Market landscape and insurer-provider integration: the case of ambulatory surgery centers.

Insurer-provider integration is a new form of vertical integration, with increasing prominence in health care markets. While there are potential benefits from tighter alignment between providers and payers, risks of perverse impacts on health care markets loom large. Yet, little is known about this new wave of consolidation, which limits options for policy or regulatory responses. We focus on a dominant insurer's acquisitions of ambulatory surgery centers (ASCs) to document the growth and geographic spread of these ownership events. We found that a diverse swathe of the United States has experienced an insurer-led ASC takeover. The acquisitions are also more frequently in areas where the insurer holds a higher enrollee market share at baseline, although a linear prediction of the likelihood of ASC acquisition shows a more nuanced picture.

Association between physician age and patterns of end-of-life care among older Americans.

BACKGROUND: End-of-life (EOL) care patterns may differ by physician age given differences in how physicians are trained or changes associated with aging. We sought to compare patterns of EOL care delivered to older Americans according to physician age. METHODS: We conducted a cross-sectional study of a 20% sample of Medicare fee-for-service beneficiaries aged ≥66 years who died in 2016-2019 (n = 487,293). We attributed beneficiaries to the physician who had >50% of primary care visits during the last 6 months of life. We compared beneficiary-level outcomes by physician age (<40, 40-49, 50-59, or ≥60) in two areas: (1) advance care planning (ACP) and palliative care; and (2) high-intensity care at the EOL. RESULTS: Beneficiaries attributed to younger physicians had slightly higher proportions of billed ACP (adjusted proportions, 17.1%, 16.1%, 15.5%, and 14.0% for physicians aged <40, 40-49, 50-59, and ≥60, respectively; p-for-trend adjusted for multiple comparisons <0.001) and palliative care counseling or hospice use in the last 180 days of life (64.5%, 63.6%, 61.9%, and 60.8%; p-for-trend <0.001). Similarly, physicians' younger age was associated with slightly lower proportions of emergency department visits (57.4%, 57.0%, 57.4%, and 58.1%; p-for-trend <0.001), hospital admissions (51.2%, 51.1%, 51.4%, and 52.1%; p-for-trend <0.001), intensive care unit admissions (27.8%, 27.9%, 28.2%, and 28.3%; p-for-trend = 0.03), or mechanical ventilation or cardiopulmonary resuscitation (14.2, 14.9%, 15.2%, and 15.3%; p-for-trend <0.001) in the last 30 days of life, and in-hospital death (20.2%, 20.6%, 21.3%, and 21.5%; p-for-trend <0.001). CONCLUSIONS: We found that differences in patterns of EOL care between beneficiaries cared for by younger and older physicians were small, and thus, not clinically meaningful. Future research is warranted to understand the factors that can influence patterns of EOL care provided by physicians, including initial and continuing medical education.

The segregation of physician networks providing care to black and white patients with heart disease: Concepts, measures, and empirical evaluation.

Black-White disparities in cardiac care may be related to physician referral network segregation. We developed and tested new geographic physician network segregation measures. We used Medicare claims to identify Black and White Medicare heart disease patients and map physician networks for 169 hospital referral regions (HRRs) with over 1000 Black patients. We constructed two network segregation indexes ranging from 0 (integration) to 100 (total segregation): Dissimilarity (the unevenness of Black and White patient distribution across physicians [Dn]) and Absolute Clustering (the propensity of Black patients' physicians to have closer ties with each other than with other physicians [ACLn]). We employed conditional logit models to estimate the probability of using the best (lowest mortality) geographically available hospital for Black and White patients undergoing coronary artery bypass grafting (CABG) surgery in 126 markets with sufficient sample size at increasing levels of network segregation and for low vs. high HRR Black patient population. Physician network segregation was lower than residential segregation (Dissimilarity 21.9 vs. 48.7, and Absolute Clustering 4.8 vs. 32.4) and positively correlated with residential segregation (p < .001). Network segregation effects differed by race and HRR Black patient population. For White patients, higher network segregation was associated with a higher probability of using the best available hospitals in HRRs with few black patients but unchanged (ACLn) or lower (Dn) probability of best hospital use in HRRs with many Black patients. For Black patients, higher network segregation was not associated with a substantial change in the probability of best hospital use regardless of the HRR Black patient population size. Measuring physician network segregation is feasible and associated with nuanced effects on Black-White differences in high-quality hospital use for heart disease. Further work is needed to understand underlying mechanisms and potential uses in health equity policy.

Within-Physician Differences in Patient Sharing Between Primary Care Physicians and Cardiologists Who Treat White and Black Patients With Heart Disease.

BACKGROUND: Black-White disparities in heart disease treatment may be attributable to differences in physician referral networks. We mapped physician networks for Medicare patients and examined within-physician Black-White differences in patient sharing between primary care physicians and cardiologists. METHODS AND RESULTS: Using Medicare fee-for-service files for 2016 to 2017, we identified a cohort of Black and White patients with heart disease and the primary care physicians and cardiologists treating them. To ensure the robustness of within-physician comparisons, we restricted the sample to regional health care markets (ie, hospital referral regions) with at least 10 physicians sharing ≥3 Black and White patients. We used claims to construct 2 race-specific physician network measures: degree (number of cardiologists with whom a primary care physician shares patients) and transitivity (network tightness). Measures were adjusted for Black-White differences in physician panel size and calculated for all settings (hospital and office) and for office settings only. Of 306 US hospital referral regions, 226 and 145 met study criteria for all settings and office setting analyses, respectively. Black patients had more cardiology encounters overall (6.9 versus 6.6; P<0.001) and with unique cardiologists (3.0 versus 2.6; P<0.001), but fewer office encounters (31.7% versus 41.1%; P<0.001). Primary care physicians shared Black patients with more cardiologists than White patients (mean differential degree 23.4 for all settings and 3.6 for office analyses; P<0.001 for both). Black patient-sharing networks were less tightly connected in all but office settings (mean differential transitivity -0.2 for all settings [P<0.001] and near 0 for office analyses [P=0.74]). CONCLUSIONS: Within-physician Black-White differences in patient sharing exist and may contribute to disparities in cardiac care.

A Formal Framework For Incorporating Equity Into Health Care Quality Measurement.

Quality measurement is an important tool for incentivizing improvement in the quality of health care. Most quality measurement efforts do not explicitly target health equity. Although some measurement approaches may intend to realign incentives to focus quality improvement efforts on underserved groups, the extent to which they accomplish this goal is understudied. We posit that tying incentives to approaches on the basis of stratification or disparities may have unintended consequences or limited effects. Such approaches might not reduce existing disparities because addressing one aspect of equity may be in competition with addressing others. We propose equity weighting, a new measurement framework to advance equity on multiple fronts that addresses the shortcomings of existing approaches and explicitly calibrates incentives to align with equity goals. We use colorectal cancer screening data derived from 2017 Medicare claims to illustrate how equity weighting fixes unintended consequences in other methods and how it can be adapted to policy goals.

Changes in US Hospital Financial Performance During the COVID-19 Public Health Emergency.

Importance: The COVID-19 public health emergency (PHE) caused substantial changes in hospital operations. The net effect of these changes on hospital financial performance is unclear. Objective: To evaluate changes in hospital financial performance before and during the COVID-19 PHE. Design, Setting, and Participants: This longitudinal within-hospital cohort analysis from 2017 to 2021 used national RAND hospital data merged with American Community Survey data. A total of 4223 short-term acute care or critical access hospitals in the US with financial data spanning 2017 to 2021 were evaluated. Exposure: Financial performance during the first 2 years of the PHE. Main Outcomes and Measures: The main outcome was PHE financial distress calculated based on net operating income (operating revenue minus operating expenses). Within-hospital changes in net operating income over time were evaluated with and without COVID-19 relief funding. From henceforth, 2020/2021 means the weighted average financial performance for both calendar year 2020 and 2021. Hospitals were characterized as having new financial distress if (1) their average 2020/2021 net operating income was negative and (2) the average 2020/2021 net operating income was less than that hospital's pre-2020 net operating income. Predictors of new financial distress were evaluated using logistic regression and predictors of COVID-19 relief using 2-part models. Results: In this sample of 4423 hospitals, 3529 (80.0%) received PHE funds during 2020/2021. A total of 846 (19.1%) were located in a census tract with more than 20% Hispanic residents. Of the total number of hospitals, 720 (16.3%) of hospitals had PHE financial distress, whereas 2047 (46.3%) had PHE financial distress after excluding COVID-19 relief funding from net operating income. The majority of hospitals (n = 3337; 74.8%) had a positive net operating income across 2020/2021, with 785 (17.8%) hospitals moving from a negative pre-2020 to a positive 2020/2021 net operating income. In adjusted analyses, hospitals treating a higher proportion of Hispanic populations were more likely to have PHE distress (adjusted odds ratio, 1.3; 95% CI, 1.1-1.6; P = .02). Median (IQR) operating margins from 2020/2021 were at an all-time high of 6.5% (0.2%-13.3%) compared with pre-2020 operating margins of 2.8% (-2.8% to 9.3%). Conclusions and Relevance: In this cohort study of US hospitals, the large majority had positive financial performance during 2020/2021, partly due to COVID-19 relief funds. However, hospitals serving Hispanic populations had substantially worsened financial performance during 2020/2021, even after accounting for COVID-19 relief. That COVID-19 relief funding aided in operating margins reaching all-time highs indicates funding amounts may have been larger than was necessary for many hospitals. With COVID-19 relief funding ending yet COVID-19 related continuing to affect hospital expenses, ongoing monitoring of hospital financial performance is vital to ensure patients retain access to care.

Estimated Annual Spending on Lecanemab and Its Ancillary Costs in the US Medicare Program.

This cross-sectional cost analysis uses data from the 2018 Health and Retirement Study to estimate the potential future Medicare spending and beneficiary costs for lecanemab.

Understanding the social risk factor adjustment's effect on Star Ratings.

OBJECTIVES: CMS implemented the Categorical Adjustment Index (CAI) to address measurement bias in the Medicare Advantage (MA) Star Ratings, as unadjusted scores may disadvantage MA contracts serving more enrollees at greater social risk. CAI values are added to a contract's Star Ratings to adjust for the mean within-contract performance disparity associated with its percentage of enrollees with low socioeconomic status (ie, receipt of a Part D low-income subsidy or dual eligibility for Medicare and Medicaid [LIS/DE]) and who are disabled. We examined the CAI's effect on Star Ratings and the type of contracts affected. STUDY DESIGN: Observational study of MA contracts with health and prescription drug coverage. METHODS: We compared adjusted and unadjusted 2017-2020 Star Ratings overall and by contracts' proportion of LIS/DE and disabled enrollees. We assessed the CAI's effect on qualifying for quality bonus payments (QBPs), eligibility for rebate payments, and high-performing and low-performing designations. RESULTS: The CAI's impact was modest overall (3.2%-14.9% of contracts experienced one-half Star Rating changes). Upward changes were concentrated among contracts with high percentages of LIS/DE or disabled enrollees (7.7%-32.3% of these contracts saw increased Star Ratings). In 2020, 26.0% of contracts with a high proportion of LIS/DE or disabled enrollees that qualified for a QBP did so because of the CAI. CONCLUSIONS: The CAI primarily affected contracts with high LIS/DE or disabled enrollment, which received higher Star Ratings because of the CAI. The adjustment helps ensure that such contracts' performance is not understated and reduces incentives for MA contracts to avoid patients at greater social risk.

Physician organizations' use of behavioral nudges to influence physician behavior.

OBJECTIVES: Because physicians' decisions drive health care costs and quality, there is growing interest in applying behavioral economics approaches, including behavioral nudges, to influence physicians' decisions. This paper investigates adoption of behavioral nudges by health system-affiliated physician organizations (POs), types of nudges being used, PO leader perceptions of nudge effectiveness, and implementation challenges. STUDY DESIGN: Mixed-methods study design (PO leader survey followed by in-depth qualitative interviews). Purposive sample of 30 health system-affiliated POs in 4 states; POs varied in size and quality performance. METHODS: We collected data between October 2017 and June 2019. The survey asked PO leaders to report their organization's use of 5 categories of nudges to influence primary and specialty physicians' actions. We conducted semistructured phone interviews to confirm survey responses, elicit examples of the nudges that POs reported using, understand how nudges were structured, and identify implementation challenges. We present descriptive tabulations of nudge use and effectiveness ratings. We applied thematic analysis to the interview data. RESULTS: Almost all POs in this study reported nudge use. Clinical templates, patient action lists, and altered order entry were most commonly used. However, PO leaders reported that nudge use was limited to a narrow range of clinical applications, not widespread across the organization, and mostly structured as suggestions rather than default actions or hard stops. CONCLUSIONS: Nudge use remains limited in practice. Opportunities exist to expand use of nudges to influence physician behavior; however, expanding use of behavioral nudges will require PO investment of resources to support their construction and maintenance.