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OBJECTIVE: To determine if surgery and anesthesia in the elderly may promote Alzheimer’s 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% CI 0.94, 0.98), P < 0.0001, (28.2% in Appendectomy versus 29.1% in controls, at 7.5 years). The HR for death was 0.97 (0.95, 0.99), P = 0.002, (22.7% versus 23.1% at 7.5 years). The HR for developing ADRD alone was 0.89 (0.86, 0.92), P < 0.0001, (7.6% in Appendectomy versus 8.6% in controls, at 7.5 years). No subgroup analyses found significantly elevated rates of ADRD in the Appendectomy group. CONCLUSIONS: In this natural experiment involving 329,976 elderly patients, exposure to appendectomy surgery and anesthesia did not increase the subsequent rate of ADRD.

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.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.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.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 value0.0001), HF 53% versus 98% (p value0.0001), and pneumonia 57% versus 91% (p value0.0001). Thirty-day mortality was higher among patients with ≥1 QCS compared to ≥2 comorbidities: for AMI 15.0% versus 9.5% (p0.0001), HF 9.9% versus 7.0% (p0.0001), and pneumonia 18.4% versus 13.2% (p0.0001).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.

ObjectivesEvaluate whether hospital factors, including nurse resources, explain racial differences in Medicare black and white patient surgical outcomes and whether disparities changed over time.DesignRetrospective tapered-match.Setting571 hospitals at two time points (Early Era 2003–2005; Recent Era 2013–2015).Participants6752 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).InterventionsBlack 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).Outcomes30-day and 1-year mortality.ResultsBefore 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, pConclusionsSurvival 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.

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.

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

BackgroundThere are known clinical benefits associated with investments in nursing. Less is known about their value.AimsTo 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.MethodsRetrospective 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.ResultsPatients in hospitals with better nursing resources had lower 30-day mortality: 2.7% vs 3.1% (pConclusionHospitals 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.

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 (i) content validity, (ii) construct validity, and (iii) 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.

BACKGROUND Approximately 50% of children with cancer in the United States who are aged

BACKGROUND: There are numerous definitions of multimorbidity. None systematically examines specific comorbidity combinations accounting for multiple testing when exploring large datasets. OBJECTIVES: Develop and validate a list of all single, double, and triple comorbidity combinations, with each individual Qualifying Comorbidity Set (QCS) at least doubling the odds of mortality versus its reference population. Patients with at least one QCS were defined as having multimorbidity. RESEARCH DESIGN: Cohort-based study with a matching validation study. SUBJECTS: All fee-for-service Medicare patients between age 65 and 85 without dementia or metastatic solid tumors undergoing general surgery in 2009–2010, and an additional 2011–2013 dataset. MEASURES: 30-day all-location mortality RESULTS: There were 576 qualifying comorbidity sets (2 singles, 63 doubles and 511 triples), each set at least doubling the odds of dying. In 2011, 36% of eligible patients had multimorbidity. As a group, multimorbid patients (mortality rate = 7.0%) had a mortality Mantel-Haenszel OR = 1.90 (1.77, 2.04) versus a reference that included both multimorbid and non-multimorbid patients (mortality rate = 3.3%), and Mantel-Haenszel OR = 3.72 (3.51, 3.94) versus only non-multimorbid patients (mortality rate = 1.6%). When matching 3,151 pairs of multimorbid patients from low-volume hospitals to similar patients in high-volume hospitals, the mortality rates were 6.7% versus 5.2%, respectively (P = 0.006). CONCLUSIONS: A list of QCSs identified a third of older patients undergoing general surgery that had greatly elevated mortality. These sets can be used to identify vulnerable patients and the specific combinations of comorbidities that make them susceptible to poor outcomes.

BACKGROUND: Teaching hospitals typically pioneer investment in new technology and cultivate workforce characteristics generally associated with better quality, but the value of this extra investment is unclear. OBJECTIVE: Compare outcomes and costs between major teaching and non-teaching hospitals by closely matching on patient characteristics. DESIGN: Medicare patients at 339 major teaching hospitals (resident-to-bed (RTB) ratios ≥ 0.25); matched patient controls from 2439 non-teaching hospitals (RTB ratios

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.

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.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).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.Using the ABP rate derived from administrative claims (MAX) is a valid method to estimate statewide public insurance participation rates in children.

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