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Silber JH, Rosenbaum PR, Reiter JG, Jain S, Hill AS, Hashemi S, Brown S, Olfson M, Ing C. Exposure to Operative Anesthesia in Childhood and Subsequent Neurobehavioral Diagnoses: A Natural Experiment using Appendectomy. Anesthesiology 2024:141460. [PMID: 38753986 DOI: 10.1097/aln.0000000000005075] [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: 05/18/2024]
Abstract
BACKGROUND Observational studies of anesthetic neurotoxicity may be biased because children requiring anesthesia commonly have medical conditions associated with neurobehavioral problems. This study takes advantage of a natural experiment associated with appendicitis, in order to determine if anesthesia and surgery in childhood were specifically associated with subsequent neurobehavioral outcomes. METHODS We identified 134,388 healthy children with appendectomy and examined the incidence of subsequent externalizing or behavioral disorders (conduct, impulse control, oppositional defiant, or attention-deficit/hyperactivity disorder); or internalizing or mood/anxiety disorders (depression, anxiety, or bipolar disorder) when compared to 671,940 matched healthy controls as identified in Medicaid data between 2001-2018. For comparison, we also examined 154,887 otherwise healthy children admitted to the hospital for pneumonia, cellulitis, and gastroenteritis, of which only 8% received anesthesia, and compared them to 774,435 matched healthy controls. We also examined the difference-in-differences between matched appendectomy patients and their controls and matched medical admission patients and their controls. RESULTS Compared to controls, children with appendectomy were more likely to have subsequent behavioral disorders (the hazard ratio (HR) was 1.04 (95% CI 1.01, 1.06), P = 0.0010), and mood/anxiety disorders (HR: 1.15 (95% CI 1.13, 1.17), P < 0.0001). Relative to controls, children with medical admissions were also more likely to have subsequent behavioral (HR: 1.20 (95% CI 1.18, 1.22), P < 0.0001), and mood/anxiety (HR: 1.25 (95% CI 1.23, 1.27), P < 0.0001) disorders. Comparing the difference between matched appendectomy patients and their matched controls to the difference between matched medical patients and their matched controls, medical patients had more subsequent neurobehavioral problems than appendectomy patients. CONCLUSIONS Although there is an association between neurobehavioral diagnoses and appendectomy, this association is not specific to anesthesia exposure, and is stronger in medical admissions. Medical admissions, generally without anesthesia exposure, displayed significantly higher rates of these disorders than appendectomy-exposed patients.
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Affiliation(s)
- Jeffrey H Silber
- Department of Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA Center for Outcomes Research, Children's Hospital of Philadelphia, Philadelphia, PA Professor of Pediatrics />
| | - Paul R Rosenbaum
- Department of Statistics and Data Science, The Wharton School, University of Pennsylvania, Philadelphia, PA Robert G. Putzel Professor Emeritus
| | - Joseph G Reiter
- Center for Outcomes Research, Children's Hospital of Philadelphia, Philadelphia, PA Statistical Programmer
| | - Siddharth Jain
- Center for Outcomes Research, Children's Hospital of Philadelphia, Philadelphia, PA Senior Scientist
| | - Alexander S Hill
- Center for Outcomes Research, Children's Hospital of Philadelphia, Philadelphia, PA Research Data Analyst
| | - Sean Hashemi
- Center for Outcomes Research, Children's Hospital of Philadelphia, Philadelphia, PA Resource Coordinator
| | - Sydney Brown
- Department of Anesthesiology, University of Michigan, Ann Arbor, MI Assistant Professor
| | - Mark Olfson
- Departments of Psychiatry and Epidemiology, Columbia University Vagelos College of Physicians and Surgeons and Mailman School of Public Health, New York, NY Elizabeth K. Dollard Professor of Psychiatry, Medicine and Law and Professor of Epidemiology
| | - Caleb Ing
- Departments of Anesthesiology and Epidemiology, Columbia University Vagelos College of Physicians and Surgeons and Mailman School of Public Health, New York, NY Associate Professor of Anesthesiology (in Epidemiology)
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Jain S, Rosenbaum PR, Reiter JG, Ramadan OI, Hill AS, Hashemi S, Brown RT, Kelz RR, Fleisher LA, Silber JH. Mortality Among Older Medical Patients at Flagship Hospitals and Their Affiliates. J Gen Intern Med 2024; 39:902-911. [PMID: 38087179 DOI: 10.1007/s11606-023-08415-w] [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: 05/01/2023] [Accepted: 09/05/2023] [Indexed: 02/23/2024]
Abstract
BACKGROUND We define a "flagship hospital" as the largest academic hospital within a hospital referral region and a "flagship system" as a system that contains a flagship hospital and its affiliates. It is not known if patients admitted to an affiliate hospital, and not to its main flagship hospital, have better outcomes than those admitted to a hospital outside the flagship system but within the same hospital referral region. OBJECTIVE To compare mortality at flagship hospitals and their affiliates to matched control patients not in the flagship system but within the same hospital referral region. DESIGN A matched cohort study PARTICIPANTS: The study used hospitalizations for common medical conditions between 2018-2019 among older patients age ≥ 66 years. We analyzed 118,321 matched pairs of Medicare patients admitted with pneumonia (N=57,775), heart failure (N=42,531), or acute myocardial infarction (N=18,015) in 35 flagship hospitals, 124 affiliates, and 793 control hospitals. MAIN MEASURES 30-day (primary) and 90-day (secondary) all-cause mortality. KEY RESULTS 30-day mortality was lower among patients in flagship systems versus control hospitals that are not part of the flagship system but within the same hospital referral region (difference= -0.62%, 95% CI [-0.88%, -0.37%], P<0.001). This difference was smaller in affiliates versus controls (-0.43%, [-0.75%, -0.11%], P=0.008) than in flagship hospitals versus controls (-1.02%, [-1.46%, -0.58%], P<0.001; difference-in-difference -0.59%, [-1.13%, -0.05%], P=0.033). Similar results were found for 90-day mortality. LIMITATIONS The study used claims-based data. CONCLUSIONS In aggregate, within a hospital referral region, patients treated at the flagship hospital, at affiliates of the flagship hospital, and in the flagship system as a whole, all had lower mortality rates than matched controls outside the flagship system. However, the mortality advantage was larger for flagship hospitals than for their affiliates.
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Affiliation(s)
- Siddharth Jain
- Center for Outcomes Research, Children's Hospital of Philadelphia, 2716 South Street, Suite 5140, Philadelphia, PA, 19146-2305, USA.
| | - Paul R Rosenbaum
- The Leonard Davis Institute of Health Economics, The University of Pennsylvania, Philadelphia, PA, USA
- Department of Statistics and Data Science, The Wharton School of the University of Pennsylvania, Philadelphia, PA, USA
| | - Joseph G Reiter
- Center for Outcomes Research, Children's Hospital of Philadelphia, 2716 South Street, Suite 5140, Philadelphia, PA, 19146-2305, USA
| | - Omar I Ramadan
- The Leonard Davis Institute of Health Economics, The University of Pennsylvania, Philadelphia, PA, USA
- Department of Surgery, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Alexander S Hill
- Center for Outcomes Research, Children's Hospital of Philadelphia, 2716 South Street, Suite 5140, Philadelphia, PA, 19146-2305, USA
| | - Sean Hashemi
- Center for Outcomes Research, Children's Hospital of Philadelphia, 2716 South Street, Suite 5140, Philadelphia, PA, 19146-2305, USA
| | - Rebecca T Brown
- The Leonard Davis Institute of Health Economics, The University of Pennsylvania, Philadelphia, PA, USA
- Division of Geriatric Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
- Center for Health Equity Research and Promotion, Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
| | - Rachel R Kelz
- The Leonard Davis Institute of Health Economics, The University of Pennsylvania, Philadelphia, PA, USA
- Department of Surgery, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Lee A Fleisher
- The Leonard Davis Institute of Health Economics, The University of Pennsylvania, Philadelphia, PA, USA
- Department of Anesthesiology and Critical Care, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
- Center for Perioperative Outcomes Research and Transformation, The University of Pennsylvania, Philadelphia, PA, USA
| | - Jeffrey H Silber
- Center for Outcomes Research, Children's Hospital of Philadelphia, 2716 South Street, Suite 5140, Philadelphia, PA, 19146-2305, USA
- The Leonard Davis Institute of Health Economics, The University of Pennsylvania, Philadelphia, PA, USA
- The Departments of Pediatrics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
- Department of Health Care Management, The Wharton School of the University of Pennsylvania, Philadelphia, PA, USA
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Ing C, Silber JH, Lackraj D, Olfson M, Miles C, Reiter JG, Jain S, Chihuri S, Guo L, Gyamfi-Bannerman C, Wall M, Li G. Behavioural disorders after prenatal exposure to anaesthesia for maternal surgery. Br J Anaesth 2024; 132:899-910. [PMID: 38423824 DOI: 10.1016/j.bja.2024.01.025] [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: 11/14/2023] [Revised: 12/27/2023] [Accepted: 01/16/2024] [Indexed: 03/02/2024] Open
Abstract
BACKGROUND The association between prenatal exposure to general anaesthesia for maternal surgery during pregnancy and subsequent risk of disruptive or internalising behavioural disorder diagnosis in the child has not been well-defined. METHODS A nationwide sample of pregnant women linked to their liveborn infants was evaluated using the Medicaid Analytic eXtract (MAX, 1999-2013). Multivariate matching was used to match each child prenatally exposed to general anaesthesia owing to maternal appendectomy or cholecystectomy during pregnancy with five unexposed children. The primary outcome was diagnosis of a disruptive or internalising behavioural disorder in children. Secondary outcomes included diagnoses for a range of other neuropsychiatric disorders. RESULTS We matched 34,271 prenatally exposed children with 171,355 unexposed children in the database. Prenatally exposed children were more likely than unexposed children to receive a diagnosis of a disruptive or internalising behavioural disorder (hazard ratio [HR], 1.31; 95% confidence interval [CI], 1.23-1.40). For secondary outcomes, increased hazards of disruptive (HR, 1.32; 95% CI, 1.24-1.41) and internalising (HR, 1.36; 95% CI, 1.20-1.53) behavioural disorders were identified, and also increased hazards of attention-deficit/hyperactivity disorder (HR, 1.32; 95% CI, 1.22-1.43), behavioural disorders (HR, 1.28; 95% CI, 1.14-1.42), developmental speech or language disorders (HR, 1.16; 95% CI, 1.05-1.28), and autism (HR, 1.31; 95% CI, 1.05-1.64). CONCLUSIONS Prenatal exposure to general anaesthesia is associated with a 31% increased risk for a subsequent diagnosis of a disruptive or internalising behavioural disorder in children. Caution is advised when making any clinical decisions regarding care of pregnant women, as avoidance of necessary surgery during pregnancy can have detrimental effects on mothers and their children.
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Affiliation(s)
- Caleb Ing
- Department of Anesthesiology, Columbia University Vagelos College of Physicians and Surgeons, New York, NY, USA; Department of Epidemiology, Mailman School of Public Health, New York, NY, USA.
| | - Jeffrey H Silber
- Center for Outcomes Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA; Department of Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Deven Lackraj
- Department of Anesthesiology, Columbia University Vagelos College of Physicians and Surgeons, New York, NY, USA
| | - Mark Olfson
- Department of Epidemiology, Mailman School of Public Health, New York, NY, USA; Department of Psychiatry, Columbia University Vagelos College of Physicians and Surgeons, New York, NY, USA
| | - Caleb Miles
- Department of Biostatistics, Mailman School of Public Health, New York, NY, USA
| | - Joseph G Reiter
- Center for Outcomes Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Siddharth Jain
- Center for Outcomes Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Stanford Chihuri
- Department of Anesthesiology, Columbia University Vagelos College of Physicians and Surgeons, New York, NY, USA
| | - Ling Guo
- Department of Anesthesiology, Columbia University Vagelos College of Physicians and Surgeons, New York, NY, USA
| | - Cynthia Gyamfi-Bannerman
- Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California San Diego, La Jolla, CA, USA
| | - Melanie Wall
- Department of Psychiatry, Columbia University Vagelos College of Physicians and Surgeons, New York, NY, USA; Department of Biostatistics, Mailman School of Public Health, New York, NY, USA
| | - Guohua Li
- Department of Anesthesiology, Columbia University Vagelos College of Physicians and Surgeons, New York, NY, USA; Department of Epidemiology, Mailman School of Public Health, New York, NY, USA
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Ramadan OI, Rosenbaum PR, Reiter JG, Jain S, Hill AS, Hashemi S, Kelz RR, Fleisher LA, Silber JH. Impact of Hospital Affiliation With a Flagship Hospital System on Surgical Outcomes. Ann Surg 2024; 279:631-639. [PMID: 38456279 PMCID: PMC10926994 DOI: 10.1097/sla.0000000000006132] [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: 03/09/2024]
Abstract
OBJECTIVE To compare general surgery outcomes at flagship systems, flagship hospitals, and flagship hospital affiliates versus matched controls. SUMMARY BACKGROUND DATA It is unknown whether flagship hospitals perform better than flagship hospital affiliates for surgical patients. METHODS Using Medicare claims for 2018 to 2019, we matched patients undergoing inpatient general surgery in flagship system hospitals to controls who underwent the same procedure at hospitals outside the system but within the same region. We defined a "flagship hospital" within each region as the major teaching hospital with the highest patient volume that is also part of a hospital system; its system was labeled a "flagship system." We performed 4 main comparisons: patients treated at any flagship system hospital versus hospitals outside the flagship system; flagship hospitals versus hospitals outside the flagship system; flagship hospital affiliates versus hospitals outside the flagship system; and flagship hospitals versus affiliate hospitals. Our primary outcome was 30-day mortality. RESULTS We formed 32,228 closely matched pairs across 35 regions. Patients at flagship system hospitals (32,228 pairs) had lower 30-day mortality than matched control patients [3.79% vs. 4.36%, difference=-0.57% (-0.86%, -0.28%), P<0.001]. Similarly, patients at flagship hospitals (15,571/32,228 pairs) had lower mortality than control patients. However, patients at flagship hospital affiliates (16,657/32,228 pairs) had similar mortality to matched controls. Flagship hospitals had lower mortality than affiliate hospitals [difference-in-differences=-1.05% (-1.62%, -0.47%), P<0.001]. CONCLUSIONS Patients treated at flagship hospitals had significantly lower mortality rates than those treated at flagship hospital affiliates. Hence, flagship system affiliation does not alone imply better surgical outcomes.
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Affiliation(s)
- Omar I. Ramadan
- Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA
| | - Paul R. Rosenbaum
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA
- Department of Statistics and Data Science, The Wharton School, University of Pennsylvania, Philadelphia, PA
| | - Joseph G. Reiter
- Center for Outcomes Research, Children’s Hospital of Philadelphia, Philadelphia, PA
| | - Siddharth Jain
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA
- Center for Outcomes Research, Children’s Hospital of Philadelphia, Philadelphia, PA
| | - Alexander S. Hill
- Center for Outcomes Research, Children’s Hospital of Philadelphia, Philadelphia, PA
| | - Sean Hashemi
- Center for Outcomes Research, Children’s Hospital of Philadelphia, Philadelphia, PA
| | - Rachel R. Kelz
- Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA
| | - Lee A. Fleisher
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA
- Center for Perioperative Outcomes Research and Transformation, University of Pennsylvania, Philadelphia, PA
- Department of Anesthesiology and Critical Care, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Jeffrey H. Silber
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA
- Center for Outcomes Research, Children’s Hospital of Philadelphia, Philadelphia, PA
- Department of Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
- Department of Health Care Management, The Wharton School, University of Pennsylvania, Philadelphia, PA
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Jain S, Rosenbaum PR, Reiter JG, Ramadan OI, Hill AS, Silber JH, Fleisher LA. Assessing the Ambulatory Surgery Center Volume-Outcome Association. JAMA Surg 2024; 159:397-403. [PMID: 38265816 PMCID: PMC10809135 DOI: 10.1001/jamasurg.2023.7161] [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] [Received: 06/19/2023] [Accepted: 10/01/2023] [Indexed: 01/25/2024]
Abstract
Importance In surgical patients, it is well known that higher hospital procedure volume is associated with better outcomes. To our knowledge, this volume-outcome association has not been studied in ambulatory surgery centers (ASCs) in the US. Objective To determine if low-volume ASCs have a higher rate of revisits after surgery, particularly among patients with multimorbidity. Design, Setting, and Participants This matched case-control study used Medicare claims data and analyzed surgeries performed during 2018 and 2019 at ASCs. The study examined 2328 ASCs performing common ambulatory procedures and analyzed 4751 patients with a revisit within 7 days of surgery (defined to be either 1 of 4735 revisits or 1 of 16 deaths without a revisit). These cases were each closely matched to 5 control patients without revisits (23 755 controls). Data were analyzed from January 1, 2018, through December 31, 2019. Main Outcomes and Measures Seven-day revisit in patients (cases) compared with the matched patients without the outcome (controls) in ASCs with low volume (less than 50 procedures over 2 years) vs higher volume (50 or more procedures). Results Patients at a low-volume ASC had a higher odds of a 7-day revisit vs patients who had their surgery at a higher-volume ASC (odds ratio [OR], 1.21; 95% CI, 1.09-1.36; P = .001). The odds of revisit for patients with multimorbidity were higher at low-volume ASCs when compared with higher-volume ASCs (OR, 1.57; 95% CI, 1.27-1.94; P < .001). Among patients with multimorbidity in low-volume ASCs, for those who underwent orthopedic procedures, the odds of revisit were 84% higher (OR, 1.84; 95% CI, 1.36-2.50; P < .001) vs higher-volume centers, and for those who underwent general surgery or other procedures, the odds of revisit were 36% higher (OR, 1.36; 95% CI, 1.01-1.83; P = .05) vs a higher-volume center. The findings were not statistically significant for patients without multimorbidity. Conclusions and Relevance In this observational study, the surgical volume of an ASC was an important indicator of patient outcomes. Older patients with multimorbidity should discuss with their surgeon the optimal location of their care.
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Affiliation(s)
- Siddharth Jain
- Center for Outcomes Research, Children’s Hospital of Philadelphia, Philadelphia
| | - Paul R. Rosenbaum
- The Leonard Davis Institute of Health Economics, The University of Pennsylvania, Philadelphia
- Department of Statistics and Data Science, The Wharton School, The University of Pennsylvania, Philadelphia
| | - Joseph G. Reiter
- Center for Outcomes Research, Children’s Hospital of Philadelphia, Philadelphia
| | - Omar I. Ramadan
- The Leonard Davis Institute of Health Economics, The University of Pennsylvania, Philadelphia
- Department of Surgery, The Perelman School of Medicine, The University of Pennsylvania, Philadelphia
| | - Alexander S. Hill
- Center for Outcomes Research, Children’s Hospital of Philadelphia, Philadelphia
| | - Jeffrey H. Silber
- Center for Outcomes Research, Children’s Hospital of Philadelphia, Philadelphia
- The Leonard Davis Institute of Health Economics, The University of Pennsylvania, Philadelphia
- The Department of Pediatrics, The University of Pennsylvania Perelman School of Medicine, Philadelphia
- Department of Health Care Management, The Wharton School, The University of Pennsylvania, Philadelphia
| | - Lee A. Fleisher
- The Leonard Davis Institute of Health Economics, The University of Pennsylvania, Philadelphia
- Department of Anesthesiology and Critical Care, The University of Pennsylvania Perelman School of Medicine, Philadelphia
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Lasater KB, Rosenbaum PR, Aiken LH, Brooks-Carthon JM, Kelz RR, Reiter JG, Silber JH, McHugh MD. Explaining racial disparities in surgical survival: a tapered match analysis of patient and hospital factors. BMJ Open 2023; 13:e066813. [PMID: 37169502 PMCID: PMC10186454 DOI: 10.1136/bmjopen-2022-066813] [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: 07/20/2022] [Accepted: 04/26/2023] [Indexed: 05/13/2023] Open
Abstract
OBJECTIVES Evaluate whether hospital factors, including nurse resources, explain racial differences in Medicare black and white patient surgical outcomes and whether disparities changed over time. DESIGN Retrospective tapered-match. SETTING 571 hospitals at two time points (Early Era 2003-2005; Recent Era 2013-2015). PARTICIPANTS 6752 black patients and three sets of 6752 white controls selected from 107 001 potential controls (Early Era). 4964 black patients and three sets of 4964 white controls selected from 74 108 potential controls (Recent Era). INTERVENTIONS Black patients were matched to white controls on demographics (age, sex, state and year of procedure), procedure (demographics variables plus 136 International Classification of Diseases (ICD)-9 principal procedure codes) and presentation (demographics and procedure variables plus 34 comorbidities, a mortality risk score, a propensity score for being black, emergency admission, transfer status, predicted procedure time). OUTCOMES 30-day and 1-year mortality. RESULTS Before matching, black patients had more comorbidities, higher risk of mortality despite being younger and underwent procedures at different percentages than white patients. Whites in the demographics match had lower mortality at 30 days (5.6% vs 6.7% Early Era; 5.4% vs 5.7% Recent Era) and 1-year (15.5% vs 21.5% Early Era; 12.3% vs 15.9% Recent Era). Black-white 1-year mortality differences were equivalent after matching patients with respect to presentation, procedure and demographic factors. Black-white 30-day mortality differences were equivalent after matching on procedure and demographic factors. Racial disparities in outcomes remained unchanged between the two time periods spanning 10 years. All patients in hospitals with better nurse resources had lower odds of 30-day (OR 0.60, 95% CI 0.46 to 0.78, p<0.010) and 1-year mortality (OR 0.77, 95% CI 0.65 to 0.92, p<0.010) even after accounting for other hospital factors. CONCLUSIONS Survival disparities among black and white patients are largely explained by differences in demographic, procedure and presentation factors. Better nurse resources (eg, staffing, work environment) were associated with lower mortality for all patients.
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Affiliation(s)
- Karen B Lasater
- Center for Health Outcomes and Policy Research, University of Pennsylvania School of Nursing, Philadelphia, Pennsylvania, USA
- The Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Paul R Rosenbaum
- The Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- The Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Linda H Aiken
- Center for Health Outcomes and Policy Research, University of Pennsylvania School of Nursing, Philadelphia, Pennsylvania, USA
- The Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - J Margo Brooks-Carthon
- Center for Health Outcomes and Policy Research, University of Pennsylvania School of Nursing, Philadelphia, Pennsylvania, USA
- The Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Rachel R Kelz
- The Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Joseph G Reiter
- Center for Outcomes Research, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Jeffrey H Silber
- The Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Center for Outcomes Research, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Matthew D McHugh
- Center for Health Outcomes and Policy Research, University of Pennsylvania School of Nursing, Philadelphia, Pennsylvania, USA
- The Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, Pennsylvania, USA
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Jain S, Rosenbaum PR, Reiter JG, Ramadan OI, Hill AS, Hashemi S, Brown RT, Kelz RR, Fleisher LA, Silber JH. Defining Multimorbidity in Older Patients Hospitalized with Medical Conditions. J Gen Intern Med 2023; 38:1449-1458. [PMID: 36385407 PMCID: PMC10160274 DOI: 10.1007/s11606-022-07897-4] [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: 06/03/2022] [Accepted: 10/26/2022] [Indexed: 11/17/2022]
Abstract
BACKGROUND The term "multimorbidity" identifies high-risk, complex patients and is conventionally defined as ≥2 comorbidities. However, this labels almost all older patients as multimorbid, making this definition less useful for physicians, hospitals, and policymakers. OBJECTIVE Develop new medical condition-specific multimorbidity definitions for patients admitted with acute myocardial infarction (AMI), heart failure (HF), and pneumonia patients. We developed three medical condition-specific multimorbidity definitions as the presence of single, double, or triple combinations of comorbidities - called Qualifying Comorbidity Sets (QCSs) - associated with at least doubling the risk of 30-day mortality for AMI and pneumonia, or one-and-a-half times for HF patients, compared to typical patients with these conditions. DESIGN Cohort-based matching study PARTICIPANTS: One hundred percent Medicare Fee-for-Service beneficiaries with inpatient admissions between 2016 and 2019 for AMI, HF, and pneumonia. MAIN MEASURES Thirty-day all-location mortality KEY RESULTS: We defined multimorbidity as the presence of ≥1 QCS. The new definitions labeled fewer patients as multimorbid with a much higher risk of death compared to the conventional definition (≥2 comorbidities). The proportions of patients labeled as multimorbid using the new definition versus the conventional definition were: for AMI 47% versus 87% (p value<0.0001), HF 53% versus 98% (p value<0.0001), and pneumonia 57% versus 91% (p value<0.0001). Thirty-day mortality was higher among patients with ≥1 QCS compared to ≥2 comorbidities: for AMI 15.0% versus 9.5% (p<0.0001), HF 9.9% versus 7.0% (p <0.0001), and pneumonia 18.4% versus 13.2% (p <0.0001). CONCLUSION The presence of ≥2 comorbidities identified almost all patients as multimorbid. In contrast, our new QCS-based definitions selected more specific combinations of comorbidities associated with substantial excess risk in older patients admitted for AMI, HF, and pneumonia. Thus, our new definitions offer a better approach to identifying multimorbid patients, allowing physicians, hospitals, and policymakers to more effectively use such information to consider focused interventions for these vulnerable patients.
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Affiliation(s)
- Siddharth Jain
- Center for Outcomes Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA.
- The Leonard Davis Institute of Health Economics, The University of Pennsylvania, Philadelphia, PA, USA.
| | - Paul R Rosenbaum
- The Leonard Davis Institute of Health Economics, The University of Pennsylvania, Philadelphia, PA, USA
- Department of Statistics, The Wharton School, The University of Pennsylvania, Philadelphia, PA, USA
| | - Joseph G Reiter
- Center for Outcomes Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Omar I Ramadan
- The Leonard Davis Institute of Health Economics, The University of Pennsylvania, Philadelphia, PA, USA
- Department of Surgery, The Perelman School of Medicine, The University of Pennsylvania, Philadelphia, PA, USA
| | - Alexander S Hill
- Center for Outcomes Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Sean Hashemi
- Center for Outcomes Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Rebecca T Brown
- The Leonard Davis Institute of Health Economics, The University of Pennsylvania, Philadelphia, PA, USA
- Division of Geriatric Medicine, Perelman School of Medicine of the University of Pennsylvania, Philadelphia, PA, USA
- Center for Health Equity Research and Promotion, Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Geriatrics and Extended Care, Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
| | - Rachel R Kelz
- The Leonard Davis Institute of Health Economics, The University of Pennsylvania, Philadelphia, PA, USA
- Department of Surgery, The Perelman School of Medicine, The University of Pennsylvania, Philadelphia, PA, USA
| | - Lee A Fleisher
- The Leonard Davis Institute of Health Economics, The University of Pennsylvania, Philadelphia, PA, USA
- Department of Anesthesiology and Critical Care, The University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Center for Perioperative Outcomes Research and Transformation, The University of Pennsylvania, Philadelphia, PA, USA
| | - Jeffrey H Silber
- Center for Outcomes Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- The Leonard Davis Institute of Health Economics, The University of Pennsylvania, Philadelphia, PA, USA
- Department of Anesthesiology and Critical Care, The University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- The Department of Pediatrics, The University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Health Care Management, The Wharton School, The University of Pennsylvania, Philadelphia, PA, USA
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Ramadan OI, Rosenbaum PR, Reiter JG, Jain S, Hill AS, Hashemi S, Kelz RR, Fleisher LA, Silber JH. Redefining Multimorbidity in Older Surgical Patients. J Am Coll Surg 2023; 236:1011-1022. [PMID: 36919934 DOI: 10.1097/xcs.0000000000000659] [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] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/16/2023]
Abstract
BACKGROUND Multimorbidity in surgery is common and associated with worse postoperative outcomes. However, conventional multimorbidity definitions (≥2 comorbidities) label the vast majority of older patients as multimorbid, limiting clinical usefulness. We sought to develop and validate better surgical specialty-specific multimorbidity definitions based on distinct comorbidity combinations. STUDY DESIGN We used Medicare claims for patients aged 66 to 90 years undergoing inpatient general, orthopaedic, or vascular surgery. Using 2016 to 2017 data, we identified all comorbidity combinations associated with at least 2-fold (general/orthopaedic) or 1.5-fold (vascular) greater risk of 30-day mortality compared with the overall population undergoing the same procedure; we called these combinations qualifying comorbidity sets. We applied them to 2018 to 2019 data (general = 230,410 patients, orthopaedic = 778,131 patients, vascular = 146,570 patients) to obtain 30-day mortality estimates. For further validation, we tested whether multimorbidity status was associated with differential outcomes for patients at better-resourced (based on nursing skill-mix, surgical volume, teaching status) hospitals vs all other hospitals using multivariate matching. RESULTS Compared with conventional multimorbidity definitions, the new definitions labeled far fewer patients as multimorbid: general = 85.0% (conventional) vs 55.9% (new) (p < 0.0001); orthopaedic = 66.6% vs 40.2% (p < 0.0001); and vascular = 96.2% vs 52.7% (p < 0.0001). Thirty-day mortality was higher by the new definitions: general = 3.96% (conventional) vs 5.64% (new) (p < 0.0001); orthopaedic = 0.13% vs 1.68% (p < 0.0001); and vascular = 4.43% vs 7.00% (p < 0.0001). Better-resourced hospitals offered significantly larger mortality benefits than all other hospitals for multimorbid vs nonmultimorbid general and orthopaedic, but not vascular, patients (general surgery difference-in-difference = -0.94% [-1.36%, -0.52%], p < 0.0001; orthopaedic = -0.20% [-0.34%, -0.05%], p = 0.0087; and vascular = -0.12% [-0.69%, 0.45%], p = 0.6795). CONCLUSIONS Our new multimorbidity definitions identified far more specific, higher-risk pools of patients than conventional definitions, potentially aiding clinical decision-making.
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Affiliation(s)
- Omar I Ramadan
- From the Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA (Ramadan, Kelz)
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA (Ramadan, Rosenbaum, Jain, Kelz, Fleisher, Silber)
| | - Paul R Rosenbaum
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA (Ramadan, Rosenbaum, Jain, Kelz, Fleisher, Silber)
- Department of Statistics and Data Science, The Wharton School, University of Pennsylvania, Philadelphia, PA (Rosenbaum)
| | - Joseph G Reiter
- Center for Outcomes Research, Children's Hospital of Philadelphia, Philadelphia, PA (Reiter, Jain, Hill, Silber)
| | - Siddharth Jain
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA (Ramadan, Rosenbaum, Jain, Kelz, Fleisher, Silber)
- Center for Outcomes Research, Children's Hospital of Philadelphia, Philadelphia, PA (Reiter, Jain, Hill, Silber)
| | - Alexander S Hill
- Center for Outcomes Research, Children's Hospital of Philadelphia, Philadelphia, PA (Reiter, Jain, Hill, Silber)
| | - Sean Hashemi
- From the Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA (Ramadan, Kelz)
| | - Rachel R Kelz
- From the Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA (Ramadan, Kelz)
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA (Ramadan, Rosenbaum, Jain, Kelz, Fleisher, Silber)
| | - Lee A Fleisher
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA (Ramadan, Rosenbaum, Jain, Kelz, Fleisher, Silber)
- Department of Anesthesiology and Critical Care, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA (Fleisher)
- Center for Perioperative Outcomes Research and Transformation, University of Pennsylvania, Philadelphia, PA (Fleisher)
| | - Jeffrey H Silber
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA (Ramadan, Rosenbaum, Jain, Kelz, Fleisher, Silber)
- Center for Outcomes Research, Children's Hospital of Philadelphia, Philadelphia, PA (Reiter, Jain, Hill, Silber)
- Department of Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA (Silber)
- Department of Health Care Management, The Wharton School, University of Pennsylvania, Philadelphia, PA (Silber)
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9
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Silber JH, Rosenbaum PR, Reiter JG, Jain S, Ramadan OI, Hill AS, Hashemi S, Kelz RR, Fleisher LA. The Safety of Performing Surgery at Ambulatory Surgery Centers Versus Hospital Outpatient Departments in Older Patients With or Without Multimorbidity. Med Care 2023; 61:328-337. [PMID: 36929758 PMCID: PMC10079624 DOI: 10.1097/mlr.0000000000001836] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [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: 03/18/2023]
Abstract
BACKGROUND Surgery for older Americans is increasingly being performed at ambulatory surgery centers (ASCs) rather than hospital outpatient departments (HOPDs), while rates of multimorbidity have increased. OBJECTIVE To determine whether there are differential outcomes in older patients undergoing surgical procedures at ASCs versus HOPDs. RESEARCH DESIGN Matched cohort study. SUBJECTS Of Medicare patients, 30,958 were treated in 2018 and 2019 at an ASC undergoing herniorrhaphy, cholecystectomy, or open breast procedures, matched to similar HOPD patients, and another 32,702 matched pairs undergoing higher-risk procedures. MEASURES Seven and 30-day revisit and complication rates. RESULTS For the same procedures, HOPD patients displayed a higher baseline predicted risk of 30-day revisits than ASC patients (13.09% vs 8.47%, P < 0.0001), suggesting the presence of considerable selection on the part of surgeons. In matched Medicare patients with or without multimorbidity, we observed worse outcomes in HOPD patients: 30-day revisit rates were 8.1% in HOPD patients versus 6.2% in ASC patients ( P < 0.0001), and complication rates were 41.3% versus 28.8%, P < 0.0001. Similar patterns were also found for 7-day outcomes and in higher-risk procedures examined in a secondary analysis. Similar patterns were also observed when analyzing patients with and without multimorbidity separately. CONCLUSIONS The rates of revisits and complications for ASC patients were far lower than for closely matched HOPD patients. The observed initial baseline risk in HOPD patients was much higher than the baseline risk for the same procedures performed at the ASC, suggesting that surgeons are appropriately selecting their riskier patients to be treated at the HOPD rather than the ASC.
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Affiliation(s)
- Jeffrey H. Silber
- Center for Outcomes Research, Children’s Hospital of
Philadelphia, Philadelphia, PA
- The Leonard Davis Institute of Health Economics, The
University of Pennsylvania, Philadelphia, PA
- The Department of Pediatrics, The University of
Pennsylvania Perelman School of Medicine, Philadelphia, PA
- Department of Health Care Management, The Wharton School,
The University of Pennsylvania, Philadelphia, PA
| | - Paul R. Rosenbaum
- The Leonard Davis Institute of Health Economics, The
University of Pennsylvania, Philadelphia, PA
- Department of Statistics and Data Science, The Wharton
School, The University of Pennsylvania, Philadelphia, PA
| | - Joseph G. Reiter
- Center for Outcomes Research, Children’s Hospital of
Philadelphia, Philadelphia, PA
| | - Siddharth Jain
- Center for Outcomes Research, Children’s Hospital of
Philadelphia, Philadelphia, PA
- The Leonard Davis Institute of Health Economics, The
University of Pennsylvania, Philadelphia, PA
| | - Omar I. Ramadan
- The Leonard Davis Institute of Health Economics, The
University of Pennsylvania, Philadelphia, PA
- Department of Surgery, The Perelman School of Medicine, The
University of Pennsylvania
| | - Alexander S. Hill
- Center for Outcomes Research, Children’s Hospital of
Philadelphia, Philadelphia, PA
| | - Sean Hashemi
- Center for Outcomes Research, Children’s Hospital of
Philadelphia, Philadelphia, PA
| | - Rachel R. Kelz
- The Leonard Davis Institute of Health Economics, The
University of Pennsylvania, Philadelphia, PA
- Department of Surgery, The Perelman School of Medicine, The
University of Pennsylvania
| | - Lee A. Fleisher
- The Leonard Davis Institute of Health Economics, The
University of Pennsylvania, Philadelphia, PA
- Department of Anesthesiology and Critical Care, The
University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
- Center for Perioperative Outcomes Research and
Transformation, The University of Pennsylvania, Philadelphia, PA
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10
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Silber JH, Rosenbaum PR, Reiter JG, Hill AS, Jain S, Wolk DA, Small DS, Hashemi S, Niknam BA, Neuman MD, Fleisher LA, Eckenhoff R. Alzheimer's Dementia After Exposure to Anesthesia and Surgery in the Elderly: A Matched Natural Experiment Using Appendicitis. Ann Surg 2022; 276:e377-e385. [PMID: 33214467 PMCID: PMC8437105 DOI: 10.1097/sla.0000000000004632] [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] [Indexed: 10/22/2022]
Abstract
OBJECTIVE The aim of this study was to determine whether surgery and anesthesia in the elderly may promote Alzheimer disease and related dementias (ADRD). BACKGROUND There is a substantial conflicting literature concerning the hypothesis that surgery and anesthesia promotes ADRD. Much of the literature is confounded by indications for surgery or has small sample size. This study examines elderly patients with appendicitis, a common condition that strikes mostly at random after controlling for some known associations. METHODS A matched natural experiment of patients undergoing appendectomy for appendicitis versus control patients without appendicitis using Medicare data from 2002 to 2017, examining 54,996 patients without previous diagnoses of ADRD, cognitive impairment, or neurological degeneration, who developed appendicitis between ages 68 through 77 years and underwent an appendectomy (the ''Appendectomy'' treated group), matching them 5:1 to 274,980 controls, examining the subsequent hazard for developing ADRD. RESULTS The hazard ratio (HR) for developing ADRD or death was lower in the Appendectomy group than controls: HR = 0.96 [95% confidence interval (CI) 0.94-0.98], P < 0.0001, (28.2% in Appendectomy vs 29.1% in controls, at 7.5 years). The HR for death was 0.97 (95% CI 0.95-0.99), P = 0.002, (22.7% vs 23.1% at 7.5 years). The HR for developing ADRD alone was 0.89 (95% CI 0.86-0.92), P < 0.0001, (7.6% in Appendectomy vs 8.6% in controls, at 7.5 years). No subgroup analyses found significantly elevated rates of ADRD in the Appendectomy group. CONCLUSION In this natural experiment involving 329,976 elderly patients, exposure to appendectomy surgery and anesthesia did not increase the subsequent rate of ADRD.
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Affiliation(s)
- Jeffrey H. Silber
- Center for Outcomes Research, Children’s Hospital of Philadelphia, Philadelphia, PA
- The Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA
- Department of Anesthesiology and Critical Care, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
- The Departments of Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
- Department of Health Care Management, The Wharton School, University of Pennsylvania, Philadelphia, PA
| | - Paul R. Rosenbaum
- The Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA
- Department of Statistics, The Wharton School, University of Pennsylvania, Philadelphia, PA
| | - Joseph G. Reiter
- Center for Outcomes Research, Children’s Hospital of Philadelphia, Philadelphia, PA
| | - Alexander S. Hill
- Center for Outcomes Research, Children’s Hospital of Philadelphia, Philadelphia, PA
| | - Siddharth Jain
- Center for Outcomes Research, Children’s Hospital of Philadelphia, Philadelphia, PA
- The Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA
| | - David A. Wolk
- Department of Neurology, The Perelman School of Medicine, University of Pennsylvania
| | - Dylan S. Small
- The Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA
- Department of Statistics, The Wharton School, University of Pennsylvania, Philadelphia, PA
| | - Sean Hashemi
- Center for Outcomes Research, Children’s Hospital of Philadelphia, Philadelphia, PA
| | - Bijan A. Niknam
- Center for Outcomes Research, Children’s Hospital of Philadelphia, Philadelphia, PA
| | - Mark D. Neuman
- The Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA
- Department of Anesthesiology and Critical Care, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
- Center for Perioperative Outcomes Research and Transformation, University of Pennsylvania, Philadelphia, PA
| | - Lee A. Fleisher
- The Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA
- Department of Anesthesiology and Critical Care, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
- Center for Perioperative Outcomes Research and Transformation, University of Pennsylvania, Philadelphia, PA
| | - Roderic Eckenhoff
- Department of Anesthesiology and Critical Care, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
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11
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Jain S, Rosenbaum PR, Reiter JG, Hill AS, Wolk DA, Hashemi S, Fleisher LA, Eckenhoff R, Silber JH. Risk of Parkinson's disease after anaesthesia and surgery. Br J Anaesth 2022; 128:e268-e270. [PMID: 35101245 PMCID: PMC9074782 DOI: 10.1016/j.bja.2021.12.046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Revised: 12/22/2021] [Accepted: 12/27/2021] [Indexed: 11/19/2022] Open
Affiliation(s)
- Siddharth Jain
- Center for Outcomes Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA; The Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA.
| | - Paul R Rosenbaum
- The Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA; Department of Statistics, The Wharton School, University of Pennsylvania, Philadelphia, PA, USA
| | - Joseph G Reiter
- Center for Outcomes Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Alexander S Hill
- Center for Outcomes Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - David A Wolk
- Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Sean Hashemi
- Center for Outcomes Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Lee A Fleisher
- The Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA; Department of Anesthesiology and Critical Care, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA; Center for Perioperative Outcomes Research and Transformation, University of Pennsylvania, Philadelphia, PA, USA
| | - Roderic Eckenhoff
- Department of Anesthesiology and Critical Care, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Jeffrey H Silber
- Center for Outcomes Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA; The Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA; Department of Anesthesiology and Critical Care, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA; Department of Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA; Department of Health Care Management, The Wharton School, University of Pennsylvania, Philadelphia, PA, USA
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12
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Lasater KB, McHugh MD, Rosenbaum PR, Aiken LH, Smith HL, Reiter JG, Niknam BA, Hill AS, Hochman LL, Jain S, Silber JH. Evaluating the Costs and Outcomes of Hospital Nursing Resources: a Matched Cohort Study of Patients with Common Medical Conditions. J Gen Intern Med 2021; 36:84-91. [PMID: 32869196 PMCID: PMC7458128 DOI: 10.1007/s11606-020-06151-z] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/24/2020] [Accepted: 08/12/2020] [Indexed: 11/26/2022]
Abstract
BACKGROUND Nursing resources, such as staffing ratios and skill mix, vary across hospitals. Better nursing resources have been linked to better patient outcomes but are assumed to increase costs. The value of investments in nursing resources, in terms of clinical benefits relative to costs, is unclear. OBJECTIVE To determine whether there are differential clinical outcomes, costs, and value among medical patients at hospitals characterized by better or worse nursing resources. DESIGN Matched cohort study of patients in 306 acute care hospitals. PATIENTS A total of 74,045 matched pairs of fee-for-service Medicare beneficiaries admitted for common medical conditions (25,446 sepsis pairs; 16,332 congestive heart failure pairs; 12,811 pneumonia pairs; 10,598 stroke pairs; 8858 acute myocardial infarction pairs). Patients were also matched on hospital size, technology, and teaching status. MAIN MEASURES Better (n = 76) and worse (n = 230) nursing resourced hospitals were defined by patient-to-nurse ratios, skill mix, proportions of bachelors-degree nurses, and nurse work environments. Outcomes included 30-day mortality, readmission, and resource utilization-based costs. KEY RESULTS Patients in hospitals with better nursing resources had significantly lower 30-day mortality (16.1% vs 17.1%, p < 0.0001) and fewer readmissions (32.3% vs 33.6%, p < 0.0001) yet costs were not significantly different ($18,848 vs 18,671, p = 0.133). The greatest outcomes and cost advantage of better nursing resourced hospitals were in patients with sepsis who had lower mortality (25.3% vs 27.6%, p < 0.0001). Overall, patients with the highest risk of mortality on admission experienced the greatest reductions in mortality and readmission from better nursing at no difference in cost. CONCLUSIONS Medicare beneficiaries with common medical conditions admitted to hospitals with better nursing resources experienced more favorable outcomes at almost no difference in cost.
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Affiliation(s)
- Karen B Lasater
- Center for Health Outcomes and Policy Research, School of Nursing, University of Pennsylvania, Philadelphia, PA, USA.
- The Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA.
| | - Matthew D McHugh
- Center for Health Outcomes and Policy Research, School of Nursing, University of Pennsylvania, Philadelphia, PA, USA
- The Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA
| | - Paul R Rosenbaum
- The Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA
- Department of Statistics, The Wharton School, University of Pennsylvania, Philadelphia, PA, USA
| | - Linda H Aiken
- Center for Health Outcomes and Policy Research, School of Nursing, University of Pennsylvania, Philadelphia, PA, USA
- The Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA
| | - Herbert L Smith
- Center for Health Outcomes and Policy Research, School of Nursing, University of Pennsylvania, Philadelphia, PA, USA
- Population Studies Center, University of Pennsylvania, Philadelphia, PA, USA
| | - Joseph G Reiter
- Center for Outcomes Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Bijan A Niknam
- Center for Outcomes Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Alexander S Hill
- Center for Outcomes Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Lauren L Hochman
- Center for Outcomes Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Siddharth Jain
- The Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA
- Center for Outcomes Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Jeffrey H Silber
- Center for Health Outcomes and Policy Research, School of Nursing, University of Pennsylvania, Philadelphia, PA, USA
- The Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA
- Center for Outcomes Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- The Departments of Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Anesthesiology and Critical Care, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Health Care Management, The Wharton School, University of Pennsylvania, Philadelphia, PA, USA
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13
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Winestone LE, Hochman LL, Sharpe JE, Alvarez E, Becker L, Chow EJ, Reiter JG, Ginsberg JP, Silber JH. Impact of Dependent Coverage Provision of the Affordable Care Act on Insurance Continuity for Adolescents and Young Adults With Cancer. JCO Oncol Pract 2020; 17:e882-e890. [PMID: 33090897 DOI: 10.1200/op.20.00330] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
PURPOSE The 2010 Dependent Coverage Provision (DCP) of the Affordable Care Act (ACA) allowed enrollees to remain on their parents' health insurance until 26 years of age. We compared rates of insurance disenrollment among patients with cancer who were DCP-eligible at age 19 to those who were not eligible at age 19. METHODS Using OptumLabs Data Warehouse, which contains longitudinal, real-world, de-identified administrative claims for commercial enrollees, we examined patients born between 1982 and 1993 and diagnosed with cancer between 2000 and 2015. In the recent cohort, patients who turned 19 in 2010-2012 (DCP-eligible to stay on parents' insurance) were matched to patients who turned 19 in 2007-2009 (not DCP-eligible when turning 19). In an earlier control cohort, patients who turned 19 between 2004 and 2006 (not DCP-eligible) were matched to patients who turned 19 between 2001 and 2003 (not DCP-eligible). Patients were matched on cancer type, diagnosis date, demographics, and treatment characteristics. The time to loss of coverage was estimated using Cox models. Difference-in-difference between the recent and earlier cohorts was also evaluated. RESULTS A total of 2,829 patients who turned 19 years of age in 2010-2012 were matched to patients who turned 19 in 2007-2009. Median time to disenrollment was 26 months for younger patients versus 22 months for older patients (hazard ratio [HR], 0.85; 95% CI, 0.80 to 0.90; P = .001). In 8,978 patients who turned 19 between 2001 and 2006, median time to disenrollment was 20 months among both younger and older patients (HR, 0.99; 95% CI, 0.94 to 1.03; P = .59). The difference between the recent cohort and the earlier control cohort was a 15% greater reduction in coverage loss (P < .0001), favoring those turning 19 after the DCP went into effect. CONCLUSION In the vulnerable population of adolescent and young adult cancer survivors, the ACA may have lowered the insurance dropout rate.
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Affiliation(s)
- Lena E Winestone
- Division of Allergy, Immunology, and Blood & Marrow Transplant, Department of Pediatrics, University of California San Francisco (UCSF) Benioff Children's Hospital; and UCSF Helen Diller Family Comprehensive Cancer Center, San Francisco, CA
| | - Lauren L Hochman
- Center for Outcomes Research, Children's Hospital of Philadelphia, Philadelphia, PA
| | - James E Sharpe
- Center for Outcomes Research, Children's Hospital of Philadelphia, Philadelphia, PA
| | - Elysia Alvarez
- Department of Pediatrics, University of California Davis, Sacramento, CA
| | | | - Eric J Chow
- Department of Pediatrics, University of Washington, Seattle Children's Hospital; and Fred Hutchinson Cancer Research Institute, Seattle, WA
| | - Joseph G Reiter
- Center for Outcomes Research, Children's Hospital of Philadelphia, Philadelphia, PA
| | - Jill P Ginsberg
- Department of Pediatrics, University of Pennsylvania Perelman School of Medicine; and Division of Pediatric Oncology, The Children's Hospital of Philadelphia, Philadelphia, PA.,Cancer Survivorship Program, Children's Hospital of Philadelphia, Philadelphia, PA
| | - Jeffrey H Silber
- Center for Outcomes Research, Children's Hospital of Philadelphia, Philadelphia, PA.,Department of Pediatrics, University of Pennsylvania Perelman School of Medicine; and Division of Pediatric Oncology, The Children's Hospital of Philadelphia, Philadelphia, PA.,Department of Health Care Management, The Wharton School; and Leonard Davis Institute of Health Economics, The University of Pennsylvania, Philadelphia, PA
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14
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Jain S, Rosenbaum PR, Reiter JG, Hoffman G, Small DS, Ha J, Hill AS, Wolk DA, Gaulton T, Neuman MD, Eckenhoff RG, Fleisher LA, Silber JH. Using Medicare claims in identifying Alzheimer's disease and related dementias. Alzheimers Dement 2020; 17:10.1002/alz.12199. [PMID: 33090695 PMCID: PMC8296851 DOI: 10.1002/alz.12199] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2020] [Revised: 08/25/2020] [Accepted: 08/29/2020] [Indexed: 12/11/2022]
Abstract
INTRODUCTION This study develops a measure of Alzheimer's disease and related dementias (ADRD) using Medicare claims. METHODS Validation resembles the approach of the American Psychological Association, including (1) content validity, (2) construct validity, and (3) predictive validity. RESULTS We found that four items-a Medicare claim recording ADRD 1 year ago, 2 years ago, 3 years ago, and a total stay of 6 months in a nursing home-exhibit a pattern of association consistent with a single underlying ADRD construct, and presence of any two of these four items predict a direct measure of cognitive function and also future claims for ADRD. DISCUSSION Our four items are internally consistent with the measurement of a single quantity. The presence of any two items do a better job than a single claim when predicting both a direct measure of cognitive function and future ADRD claims.
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Affiliation(s)
- Siddharth Jain
- Center for Outcomes Research, Children’s Hospital of Philadelphia, Philadelphia, PA
- The Leonard Davis Institute of Health Economics, The University of Pennsylvania, Philadelphia, PA
| | - Paul R. Rosenbaum
- The Leonard Davis Institute of Health Economics, The University of Pennsylvania, Philadelphia, PA
- Department of Statistics, The Wharton School, The University of Pennsylvania, Philadelphia, PA
| | - Joseph G. Reiter
- Center for Outcomes Research, Children’s Hospital of Philadelphia, Philadelphia, PA
| | - Geoffrey Hoffman
- Department of Systems, Populations and Leadership, University of Michigan School of Nursing, Ann Arbor, MI, USA
- University of Michigan’s Institute for Healthcare Policy and Innovation, Ann Arbor, MI, USA
| | - Dylan S. Small
- The Leonard Davis Institute of Health Economics, The University of Pennsylvania, Philadelphia, PA
- Department of Statistics, The Wharton School, The University of Pennsylvania, Philadelphia, PA
| | - JinKyung Ha
- Division of Geriatrics/Institute of Gerontology, University of Michigan, Ann Arbor, MI, USA
| | - Alexander S. Hill
- Center for Outcomes Research, Children’s Hospital of Philadelphia, Philadelphia, PA
| | - David A. Wolk
- Department of Neurology, The Perelman School of Medicine, The University of Pennsylvania
| | - Timothy Gaulton
- The Leonard Davis Institute of Health Economics, The University of Pennsylvania, Philadelphia, PA
- Center for Perioperative Outcomes Research and Transformation, The University of Pennsylvania, Philadelphia, PA
- Department of Anesthesiology and Critical Care, The University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Mark D. Neuman
- The Leonard Davis Institute of Health Economics, The University of Pennsylvania, Philadelphia, PA
- Center for Perioperative Outcomes Research and Transformation, The University of Pennsylvania, Philadelphia, PA
- Department of Anesthesiology and Critical Care, The University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Roderic G. Eckenhoff
- Department of Anesthesiology and Critical Care, The University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Lee A. Fleisher
- The Leonard Davis Institute of Health Economics, The University of Pennsylvania, Philadelphia, PA
- Center for Perioperative Outcomes Research and Transformation, The University of Pennsylvania, Philadelphia, PA
- Department of Anesthesiology and Critical Care, The University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Jeffrey H. Silber
- Center for Outcomes Research, Children’s Hospital of Philadelphia, Philadelphia, PA
- The Leonard Davis Institute of Health Economics, The University of Pennsylvania, Philadelphia, PA
- Department of Anesthesiology and Critical Care, The University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
- The Departments of Pediatrics, The University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
- Department of Health Care Management, The Wharton School, The University of Pennsylvania, Philadelphia, PA
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15
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Schapira MM, Stevens EM, Sharpe JE, Hochman L, Reiter JG, Calhoun SR, Shah SA, Bailey LC, Bagatell R, Silber JH, Tai E, Barakat LP. Outcomes among pediatric patients with cancer who are treated on trial versus off trial: A matched cohort study. Cancer 2020; 126:3471-3482. [PMID: 32453441 PMCID: PMC11059191 DOI: 10.1002/cncr.32947] [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] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2019] [Revised: 03/31/2020] [Accepted: 03/31/2020] [Indexed: 11/11/2022]
Abstract
BACKGROUND Approximately 50% of children with cancer in the United States who are aged <15 years receive primary treatment on a therapeutic clinical trial. To the authors' knowledge, it remains unknown whether trial enrollment has a clinical benefit compared with the best alternative standard therapy and/or off trial (ie, clinical trial effect). The authors conducted a retrospective matched cohort study to compare the morbidity and mortality of pediatric patients with cancer who are treated on a phase 3 clinical trial compared with those receiving standard therapy and/or off trial. METHODS Subjects were aged birth to 19 years; were diagnosed between 2000 and 2010 with acute lymphocytic leukemia (ALL), acute myeloid leukemia (AML), rhabdomyosarcoma, or neuroblastoma; and had received initial treatment at the Children's Hospital of Philadelphia. On-trial and off-trial subjects were matched based on age, race, ethnicity, a diagnosis of Down syndrome (for patients with ALL or AML), prognostic risk level, date of diagnosis, and tumor type. RESULTS A total of 428 participants were matched in 214 pairs (152 pairs for ALL, 24 pairs for AML, 32 pairs for rhabdomyosarcoma, and 6 pairs for neuroblastoma). The 5-year survival rate did not differ between those treated on trial versus those treated with standard therapy and/or off trial (86.9% vs 82.2%; P = .093). On-trial patients had a 32% lower odds of having worse (higher) mortality-morbidity composite scores, although this did not reach statistical significance (odds ratio, 0.68; 95% confidence interval, 0.45-1.03 [P = .070]). CONCLUSIONS There was no statistically significant difference in outcomes noted between those patients treated on trial and those treated with standard therapy and/or off trial. However, in partial support of the clinical trial effect, the results of the current study indicate a trend toward more favorable outcomes in children treated on trial compared with those treated with standard therapy and/or off trial. These findings can support decision making regarding enrollment in pediatric phase 3 clinical trials.
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Affiliation(s)
- Marilyn M. Schapira
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
- Center for Health Equity Research and Promotion (CHERP), Philadelphia VA Medical Center, Philadelphia, Pennsylvania
| | | | - James E. Sharpe
- Center for Outcomes Resarch, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - Lauren Hochman
- Center for Outcomes Resarch, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - Joseph G. Reiter
- Center for Outcomes Resarch, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - Shawna R. Calhoun
- Center for Outcomes Resarch, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - Shivani A. Shah
- Center for Outcomes Resarch, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - Leonard Charles Bailey
- Division of Oncology, Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
- Department of Biomedical and Health Informatics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - Rochelle Bagatell
- Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
- Division of Oncology, Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Jeffrey H. Silber
- Center for Outcomes Resarch, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
- Division of Oncology, Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
- Department of Anesthesiology and Critical Care, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
- Department of Health Care Management, Wharton School, The University of Pennsylvania, Philadelphia, Pennsylvania
| | - Eric Tai
- Division of Cancer Prevention and Control, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Lamia P. Barakat
- Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
- Division of Oncology, Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
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16
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Lasater KB, McHugh M, Rosenbaum PR, Aiken LH, Smith H, Reiter JG, Niknam BA, Hill AS, Hochman LL, Jain S, Silber JH. Valuing hospital investments in nursing: multistate matched-cohort study of surgical patients. BMJ Qual Saf 2020; 30:46-55. [PMID: 32220938 DOI: 10.1136/bmjqs-2019-010534] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2019] [Revised: 03/13/2020] [Accepted: 03/16/2020] [Indexed: 12/16/2022]
Abstract
BACKGROUND There are known clinical benefits associated with investments in nursing. Less is known about their value. AIMS To compare surgical patient outcomes and costs in hospitals with better versus worse nursing resources and to determine if value differs across these hospitals for patients with different mortality risks. METHODS Retrospective matched-cohort design of patient outcomes at hospitals with better versus worse nursing resources, defined by patient-to-nurse ratios, skill mix, proportions of bachelors-degree nurses and nurse work environments. The sample included 62 715 pairs of surgical patients in 76 better nursing resourced hospitals and 230 worse nursing resourced hospitals from 2013 to 2015. Patients were exactly matched on principal procedures and their hospital's size category, teaching and technology status, and were closely matched on comorbidities and other risk factors. RESULTS Patients in hospitals with better nursing resources had lower 30-day mortality: 2.7% vs 3.1% (p<0.001), lower failure-to-rescue: 5.4% vs 6.2% (p<0.001), lower readmissions: 12.6% vs 13.5% (p<0.001), shorter lengths of stay: 4.70 days vs 4.76 days (p<0.001), more intensive care unit admissions: 17.2% vs 15.4% (p<0.001) and marginally higher nurse-adjusted costs (which account for the costs of better nursing resources): $20 096 vs $19 358 (p<0.001), as compared with patients in worse nursing resourced hospitals. The nurse-adjusted cost associated with a 1% improvement in mortality at better nursing hospitals was $2035. Patients with the highest mortality risk realised the greatest value from nursing resources. CONCLUSION Hospitals with better nursing resources provided better clinical outcomes for surgical patients at a small additional cost. Generally, the sicker the patient, the greater the value at better nursing resourced hospitals.
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Affiliation(s)
- Karen B Lasater
- School of Nursing, Center for Health Outcomes and Policy Research, University of Pennsylvania, Philadelphia, Pennsylvania, USA .,The Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Matthew McHugh
- School of Nursing, Center for Health Outcomes and Policy Research, University of Pennsylvania, Philadelphia, Pennsylvania, USA.,The Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Paul R Rosenbaum
- The Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, Pennsylvania, USA.,The Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Linda H Aiken
- School of Nursing, Center for Health Outcomes and Policy Research, University of Pennsylvania, Philadelphia, Pennsylvania, USA.,The Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Herbert Smith
- School of Nursing, Center for Health Outcomes and Policy Research, University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Population Studies Center, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Joseph G Reiter
- Center for Outcomes Research, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Bijan A Niknam
- Center for Outcomes Research, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Alexander S Hill
- Center for Outcomes Research, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Lauren L Hochman
- Center for Outcomes Research, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Siddharth Jain
- The Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Center for Outcomes Research, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Jeffrey H Silber
- Center for Outcomes Research, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.,School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
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17
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Caswell-Jin JL, McNamara K, Reiter JG, Sun R, Hu Z, Ma Z, Suarez CJ, Tilk S, Raghavendra A, Forte V, Chin SF, Bardwell H, Provenzano E, Caldas C, Lang J, West R, Tripathy D, Press MF, Curtis C. Abstract P3-06-01: Clonal evolution and heterogeneity in breast tumors treated with neoadjuvant HER2-targeted therapy. Cancer Res 2019. [DOI: 10.1158/1538-7445.sabcs18-p3-06-01] [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: 11/16/2022]
Abstract
Abstract
Background: Understanding to what extent a breast tumor's genetic composition may change over the course of a few months of neoadjuvant therapy has implications for optimal therapeutic approach. However, genomic changes observed across treatment may result from either treatment-induced clonal evolution or geographically disparate sampling of a heterogeneous tumor. We sought to characterize the geographic heterogeneity in primary breast tumors, and to incorporate this information into analysis of clonal evolution with neoadjuvant therapy.
Methods: We assembled the largest cohort to date of multi-region (n=2-3) whole-exome sequenced (WES) or whole-genome sequenced untreated primary breast tumors with matched normal and adequate tumor purity for analysis: four tumors with data generated for this study and five tumors compiled from three previous studies. We also generated the first cohort of multi-region (n=2-6) WES breast tumors post-neoadjuvant HER2-targeted therapy and chemotherapy, sequencing one region from a pre-treatment diagnostic specimen, multiple regions from the post-treatment surgical specimen, and matched normal for five HER2+ breast tumors that did not achieve a pathologic complete response. We used an agent-based model of spatial tumor growth to investigate whether the mutational patterns we observed with treatment were consistent with pre-existing heterogeneity or treatment-induced selection.
Results: In untreated primary breast tumors, on average 30% (range 1-70%) of apparently clonal mutations from a single region were absent or rare in a second, spatially disparate region (high-frequency regional, or HFR). Intra-tumor heterogeneity was similar post-treatment (HFR 28%, range 10-54%), and was higher in breast tumors than in previously analyzed colon, brain, lung, and esophageal tumors. Simulation studies confirmed that with high heterogeneity as observed in breast tumors, analysis of one pre-treatment and one post-treatment region could not distinguish treatment-induced clonal evolution from pre-existing heterogeneity; however, obtaining at least two post-treatment regions allowed for detection of clonal shifts with treatment. Analysis of multi-region data revealed that clonal replacement occurred with neoadjuvant therapy in two of the five tumors. Candidate causes of therapeutic resistance included amplifications in CCND1, ERBB4, and MYC in one subclone, and functional protein-altering mutations in ERCC2, SMO, and WT1 in another. Mathematical modeling suggested that these putative resistant subclones comprised 0.02-12.5% of the overall pre-treatment cell population, substantially larger than previous estimates of resistant tumor clone size.
Conclusions: WES data from multiple regions of untreated and treated primary breast tumors revealed considerable heterogeneity that remained present throughout treatment with chemotherapy and HER2-targeted therapy, even while major clonal sweeps took place in a minority of tumors. Obtaining at least two samples for analysis from breast tumors post-neoadjuvant therapy may reveal the tumor's evolutionary path and, especially as increasing numbers of molecular and immune therapeutic targets are identified, inform new clinical strategies.
Citation Format: Caswell-Jin JL, McNamara K, Reiter JG, Sun R, Hu Z, Ma Z, Suarez CJ, Tilk S, Raghavendra A, Forte V, Chin S-F, Bardwell H, Provenzano E, Caldas C, Lang J, West R, Tripathy D, Press MF, Curtis C. Clonal evolution and heterogeneity in breast tumors treated with neoadjuvant HER2-targeted therapy [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P3-06-01.
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Affiliation(s)
- JL Caswell-Jin
- Stanford University School of Medicine, Stanford, CA; The University of Texas MD Anderson Cancer Center, Houston, TX; Norris Comprehensive Cancer Center, Los Angeles, CA; Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom; Cambridge Experimental Cancer Medicine Centre and NIHR Cambridge Biomedical Research Centre, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - K McNamara
- Stanford University School of Medicine, Stanford, CA; The University of Texas MD Anderson Cancer Center, Houston, TX; Norris Comprehensive Cancer Center, Los Angeles, CA; Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom; Cambridge Experimental Cancer Medicine Centre and NIHR Cambridge Biomedical Research Centre, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - JG Reiter
- Stanford University School of Medicine, Stanford, CA; The University of Texas MD Anderson Cancer Center, Houston, TX; Norris Comprehensive Cancer Center, Los Angeles, CA; Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom; Cambridge Experimental Cancer Medicine Centre and NIHR Cambridge Biomedical Research Centre, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - R Sun
- Stanford University School of Medicine, Stanford, CA; The University of Texas MD Anderson Cancer Center, Houston, TX; Norris Comprehensive Cancer Center, Los Angeles, CA; Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom; Cambridge Experimental Cancer Medicine Centre and NIHR Cambridge Biomedical Research Centre, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - Z Hu
- Stanford University School of Medicine, Stanford, CA; The University of Texas MD Anderson Cancer Center, Houston, TX; Norris Comprehensive Cancer Center, Los Angeles, CA; Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom; Cambridge Experimental Cancer Medicine Centre and NIHR Cambridge Biomedical Research Centre, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - Z Ma
- Stanford University School of Medicine, Stanford, CA; The University of Texas MD Anderson Cancer Center, Houston, TX; Norris Comprehensive Cancer Center, Los Angeles, CA; Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom; Cambridge Experimental Cancer Medicine Centre and NIHR Cambridge Biomedical Research Centre, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - CJ Suarez
- Stanford University School of Medicine, Stanford, CA; The University of Texas MD Anderson Cancer Center, Houston, TX; Norris Comprehensive Cancer Center, Los Angeles, CA; Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom; Cambridge Experimental Cancer Medicine Centre and NIHR Cambridge Biomedical Research Centre, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - S Tilk
- Stanford University School of Medicine, Stanford, CA; The University of Texas MD Anderson Cancer Center, Houston, TX; Norris Comprehensive Cancer Center, Los Angeles, CA; Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom; Cambridge Experimental Cancer Medicine Centre and NIHR Cambridge Biomedical Research Centre, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - A Raghavendra
- Stanford University School of Medicine, Stanford, CA; The University of Texas MD Anderson Cancer Center, Houston, TX; Norris Comprehensive Cancer Center, Los Angeles, CA; Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom; Cambridge Experimental Cancer Medicine Centre and NIHR Cambridge Biomedical Research Centre, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - V Forte
- Stanford University School of Medicine, Stanford, CA; The University of Texas MD Anderson Cancer Center, Houston, TX; Norris Comprehensive Cancer Center, Los Angeles, CA; Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom; Cambridge Experimental Cancer Medicine Centre and NIHR Cambridge Biomedical Research Centre, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - S-F Chin
- Stanford University School of Medicine, Stanford, CA; The University of Texas MD Anderson Cancer Center, Houston, TX; Norris Comprehensive Cancer Center, Los Angeles, CA; Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom; Cambridge Experimental Cancer Medicine Centre and NIHR Cambridge Biomedical Research Centre, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - H Bardwell
- Stanford University School of Medicine, Stanford, CA; The University of Texas MD Anderson Cancer Center, Houston, TX; Norris Comprehensive Cancer Center, Los Angeles, CA; Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom; Cambridge Experimental Cancer Medicine Centre and NIHR Cambridge Biomedical Research Centre, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - E Provenzano
- Stanford University School of Medicine, Stanford, CA; The University of Texas MD Anderson Cancer Center, Houston, TX; Norris Comprehensive Cancer Center, Los Angeles, CA; Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom; Cambridge Experimental Cancer Medicine Centre and NIHR Cambridge Biomedical Research Centre, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - C Caldas
- Stanford University School of Medicine, Stanford, CA; The University of Texas MD Anderson Cancer Center, Houston, TX; Norris Comprehensive Cancer Center, Los Angeles, CA; Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom; Cambridge Experimental Cancer Medicine Centre and NIHR Cambridge Biomedical Research Centre, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - J Lang
- Stanford University School of Medicine, Stanford, CA; The University of Texas MD Anderson Cancer Center, Houston, TX; Norris Comprehensive Cancer Center, Los Angeles, CA; Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom; Cambridge Experimental Cancer Medicine Centre and NIHR Cambridge Biomedical Research Centre, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - R West
- Stanford University School of Medicine, Stanford, CA; The University of Texas MD Anderson Cancer Center, Houston, TX; Norris Comprehensive Cancer Center, Los Angeles, CA; Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom; Cambridge Experimental Cancer Medicine Centre and NIHR Cambridge Biomedical Research Centre, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - D Tripathy
- Stanford University School of Medicine, Stanford, CA; The University of Texas MD Anderson Cancer Center, Houston, TX; Norris Comprehensive Cancer Center, Los Angeles, CA; Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom; Cambridge Experimental Cancer Medicine Centre and NIHR Cambridge Biomedical Research Centre, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - MF Press
- Stanford University School of Medicine, Stanford, CA; The University of Texas MD Anderson Cancer Center, Houston, TX; Norris Comprehensive Cancer Center, Los Angeles, CA; Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom; Cambridge Experimental Cancer Medicine Centre and NIHR Cambridge Biomedical Research Centre, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - C Curtis
- Stanford University School of Medicine, Stanford, CA; The University of Texas MD Anderson Cancer Center, Houston, TX; Norris Comprehensive Cancer Center, Los Angeles, CA; Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom; Cambridge Experimental Cancer Medicine Centre and NIHR Cambridge Biomedical Research Centre, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
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18
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Silber JH, Rosenbaum PR, Ross RN, Reiter JG, Niknam BA, Hill AS, Bongiorno DM, Shah SA, Hochman LL, Even-Shoshan O, Fox KR. Disparities in Breast Cancer Survival by Socioeconomic Status Despite Medicare and Medicaid Insurance. Milbank Q 2019; 96:706-754. [PMID: 30537364 DOI: 10.1111/1468-0009.12355] [Citation(s) in RCA: 76] [Impact Index Per Article: 15.2] [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: 12/29/2022] Open
Abstract
Policy Points Patients with low socioeconomic status (SES) experience poorer survival rates after diagnosis of breast cancer, even when enrolled in Medicare and Medicaid. Most of the difference in survival is due to more advanced cancer on presentation and the general poor health of lower SES patients, while only a very small fraction of the SES disparity is due to differences in cancer treatment. Even when comparing only low- versus not-low-SES whites (without confounding by race) the survival disparity between disparate white SES populations is very large and is associated with lower use of preventive care, despite having insurance. CONTEXT Disparities in breast cancer survival by socioeconomic status (SES) exist despite the "safety net" programs Medicare and Medicaid. What is less clear is the extent to which SES disparities affect various racial and ethnic groups and whether causes differ across populations. METHODS We conducted a tapered matching study comparing 1,890 low-SES (LSES) non-Hispanic white, 1,824 black, and 723 Hispanic white women to 60,307 not-low-SES (NLSES) non-Hispanic white women, all in Medicare and diagnosed with invasive breast cancer between 1992 and 2010 in 17 US Surveillance, Epidemiology, and End Results (SEER) regions. LSES Medicare patients were Medicaid dual-eligible and resided in neighborhoods with both high poverty and low education. NLSES Medicare patients had none of these factors. MEASUREMENTS 5-year and median survival. FINDINGS LSES non-Hispanic white patients were diagnosed with more stage IV disease (6.6% vs 3.6%; p < 0.0001), larger tumors (24.6 mm vs 20.2 mm; p < 0.0001), and more chronic diseases such as diabetes (37.8% vs 19.0%; p < 0.0001) than NLSES non-Hispanic white patients. Disparity in 5-year survival (NLSES - LSES) was 13.7% (p < 0.0001) when matched for age, year, and SEER site (a 42-month difference in median survival). Additionally, matching 55 presentation factors, including stage, reduced the disparity to 4.9% (p = 0.0012), but further matching on treatments yielded little further change in disparity: 4.6% (p = 0.0014). Survival disparities among LSES blacks and Hispanics, also versus NLSES whites, were significantly associated with presentation factors, though black patients also displayed disparities related to initial treatment. Before being diagnosed, all LSES populations used significantly less preventive care services than matched NLSES controls. CONCLUSIONS In Medicare, SES disparities in breast cancer survival were large (even among non-Hispanic whites) and predominantly related to differences of presentation characteristics at diagnosis rather than differences in treatment. Preventive care was less frequent in LSES patients, which may help explain disparities at presentation.
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Affiliation(s)
- Jeffrey H Silber
- Center for Outcomes Research, Children's Hospital of Philadelphia.,Leonard and Madlyn Abramson Cancer Center of the University of Pennsylvania.,University of Pennsylvania Perelman School of Medicine.,Division of Pediatric Oncology, Children's Hospital of Philadelphia.,The Wharton School, University of Pennsylvania.,Leonard Davis Institute of Health Economics, University of Pennsylvania
| | - Paul R Rosenbaum
- The Wharton School, University of Pennsylvania.,Leonard Davis Institute of Health Economics, University of Pennsylvania
| | - Richard N Ross
- Center for Outcomes Research, Children's Hospital of Philadelphia
| | - Joseph G Reiter
- Center for Outcomes Research, Children's Hospital of Philadelphia
| | - Bijan A Niknam
- Center for Outcomes Research, Children's Hospital of Philadelphia
| | - Alexander S Hill
- Center for Outcomes Research, Children's Hospital of Philadelphia
| | | | - Shivani A Shah
- Center for Outcomes Research, Children's Hospital of Philadelphia
| | - Lauren L Hochman
- Center for Outcomes Research, Children's Hospital of Philadelphia
| | - Orit Even-Shoshan
- Center for Outcomes Research, Children's Hospital of Philadelphia.,Leonard Davis Institute of Health Economics, University of Pennsylvania
| | - Kevin R Fox
- Leonard and Madlyn Abramson Cancer Center of the University of Pennsylvania.,University of Pennsylvania Perelman School of Medicine.,Hospital of the University of Pennsylvania
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19
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Silber JH, Zeigler AE, Reiter JG, Hochman LL, Ludwig JM, Wang W, Calhoun SR, Pati S. Using Appendicitis to Improve Estimates of Childhood Medicaid Participation Rates. Acad Pediatr 2018; 18:593-600. [PMID: 29581042 DOI: 10.1016/j.acap.2018.03.008] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/24/2017] [Revised: 02/23/2018] [Accepted: 03/17/2018] [Indexed: 10/17/2022]
Abstract
OBJECTIVE Administrative data are often used to estimate state Medicaid/Children's Health Insurance Program duration of enrollment and insurance continuity, but they are generally not used to estimate participation (the fraction of eligible children enrolled) because administrative data do not include reasons for disenrollment and cannot observe eligible never-enrolled children, causing estimates of eligible unenrolled to be inaccurate. Analysts are therefore forced to either utilize survey information that is not generally linkable to administrative claims or rely on duration and continuity measures derived from administrative data and forgo estimating claims-based participation. We introduce appendectomy-based participation (ABP) to estimate statewide participation rates using claims by taking advantage of a natural experiment around statewide appendicitis admissions to improve the accuracy of participation rate estimates. METHODS We used Medicaid Analytic eXtract (MAX) for 2008-2010; and the American Community Survey for 2008-2010 from 43 states to calculate ABP, continuity ratio, duration, and participation based on the American Community Survey (ACS). RESULTS In the validation study, median participation rate using ABP was 86% versus 87% for ACS-based participation estimates using logical edits and 84% without logical edits. Correlations between ABP and ACS with or without logical edits was 0.86 (P < .0001). Using regression analysis, ABP alone was a significant predictor of ACS (P < .0001) with or without logical edits, and adding duration and/or the continuity ratio did not significantly improve the model. CONCLUSION Using the ABP rate derived from administrative claims (MAX) is a valid method to estimate statewide public insurance participation rates in children.
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Affiliation(s)
- Jeffrey H Silber
- Center for Outcomes Research, Children's Hospital of Philadelphia, Philadelphia, Pa; Department of Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pa; Department of Health Care Management, The Wharton School, University of Pennsylvania, Philadelphia, Pa; The Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, Pa.
| | - Ashley E Zeigler
- Center for Outcomes Research, Children's Hospital of Philadelphia, Philadelphia, Pa
| | - Joseph G Reiter
- Center for Outcomes Research, Children's Hospital of Philadelphia, Philadelphia, Pa
| | - Lauren L Hochman
- Center for Outcomes Research, Children's Hospital of Philadelphia, Philadelphia, Pa
| | - Justin M Ludwig
- Center for Outcomes Research, Children's Hospital of Philadelphia, Philadelphia, Pa
| | - Wei Wang
- Center for Outcomes Research, Children's Hospital of Philadelphia, Philadelphia, Pa
| | - Shawna R Calhoun
- Center for Outcomes Research, Children's Hospital of Philadelphia, Philadelphia, Pa
| | - Susmita Pati
- Division of Primary Care Pediatrics, Stony Brook University School of Medicine & Stony Brook Children's Hospital, Stony Brook, NY
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20
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Koyawala N, Silber JH, Rosenbaum PR, Wang W, Hill AS, Reiter JG, Niknam BA, Even-Shoshan O, Bloom RD, Sawinski D, Nazarian S, Trofe-Clark J, Lim MA, Schold JD, Reese PP. Comparing Outcomes between Antibody Induction Therapies in Kidney Transplantation. J Am Soc Nephrol 2017; 28:2188-2200. [PMID: 28320767 DOI: 10.1681/asn.2016070768] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [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: 07/19/2016] [Accepted: 01/24/2017] [Indexed: 12/24/2022] Open
Abstract
Kidney transplant recipients often receive antibody induction. Previous studies of induction therapy were often limited by short follow-up and/or absence of information about complications. After linking Organ Procurement and Transplantation Network data with Medicare claims, we compared outcomes between three induction therapies for kidney recipients. Using novel matching techniques developed on the basis of 15 clinical and demographic characteristics, we generated 1:1 pairs of alemtuzumab-rabbit antithymocyte globulin (rATG) (5330 pairs) and basiliximab-rATG (9378 pairs) recipients. We used paired Cox regression to analyze the primary outcomes of death and death or allograft failure. Secondary outcomes included death or sepsis, death or lymphoma, death or melanoma, and healthcare resource utilization within 1 year. Compared with rATG recipients, alemtuzumab recipients had higher risk of death (hazard ratio [HR], 1.14; 95% confidence interval [95% CI], 1.03 to 1.26; P<0.01) and death or allograft failure (HR, 1.18; 95% CI, 1.09 to 1.28; P<0.001). Results for death as well as death or allograft failure were generally consistent among elderly and nonelderly subgroups and among pairs receiving oral prednisone. Compared with rATG recipients, basiliximab recipients had higher risk of death (HR, 1.08; 95% CI, 1.01 to 1.16; P=0.03) and death or lymphoma (HR, 1.12; 95% CI, 1.01 to 1.23; P=0.03), although these differences were not confirmed in subgroup analyses. One-year resource utilization was slightly lower among alemtuzumab recipients than among rATG recipients, but did not differ between basiliximab and rATG recipients. This observational evidence indicates that, compared with alemtuzumab and basiliximab, rATG associates with lower risk of adverse outcomes, including mortality.
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Affiliation(s)
| | - Jeffrey H Silber
- Center for Outcomes Research, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania.,Department of Pediatrics
| | - Paul R Rosenbaum
- Department of Statistics, Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Wei Wang
- Center for Outcomes Research, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - Alexander S Hill
- Center for Outcomes Research, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - Joseph G Reiter
- Center for Outcomes Research, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - Bijan A Niknam
- Center for Outcomes Research, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - Orit Even-Shoshan
- Center for Outcomes Research, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - Roy D Bloom
- Renal Electrolyte and Hypertension Division, Department of Medicine, and
| | - Deirdre Sawinski
- Renal Electrolyte and Hypertension Division, Department of Medicine, and
| | | | - Jennifer Trofe-Clark
- Renal Electrolyte and Hypertension Division, Department of Medicine, and.,Pharmacy Services, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania; and
| | - Mary Ann Lim
- Renal Electrolyte and Hypertension Division, Department of Medicine, and
| | - Jesse D Schold
- Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio
| | - Peter P Reese
- Renal Electrolyte and Hypertension Division, Department of Medicine, and .,Department of Biostatistics and Epidemiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania
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21
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Silber JH, Rosenbaum PR, Calhoun SR, Reiter JG, Hill AS, Even-Shoshan O, Greeley WJ. Outcomes, ICU Use, and Length of Stay in Chronically Ill Black and White Children on Medicaid and Hospitalized for Surgery. J Am Coll Surg 2017; 224:805-814. [PMID: 28167226 DOI: 10.1016/j.jamcollsurg.2017.01.053] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2016] [Revised: 01/23/2017] [Accepted: 01/24/2017] [Indexed: 11/26/2022]
Abstract
BACKGROUND With increasing Medicaid coverage, it has become especially important to determine whether racial differences exist within the Medicaid system. We asked whether disparities exist in hospital practice and patient outcomes between matched black and white Medicaid children with chronic conditions undergoing surgery. STUDY DESIGN We conducted a matched cohort study, matching 6,398 pairs within states on detailed patient characteristics using data from 25 states contributing adequate Medicaid Analytic eXtract claims for admissions of children with chronic conditions undergoing the same surgical procedures between January 1, 2009 and November 30, 2010 for ages 1 to 18 years. RESULTS The black patient 30-day revisit rate was 19.3% vs 19.8% in matched white patients (p = 0.61), 30-day readmission rates were 7.0% vs 6.9% (p = 0.43), and 30-day mortality rates were 0.38% vs 0.19% (p = 0.06), respectively. A higher percentage of black patients exceeded their own state's individual median length of stay (44.0% vs 39.6%; p < 0.001) and median ICU length of stay (25.9% vs 23.8%; p < 0.001). Intensive care unit use was higher in black patients (25.9% vs 23.8%; p < 0.001). After adjusting for multiple testing, only 2 states were found to differ significantly by race (New York for length of stay and New Jersey for ICU use). CONCLUSIONS We did not observe disparities in 30-day revisits and readmissions for chronically ill children in Medicaid undergoing surgery, and only slight differences in length of stay, ICU length of stay, and use of the ICU, where blacks displayed somewhat elevated rates compared with white controls.
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Affiliation(s)
- Jeffrey H Silber
- Center for Outcomes Research, The Children's Hospital of Philadelphia, Philadelphia, PA; Department of Pediatrics, The University of Pennsylvania School of Medicine, Philadelphia, PA; Department of Anesthesiology and Critical Care, The University of Pennsylvania School of Medicine, Philadelphia, PA; Department of Health Care Management, The Wharton School, The University of Pennsylvania, Philadelphia, PA; The Leonard Davis Institute of Health Economics, The University of Pennsylvania, Philadelphia, PA.
| | - Paul R Rosenbaum
- Department of Statistics, The Wharton School, The University of Pennsylvania, Philadelphia, PA; The Leonard Davis Institute of Health Economics, The University of Pennsylvania, Philadelphia, PA
| | - Shawna R Calhoun
- Center for Outcomes Research, The Children's Hospital of Philadelphia, Philadelphia, PA
| | - Joseph G Reiter
- Center for Outcomes Research, The Children's Hospital of Philadelphia, Philadelphia, PA
| | - Alexander S Hill
- Center for Outcomes Research, The Children's Hospital of Philadelphia, Philadelphia, PA
| | - Orit Even-Shoshan
- Center for Outcomes Research, The Children's Hospital of Philadelphia, Philadelphia, PA
| | - William J Greeley
- Department of Anesthesiology and Critical Care, The University of Pennsylvania School of Medicine, Philadelphia, PA
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22
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Silber JH, Rosenbaum PR, Calhoun SR, Reiter JG, Hill AS, Guevara JP, Zorc JJ, Even-Shoshan O. Racial Disparities in Medicaid Asthma Hospitalizations. Pediatrics 2017; 139:peds.2016-1221. [PMID: 28025238 DOI: 10.1542/peds.2016-1221] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 09/14/2016] [Indexed: 11/24/2022] Open
Abstract
BACKGROUND AND OBJECTIVES Black children with asthma comprise one-third of all asthma patients in Medicaid. With increasing Medicaid coverage, it has become especially important to monitor Medicaid for differences in hospital practice and patient outcomes by race. METHODS A multivariate matched cohort design, studying 11 079 matched pairs of children in Medicaid (black versus white matched pairs from inside the same state) admitted for asthma between January 1, 2009 and November 30, 2010 in 33 states contributing adequate Medicaid Analytic eXtract claims. RESULTS Ten-day revisit rates were 3.8% in black patients versus 4.2% in white patients (P = .12); 30-day revisit and readmission rates were also not significantly different by race (10.5% in black patients versus 10.8% in white patients; P = .49). Length of stay (LOS) was also similar; both groups had a median stay of 2.0 days, with a slightly lower percentage of black patients exceeding their own state's median LOS (30.2% in black patients versus 31.8% in white patients; P = .01). The mean paired difference in LOS was 0.00 days (95% confidence interval, -0.08 to 0.08). However, ICU use was higher in black patients than white patients (22.2% versus 17.5%; P < .001). After adjusting for multiple testing, only 4 states were found to differ significantly, but only in ICU use, where blacks had higher rates of use. CONCLUSIONS For closely matched black and white patients, racial disparities concerning asthma admission outcomes and style of practice are small and generally nonsignificant, except for ICU use, where we observed higher rates in black patients.
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Affiliation(s)
- Jeffrey H Silber
- Center for Outcomes Research, and .,Departments of Pediatrics.,Anesthesiology and Critical Care, School of Medicine.,Health Care Management, and.,Leonard Davis Institute of Health Economics, The University of Pennsylvania, Philadelphia, Pennsylvania
| | - Paul R Rosenbaum
- Leonard Davis Institute of Health Economics, The University of Pennsylvania, Philadelphia, Pennsylvania.,Statistics, The Wharton School, and
| | | | | | | | - James P Guevara
- Departments of Pediatrics.,Leonard Davis Institute of Health Economics, The University of Pennsylvania, Philadelphia, Pennsylvania.,Divisions of General Pediatrics, and
| | - Joseph J Zorc
- Departments of Pediatrics.,Emergency Medicine, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania; and
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