Changes in Hospital Adverse Events and Patient Outcomes Associated With Private Equity Acquisition.

Importance: The effects of private equity acquisitions of US hospitals on the clinical quality of inpatient care and patient outcomes remain largely unknown. Objective: To examine changes in hospital-acquired adverse events and hospitalization outcomes associated with private equity acquisitions of US hospitals. Design, Setting, and Participants: Data from 100% Medicare Part A claims for 662 095 hospitalizations at 51 private equity-acquired hospitals were compared with data for 4 160 720 hospitalizations at 259 matched control hospitals (not acquired by private equity) for hospital stays between 2009 and 2019. An event study, difference-in-differences design was used to assess hospitalizations from 3 years before to 3 years after private equity acquisition using a linear model that was adjusted for patient and hospital attributes. Main Outcomes and Measures: Hospital-acquired adverse events (synonymous with hospital-acquired conditions; the individual conditions were defined by the US Centers for Medicare & Medicaid Services as falls, infections, and other adverse events), patient mix, and hospitalization outcomes (including mortality, discharge disposition, length of stay, and readmissions). Results: Hospital-acquired adverse events (or conditions) were observed within 10 091 hospitalizations. After private equity acquisition, Medicare beneficiaries admitted to private equity hospitals experienced a 25.4% increase in hospital-acquired conditions compared with those treated at control hospitals (4.6 [95% CI, 2.0-7.2] additional hospital-acquired conditions per 10 000 hospitalizations, P = .004). This increase in hospital-acquired conditions was driven by a 27.3% increase in falls (P = .02) and a 37.7% increase in central line-associated bloodstream infections (P = .04) at private equity hospitals, despite placing 16.2% fewer central lines. Surgical site infections doubled from 10.8 to 21.6 per 10 000 hospitalizations at private equity hospitals despite an 8.1% reduction in surgical volume; meanwhile, such infections decreased at control hospitals, though statistical precision of the between-group comparison was limited by the smaller sample size of surgical hospitalizations. Compared with Medicare beneficiaries treated at control hospitals, those treated at private equity hospitals were modestly younger, less likely to be dually eligible for Medicare and Medicaid, and more often transferred to other acute care hospitals after shorter lengths of stay. In-hospital mortality (n = 162 652 in the population or 3.4% on average) decreased slightly at private equity hospitals compared with the control hospitals; there was no differential change in mortality by 30 days after hospital discharge. Conclusions and Relevance: Private equity acquisition was associated with increased hospital-acquired adverse events, including falls and central line-associated bloodstream infections, along with a larger but less statistically precise increase in surgical site infections. Shifts in patient mix toward younger and fewer dually eligible beneficiaries admitted and increased transfers to other hospitals may explain the small decrease in in-hospital mortality at private equity hospitals relative to the control hospitals, which was no longer evident 30 days after discharge. These findings heighten concerns about the implications of private equity on health care delivery.

Prescription Drug Spending in Fee-for-Service Medicare, 2008-2019.

Importance: Prescription drug spending is a topic of increased interest to the public and policymakers. However, prior assessments have been limited by focusing on retail spending (Part D-covered drugs), omitting clinician-administered (Part B-covered) drug spending, or focusing on all fee-for-service Medicare beneficiaries, regardless of their enrollment into prescription drug coverage. Objective: To estimate the proportion of health care spending contributed by prescription drugs and to assess spending for retail and clinician-administered prescriptions. Design, Setting, and Participants: Descriptive, serial, cross-sectional analysis of a 20% random sample of fee-for-service Medicare beneficiaries in the United States from 2008 to 2019 who were continuously enrolled in Parts A (hospital), B (medical), and D (prescription drug) benefits, and not in Medicare Advantage. Exposure: Calendar year. Main Outcomes and Measures: Net spending on retail (Part D-covered) and clinician-administered (Part B-covered) prescription drugs; prescription drug spending (spending on Part B-covered and Part D-covered drugs) as a percentage of total per-capita health care spending. Measures were adjusted for inflation and for postsale rebates (for Part D-covered drugs). Results: There were 3 201 284 beneficiaries enrolled in Parts A, B, and D in 2008 and 4 502 718 in 2019. In 2019, beneficiaries had a mean (SD) age of 71.7 (12.0) years, documented sex was female for 57.7%, and 69.5% had no low-income subsidies. Total per-capita spending was $16 345 in 2008 and $20 117 in 2019. Comparing 2008 with 2019, per-capita Part A spending was $7106 (95% CI, $7084-$7128) vs $7120 (95% CI, $7098-$7141), Part B drug spending was $720 (95% CI, $713-$728) vs $1641 (95% CI, $1629-$1653), Part B nondrug spending was $5113 (95% CI, $5105-$5122) vs $6702 (95% CI, $6692-$6712), and Part D net spending was $3122 (95% CI, $3117-$3127) vs $3477 (95% CI, $3466-$3489). The proportion of total annual spending attributed to prescription drugs increased from 24.0% in 2008 to 27.2% in 2019, net of estimated rebates and discounts. Conclusions and Relevance: In 2019, spending on prescription drugs represented approximately 27% of total spending among fee-for-service Medicare beneficiaries enrolled in Part D, even after accounting for postsale rebates.

Higher Surgeon Procedure Volume Is Associated with Improved Hemodialysis Vascular Access Outcomes.

The objective of this study was to examine the association between surgeon characteristics, procedural volume, and short-term outcomes of hemodialysis vascular access. A retrospective cohort study was performed using Medicare Part A and B data from 2007 through 2014 merged with American Medical Association Physician Masterfile surgeon data. A total of 29,034 procedures met the inclusion criteria: 22,541 (78%) arteriovenous fistula (AVF) and 6,493 (22%) arteriovenous graft (AVG). Of these, 13,110 (45.2%) were performed by vascular surgeons, 9,398 (32.3%) by general surgeons, 2,313 (8%) by thoracic surgeons, 1,517 (5.2%) by other specialties, and 2,696 (9.3%) were unknown. Every 10-year increase in years in practice was associated with a 6.9 per cent decrease in the odds of creating AVF versus AVG (P = 0.02). Surgeon characteristics were not associated with the likelihood of vascular access failure. Every 10-procedure increase in cumulative procedure volume was associated with a 5 per cent decrease in the odds of vascular access failure (P = 0.007). There was no association of provider characteristics or procedure volume with survival free of repeat AVF/AVG or TC placement at 12 months. A significant portion of the variability in likelihood of creating AVF versus AVG is attributable to the provider-level variation. Increase in procedure volume is associated with decreased odds of vascular access failure.

Medication adherence as a measure of the quality of care provided by physicians.

OBJECTIVES: To assess the extent to which medication adherence in congestive heart failure (CHF) and diabetes may serve as a measure of physician-level quality. STUDY DESIGN: A retrospective analysis of Medicare data from 2007 to 2009, including parts A (inpatient), B (outpatient), and D (pharmacy). METHODS: For each disease, we assessed the correlation between medication adherence and health outcomes at the physician level. We controlled for selection bias by first regressing patient-level outcomes on a set of covariates including comorbid conditions, demographic attributes, and physician fixed effects. We then classified physicians into 3 levels of average patient medication adherence-low, medium, and high-and compared health outcomes across these groups. RESULTS: There is a clear relationship between average medication adherence and patient health outcomes as measured at the physician level. Within the diabetes sample, among physicians with high average adherence and controlling for patient characteristics, 26.3 per 1000 patients had uncontrolled diabetes compared with 45.9 per 1000 patients among physicians with low average adherence. Within the CHF sample, also controlling for patient characteristics, the average rate of CHF emergency care usage among patients seen by physicians with low average adherence was 16.3% compared with 13.5% for doctors with high average adherence. CONCLUSIONS: This study's results establish a physician-level correlation between improved medication adherence and improved health outcomes in the Medicare population. Our findings suggest that medication adherence could be a useful measure of physician quality, at least for chronic conditions for which prescription medications are an important component of treatment.

Admission diagnoses among patients with heart failure: Variation by ACO performance on a measure of risk-standardized acute admission rates.

BACKGROUND: A key quality metric for Accountable Care Organizations (ACOs) is the rate of hospitalization among patients with heart failure (HF). Among this patient population, non-HF-related hospitalizations account for a substantial proportion of admissions. Understanding the types of admissions and the distribution of admission types across ACOs of varying performance may provide important insights for lowering admission rates. METHODS: We examined admission diagnoses among 220 Medicare Shared Savings Program ACOs in 2013. ACOs were stratified into quartiles by their performance on a measure of unplanned risk-standardized acute admission rates (RSAARs) among patients with HF. Using a previously validated algorithm, we categorized admissions by principal discharge diagnosis into: HF, cardiovascular/non-HF, and noncardiovascular. We compared the mean admission rates by admission type as well as the proportion of admission types across RSAAR quartiles (Q1-Q4). RESULTS: Among 220 ACOs caring for 227,356 patients with HF, the median (IQR) RSAARs per 100 person-years ranged from 64.5 (61.7-67.7) in Q1 (best performers) to 94.0 (90.1-99.9) in Q4 (worst performers). The mean admission rates by admission types for ACOs in Q1 compared with Q4 were as follows: HF admissions: 9.8 (2.2) vs 14.6 (2.8) per 100 person years (P < .0001); cardiovascular/non-HF admissions: 11.1 (1.6) vs 15.9 (2.6) per 100 person-years (P < .0001); and noncardiovascular admissions: 42.7 (5.4) vs 69.6 (11.3) per 100 person-years (P < .0001). The proportion of admission due to HF, cardiovascular/non-HF, and noncardiovascular conditions was 15.4%, 17.5%, and 67.1% in Q1 compared with 14.6%, 15.9%, and 69.4% in Q4 (P < .007). CONCLUSIONS: Although ACOs with the best performance on a measure of all-cause admission rates among people with HF tended to have fewer admissions for HF, cardiovascular/non-HF, and noncardiovascular conditions compared with ACOs with the worst performance (highest admission rates), the largest difference in admission rates were for noncardiovascular admission types. Across all ACOs, two-thirds of admissions of patients with HF were for noncardiovascular causes. These findings suggest that comprehensive approaches are needed to reduce the diverse admission types for which HF patients are at risk.

Empirical-Based Typology of Health Care Utilization by Medicare Eligible Veterans.

OBJECTIVE: Up to 70 percent of patients who receive care through Veterans Health Administration (VHA) facilities also receive care from non-VA providers. Using applied classification techniques, this study sought to improve understanding of how elderly VA patients use VA services and complementary use of non-VA care. METHODS: The study included 1,721,900 veterans age 65 and older who were enrolled in VA and Medicare during 2013 with at least one VA encounter during 2013. Outpatient and inpatient encounters and medications received in VA were classified, and mutually exclusive patient subsets distinguished by patterns of VA service use were derived empirically using latent class analysis (LCA). Patient characteristics and complementary use of non-VA care were compared by patient subset. RESULTS: Five patterns of VA service use were identified that were distinguished by quantity of VA medical and specialty services, medication complexity, and mental health services. Low VA Medical users tend to be healthier and rely on non-VA services, while High VA users have multiple high cost illnesses and concentrate their care in the VA. CONCLUSIONS: VA patients distinguished by patterns of VA service use differ in illness burden and the use of non-VA services. This information may be useful for framing efforts to optimize access to care and care coordination for elderly VA patients.

Octogenarians' post-acute care use after cardiac valve surgery and recovery: clinical implications.

Octogenarians receiving cardiac valve surgery is increasing and recovery is challenging. Post-acute care (PAC) services assist with recovery, yet services provided in facilities do not provide adequate cardiac-focused care or long-term self-management support. The purpose of the paper was to report post-acute care discharge rates in octogenarians and propose clinical implications to improve PAC services. Using a 2003 Medicare Part A database, we studied post-acute care service use in octogenarians after cardiac valve surgery. We propose expansion of the Geriatric Cardiac Care model to include broader clinical therapy dynamics. The sample (n = 10,062) included patients over 80 years discharged from acute care following valve surgery. Post-acute care services were used by 68% of octagarians following cardiac valve surgery (1% intermediate rehabilitation, 35% skilled nursing facility, 32% home health). The large percentage of octagarians using PAC point to the importance of integrating geriatric cardiac care into post-acute services to optimize recovery outcomes.

The Role of Medicare's Inpatient Cost-Sharing in Medicaid Entry.

OBJECTIVE: To isolate the effect of greater inpatient cost-sharing on Medicaid entry among Medicare beneficiaries. DATA SOURCES: Medicare administrative data (years 2007-2010) were linked to nursing home assessments and area-level socioeconomic indicators. STUDY DESIGN: Medicare beneficiaries who are readmitted to a hospital must pay an additional deductible ($1,100 in 2010) if their readmission occurs more than 59 days following discharge. In a regression discontinuity analysis, we take advantage of this Medicare benefit feature to test whether beneficiaries with greater cost-sharing have higher rates of Medicaid enrollment. DATA EXTRACTION METHODS: We identified 221,248 Medicare beneficiaries with an initial hospital stay and a readmission 53-59 days later (no deductible) or 60-66 days later (charged a deductible). PRINCIPAL FINDINGS: Among beneficiaries in low-socioeconomic areas with two hospitalizations, those readmitted 60-66 days after discharge were 21 percent more likely to join Medicaid compared with those readmitted 53-59 days following their initial hospitalization (absolute difference in adjusted risk of Medicaid entry: 3.7 percent vs. 3.1 percent, p = .01). CONCLUSIONS: Increasing Medicare cost-sharing requirements may promote Medicaid enrollment among low-income beneficiaries. Potential savings from an increased cost-sharing in the Medicare program may be offset by increased Medicaid participation.

Propensity scores with misclassified treatment assignment: a likelihood-based adjustment.

Propensity score methods are widely used in comparative effectiveness research using claims data. In this context, the inaccuracy of procedural or billing codes in claims data frequently misclassifies patients into treatment groups, that is, the treatment assignment ($T$) is often measured with error. In the context of a validation data where treatment assignment is accurate, we show that misclassification of treatment assignment can impact three distinct stages of a propensity score analysis: (i) propensity score estimation; (ii) propensity score implementation; and (iii) outcome analysis conducted conditional on the estimated propensity score and its implementation. We examine how the error in $T$ impacts each stage in the context of three common propensity score implementations: subclassification, matching, and inverse probability of treatment weighting (IPTW). Using validation data, we propose a two-step likelihood-based approach which fully adjusts for treatment misclassification bias under subclassification. This approach relies on two common measurement error-assumptions; non-differential measurement error and transportability of the measurement error model. We use simulation studies to assess the performance of the adjustment under subclassification, and also investigate the method's performance under matching or IPTW. We apply the methods to Medicare Part A hospital claims data to estimate the effect of resection versus biopsy on 1-year mortality among $10\,284$ Medicare beneficiaries diagnosed with brain tumors. The ICD9 billing codes from Medicare Part A inaccurately reflect surgical treatment, but SEER-Medicare validation data are available with more accurate information.

Damage caps and defensive medicine, revisited.

Does tort reform reduce defensive medicine and thus healthcare spending? Several (though not all) prior studies, using a difference-in-differences (DiD) approach, find lower Medicare spending for hospital care after states adopt caps on non-economic or total damages ("damage caps"), during the "second" reform wave of the mid-1980s. We re-examine this issue in several ways. We study the nine states that adopted caps during the "third reform wave," from 2002 to 2005. We find that damage caps have no significant impact on Medicare Part A spending, but predict roughly 4% higher Medicare Part B spending. We then revisit the 1980s caps, and find no evidence of a post-adoption drop (or rise) in spending for these caps.