of receiving aggressive treatment in the 6 months after diagnosis was 0.66 (95% CI, 0.53-0.81), and the AOR of ICU use was 0.78 (95% CI, 0.62-0.99) relative to patients seen in VAMCs in the bottom hospice quintile. The 6-month costs were lower by an estimated $266 (95% CI, -$358 to -$164) per day for the high-quintile group vs the low-quintile group. There was no survival difference.

Conclusions and Relevance

Increasing the availability of hospice care without restricting treatment access for veterans with advanced lung cancer was associated with less aggressive medical treatment and significantly lower costs while still providing cancer treatment.

New-onset postoperative atrial fibrillation impact on 5-year clinical outcomes and costs

OBJECTIVE

The impact of new-onset postoperative atrial fibrillation (POAF) following coronary artery bypass grafting (CABG) surgery on long-term clinical outcomes and costs is not known. This subanalysis of the Veterans Affairs "Randomized On/Off Bypass Follow-up Study" compared 5-year outcomes and costs between patients with and without POAF.

METHODS

Of the 2203 veterans in the study, 100 with pre-CABG atrial fibrillation (93) or missing data (7) were excluded (4.8%). Unadjusted and risk-adjusted outcomes were compared between new-onset POAF (n = 551) and patients without POAF (n = 1552). Five-year clinical outcomes included mortality, major adverse cardiovascular events (MACE, comprising mortality, repeat revascularization, and myocardial infarction), MACE subcomponents, stroke, and costs. A stringent P value of ≤.01 was required to identify statistical significance.

RESULTS

Patients with POAF were older and had more complex comorbidities. Unadjusted 5-year all-cause mortality was 16.3% POAF versus 11.9% no-POAF, P = .008. Unadjusted cardiac-mortality was 7.4% versus 4.8%, P = .022. There were no differences between groups in any other unadjusted outcomes including MACE or stroke. After risk adjustment, there were no significant differences between groups in 5-year all-cause mortality (POAF odds ratio, 1.19; 99% confidence interval, 0.81-1.75) or cardiac mortality (odds ratio, 1.51, 99% confidence interval, 0.88-2.60). Adjusted first-year post-CABG costs were $15,300 greater for patients with POAF, but 2- through 5-year costs were similar.

CONCLUSIONS

No 5-year risk-adjusted outcome differences were found between patients with and without POAF after CABG. Although first-year costs were greater in patients with POAF, this difference did not persist in subsequent years.

Characteristics of mental health trials registered in ClinicalTrials.gov

The ClinicalTrials.gov registry was established in 2000 to address concerns about publication bias and public access to information about clinical trials. We aimed to evaluate differences between for-profit and non-profit sponsors of efficacy mental health trials registered in ClinicalTrials.gov on key trial characteristics that relate to data integrity. We also sought to evaluate whether the registry is fulfilling its purpose as a means of promoting transparency between researchers and the public by providing complete and quality information about the trials it contains. We found that trials tend to be small, use a placebo instead of an active comparator, and employ randomization and blinding. We discuss the implications of these design characteristics and the limitations of the registry.

Association of Postoperative Readmissions With Surgical Quality Using a Delphi Consensus Process to Identify Relevant Diagnosis Codes

Importance

Postoperative readmission data are used to measure hospital performance, yet the extent to which these readmissions reflect surgical quality is unknown.

Objective

To establish expert consensus on whether reasons for postoperative readmission are associated with the quality of surgery in the index admission.

Design, Setting, and Participants

In a modified Delphi process, a panel of 14 experts in medical and surgical readmissions comprising physicians and nonphysicians from Veterans Affairs (VA) and private-sector institutions reviewed 30-day postoperative readmissions from fiscal years 2008 through 2014 associated with inpatient surgical procedures performed at a VA medical center between October 1, 2007, and September 30, 2014. The consensus process was conducted from January through May 2017. Reasons for readmission were grouped into categories based on International Classification of Diseases, Ninth Revision (ICD-9) diagnosis codes. Panelists were given the proportion of readmissions coded by each reason and median (interquartile range) days to readmission. They answered the question, "Does the readmission reason reflect possible surgical quality of care problems in the index admission?" on a scale of 1 (never related) to 5 (directly related) in 3 rounds of consensus building. The consensus process was completed in May 2017 and data were analyzed in June 2017.

Main Outcomes and Measures

Consensus on proportion of ICD-9-coded readmission reasons that reflected quality of surgical procedure.

Results

In 3 Delphi rounds, the 14 panelists achieved consensus on 50 reasons for readmission; 12 panelists also completed group telephone calls between rounds 1 and 2. Readmissions with diagnoses of infection, sepsis, pneumonia, hemorrhage/hematoma, anemia, ostomy complications, acute renal failure, fluid/electrolyte disorders, or venous thromboembolism were considered associated with surgical quality and accounted for 25 521 of 39 664 readmissions (64% of readmissions; 7.5% of 340 858 index surgical procedures). The proportion of readmissions considered to be not associated with surgical quality varied by procedure, ranging from to 21% (613 of 2331) of readmissions after lower-extremity amputations to 47% (745 of 1598) of readmissions after cholecystectomy.

Conclusions and Relevance

One-third of postoperative readmissions are unlikely to reflect problems with surgical quality. Future studies should test whether restricting readmissions to those with specific ICD-9 codes might yield a more useful quality measure.

Health System and Beneficiary Costs Associated With Intensive End-of-Life Medical Services

IMPORTANCE

Despite recommendations to reduce intensive medical treatment at the end of life, many patients with cancer continue to receive such services.

OBJECTIVE

To quantify expected beneficiary and health system costs incurred in association with receipt of intensive medical services in the last month of life.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective cohort study used data collected nationally from Medicare and the Veterans Health Administration for care provided in fiscal years 2010 to 2014. Participants were 48 937 adults aged 66 years or older who died of solid tumor and were continuously enrolled in fee-for-service Medicare and the Veterans Health Administration in the 12 months prior to death. The data were analyzed from February to August 2019.

EXPOSURES

American Society of Clinical Oncology metrics regarding medically intensive services provided in the last month of life, including hospital stay, intensive care unit stay, chemotherapy, 2 or more emergency department visits, or hospice for 3 or fewer days.

MAIN OUTCOMES AND MEASURES

Costs in the last month of life associated with receipt of intensive medical services were evaluated for both beneficiaries and the health system. Costs were estimated from generalized linear models, adjusting for patient demographics and comorbidities and conditioning on geographic region.

RESULTS

Of 48 937 veterans who received care through the Veterans Health Administration and Medicare, most were white (90.8%) and male (98.9%). More than half (58.9%) received at least 1 medically intensive service in the last month of life. Patients who received no medically intensive service generated a mean (SD) health system cost of $7660 ($1793), whereas patients who received 1 or more medically intensive services generated a mean (SD) health system cost of $23 612 ($5528); thus, the additional financial consequence to the health care system for medically intensive services was $15 952 (95% CI, $15 676-$16 206; P < .001). The biggest contributor to these differences was $21 093 (95% CI, $20 364-$21 689) for intensive care unit stay, while the smallest contributor was $3460 (95% CI, $2927-$3880) for chemotherapy. Mean (SD) expected beneficiary costs for the last month of life were $133 ($50) for patients with no medically intensive service and $1257 ($408) for patients with at least 1 medically intensive service (P < .001).

CONCLUSIONS AND RELEVANCE

Given the low income of many elderly patients in the United States, the financial consequences of medically intensive services may be substantial. Costs of medically intensive services at the end of life, including patient financial consequences, should be considered by both physicians and families.

Implementing alcohol use disorder pharmacotherapy in primary care settings: a qualitative analysis of provider-identified barriers and impact on implementation outcomes

Background

Despite the high prevalence of alcohol use disorders (AUDs), in 2016, only 7.8% of individuals meeting diagnostic criteria received any type of AUD treatment. Developing options for treatment within primary care settings is imperative to increase treatment access. As part of a trial to implement AUD pharmacotherapy in primary care settings, this qualitative study analyzed pre-implementation provider interviews using the Consolidated Framework for Implementation Research (CFIR) to identify implementation barriers.

Methods

Three large Veterans Health Administration facilities participated in the implementation intervention. Local providers were trained to serve as implementation/clinical champions and received external facilitation from the project team. Primary care providers received a dashboard of patients with AUD for case identification, educational materials, and access to consultation from clinical champions. Veterans with AUD diagnoses received educational information in the mail. Prior to the start of implementation activities, 24 primary care providers (5–10 per site) participated in semi-structured interviews. Transcripts were analyzed using common coding techniques for qualitative data using the CFIR codebook Innovation/Intervention Characteristics, Outer Setting, Inner Setting, and Characteristics of Individuals domains. Number and type of barriers identified were compared to quantitative changes in AUD pharmacotherapy prescribing rates.

Results

Four major barriers emerged across all three sites: complexity of providing AUD pharmacotherapy in primary care, the limited compatibility of AUD treatment with existing primary care processes, providers’ limited knowledge and negative beliefs about AUD pharmacotherapy and providers’ negative attitudes toward patients with AUD. Site specific barriers included lack of relative advantage of providing AUD pharmacotherapy in primary care over current practice, complaints about the design quality and packaging of implementation intervention materials, limited priority of addressing AUD in primary care and limited available resources to implement AUD pharmacotherapy in primary care.

Conclusions

CFIR constructs were useful for identifying pre-implementation barriers that informed refinements to the implementation intervention. The number and type of pre-implementation barriers identified did not demonstrate a clear relationship to the degree to which sites were able to improve AUD pharmacotherapy prescribing rate. Site-level implementation process factors such as leadership support and provider turn-over likely also interacted with pre-implementation barriers to drive implementation outcomes.

Electronic supplementary material

The online version of this article (10.1186/s13722-019-0151-7) contains supplementary material, which is available to authorized users.

Comparison of a Potential Hospital Quality Metric With Existing Metrics for Surgical Quality-Associated Readmission

Importance

The existing readmission quality metric does not meaningfully distinguish readmissions associated with surgical quality from those that are not associated with surgical quality and thus may not reflect the quality of surgical care.

Objective

To compare a quality metric that classifies readmissions associated with surgical quality with the existing metric of any unplanned readmission in a surgical population.

Design, Setting, and Participants

Cohort study using US nationwide administrative data collected on 4 high-volume surgical procedures performed at 103 Veterans Affairs hospitals from October 1, 2007, through September 30, 2014. Data analysis was conducted from October 1, 2017, to January 24, 2019.

Main Outcomes and Measures

Hospital-level rates of unplanned readmission (existing metric) and surgical readmissions associated with surgical quality (new metric) in the 30 days following hospital discharge for an inpatient surgical procedure.

Results

The study population included 109 258 patients who underwent surgery at 103 hospitals. Patients were majority male (94.1%) and white (78.2%) with a mean (SD) age of 64.0 (10.0) years at the time of surgery. After case-mix adjustment, 30-day surgical readmissions ranged from 4.6% (95% CI, 4.5%-4.8%) among knee arthroplasties to 11.1% (95% CI, 10.9%-11.3%) among colorectal resections. The new surgical readmission metric was significantly correlated with facility-level postdischarge complications for all procedures, with ρ coefficients ranging from 0.33 (95% CI, 0.13-0.51) for cholecystectomy to 0.52 (95% CI, 0.38-0.68) for colorectal resection. Correlations between postdischarge complications and the new surgical readmission metric were higher than correlations between complications and the existing readmission metric for all procedures examined (knee arthroplasty: 0.50 vs 0.48; hip replacement: 0.44 vs 0.18; colorectal resection: 0.52 vs 0.42; and cholecystectomy: 0.33 vs 0.10). When compared with using the existing readmission metric, using the new surgical readmission metric could change hip replacement-associated payment penalty determinations in 28.4% of hospitals and knee arthroplasty-associated penalties in 26.0% of hospitals.

Conclusions and Relevance

In this study, surgical quality-associated readmissions were more correlated with postdischarge complications at a higher rate than were unplanned readmissions. Thus, a metric based on such readmissions may be a better measure of surgical care quality. This work provides an important step in the development of future value-based payments and promotes evidence-based quality metrics targeting the quality of surgical care.

Quality Of End-Of-Life Care Is Higher In The VA Compared To Care Paid For By Traditional Medicare

Congressional and Veterans Affairs (VA) leaders have recommended the VA become more of a purchaser than a provider of health care. Fee-for-service Medicare provides an example of how purchased care differs from the VA's directly provided care. Using established indicators of overly intensive end-of-life care, we compared the quality of care provided through the two systems to veterans dying of cancer in fiscal years 2010-14. The Medicare-reliant veterans were significantly more likely to receive high-intensity care, in the form of chemotherapy, hospital stays, admission to the intensive care unit, more days spent in the hospital, and death in the hospital. However, they were significantly less likely than VA-reliant patients to have multiple emergency department visits. Higher-intensity end-of-life care may be driven by financial incentives present in fee-for-service Medicare but not in the VA's integrated system. To avoid putting VA-reliant veterans at risk of receiving lower-quality care, VA care-purchasing programs should develop coordination and quality monitoring programs to guard against overly intensive end-of-life care.

Assessment of the Medicare Advantage Risk Adjustment Model for Measuring Veterans Affairs Hospital Performance

IMPORTANCE

Policymakers and consumers are eager to compare hospitals on performance metrics, such as surgical complications or unplanned readmissions, measured from administrative data. Fair comparisons depend on risk adjustment algorithms that control for differences in case mix.

OBJECTIVE

To examine whether the Medicare Advantage risk adjustment system version 21 (V21) adequately risk adjusts performance metrics for Veterans Affairs (VA) hospitals.

DESIGN, SETTING, AND PARTICIPANTS

This cohort analysis of administrative data from all 5.5 million veterans who received VA care or VA-purchased care in 2012 was performed from September 8, 2015, to October 22, 2018. Data analysis was performed from January 22, 2016, to October 22, 2018.

EXPOSURES

A patient's risk as measured by the V21 model.

MAIN OUTCOMES AND MEASURES

The main outcome was total cost, and the key independent variable was the V21 risk score.

RESULTS

Of the 5 472 629 VA patients (mean [SD] age, 63.0 [16.1] years; 5 118 908 [93.5%] male), the V21 model identified 694 706 as having a mental health or substance use condition. In contrast, a separate classification system for psychiatric comorbidities identified another 1 266 938 patients with a mental health condition. The V21 model missed depression not otherwise specified (396 062 [31.3%]), posttraumatic stress disorder (345 338 [27.3%]), and anxiety (129 808 [10.2%]). Overall, the V21 model underestimated the cost of care by $2314 (6.7%) for every person with a mental health diagnosis.

CONCLUSIONS AND RELEVANCE

The findings suggest that current aspirations to engender competition by comparing hospital systems may not be appropriate or fair for safety-net hospitals, including the VA hospitals, which treat patients with complex psychiatric illness. Without better risk scores, which is technically possible, outcome comparisons may potentially mislead consumers and policymakers and possibly aggravate inequities in access for such vulnerable populations.

Differences in Risk Scores of Veterans Receiving Community Care Purchased by the Veterans Health Administration

OBJECTIVE

To assess differences in risk (measured by expected costs associated with sociodemographic and clinical profiles) between Veterans receiving outpatient services through two community care (CC) programs: the Fee program ("Fee") and the Veterans Choice Program ("Choice").

DATA SOURCES/STUDY SETTING

Administrative data from VHA's Corporate Data Warehouse in fiscal years (FY) 2014-2015.

STUDY DESIGN

We compared the clinical characteristics of Veterans across three groups (Fee only, Choice only, and Fee & Choice). We classified Veterans into risk groups based on Nosos risk scores and examined the relationship between type of outpatient utilization and risk within each CC group. We also examined changes in utilization of VHA and CC in FY14-FY15. We used chi-square tests, t tests, and ANOVAs to identify significant differences between CC groups.

PRINCIPAL FINDINGS

Of the 1,400,977 Veterans using CC in FY15, 91.4 percent were Fee-only users, 4.4 percent Choice-only users, and 4.2 percent Fee & Choice users. Mean concurrent risk scores were higher for Fee only and Fee & Choice (1.9, SD = 2.7; 1.8, SD = 2.2) compared to Choice-only users (1.0, SD = 1.2) (p < .0001). Most CC users were "dual users" of both VHA and CC in FY14-FY15.

CONCLUSIONS

As care transitions from VHA to CC, VHA should consider how best to coordinate care with community providers to reduce duplication of efforts, improve handoffs, and achieve the best outcomes for Veterans.

Exploring Trajectories of Health Care Utilization Before and After Surgery

BACKGROUND

Long-term trajectories of health care utilization in the context of surgery have not been well characterized. The objective of this study was to examine health care utilization trajectories among surgical patients and identify factors associated with high utilization that could possibly be mitigated after surgical admissions.

STUDY DESIGN

Hospital medical and surgical admissions within 2 years of an index inpatient surgery in the Veterans Health Administration (October 1, 2007 to September 30, 2014) were identified. Group-based trajectory analysis identified 5 distinct trajectories of inpatient admissions around surgery. Characteristics of trajectories of utilization were compared across groups using bivariate statistics and multivariate logistic regression.

RESULTS

Of 280,681 surgery inpatients, most underwent orthopaedic (29.2%), general (28.4%), or peripheral vascular procedures (12.2%). Five trajectories of health care utilization were identified, with 5.2% of patients among consistently high inpatient users accounting for 34.0% of inpatient days. Male (95.4% vs 93.5%, p < 0.01), African-American (21.6% vs 17.3%, p < 0.01), or unmarried patients (61.6% vs 52.5%, p < 0.01) were more likely to be high health care users as compared with other trajectories. High users also had a higher comorbidity burden and a strikingly higher burden of mental health diagnoses (depression: 30.3% vs 16.3%; bipolar disorder: 5.3% vs 2.1%, p < 0.01), social/behavioral risk factors (smoker: 41.1% vs 33.6%, p < 0.01; alcohol use disorder: 28.9% vs 12.9%, p < 0.01), and chronic pain (6.4% vs 2.8%, p < 0.01).

CONCLUSIONS

Mental health, social/behavioral, and pain-related factors are independently associated with high pre- and postoperative health care utilization in surgical patients. Connecting patients to social workers and mental health care coordinators around the time of surgery may mitigate the risk of postoperative readmissions related to these factors.

Off-Pump Versus On-Pump Impact: Diabetic Patient 5-Year Coronary Artery Bypass Clinical Outcomes

BACKGROUND

For diabetic patients who require coronary artery bypass graft (CABG) operation, controversy persists whether an off-pump or an on-pump approach may be advantageous. This US-based, multicenter, randomized, controlled trial, Department of Veterans Affairs Randomization On versus Off Bypass Follow-up Study, compared diabetic patients' 5-year clinical outcomes for off-pump versus on-pump procedures.

METHODS

From 2002 to 2008, 835 medically treated (ie, oral hypoglycemic agent or insulin) diabetic patients underwent either off-pump (n = 402) or on-pump (n = 433) CABG. Five-year primary end points included all-cause death and major adverse cardiovascular events (MACE; composite included all-cause death, myocardial infarction, or repeat revascularization). Secondary 5-year end points included cardiac death and MACE-related components. With baseline risk factors balanced, outcomes were evaluated by using a p value less than or equal to 0.01; nonsignificant trends were reported for p values greater than 0.01 and less than or equal to 0.15.

RESULTS

Five-year all-cause death rates were 20.2% off pump versus 14.1% on pump (p = 0.0198). No differences were seen in MACE (32.6% off-pump approach versus 28.6% on-pump approach, p = 0.216), repeat revascularization (12.4% off-pump approach versus 11.8% on-pump approach, p = 0.770), and nonfatal myocardial infarction (12.7% off-pump approach versus 10.4% on-pump approach, p = 0.299). Cardiac death trended worse with off-pump CABG (9.0%) than with on-pump CABG (6.25%, p = 0.137). Sensitivity analyses that removed conversions confirmed these findings.

CONCLUSIONS

With a 6.1% absolute difference, a strong trend toward improved 5-year survival was observed with on-pump CABG for medically treated diabetic patients. No off-pump advantage was found for any 5-year end points. A future clinical trial now appears warranted to rigorously compare off-pump versus on-pump longer term outcomes for diabetic patients.