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.

Estimated Annual Spending on Aducanumab in the US Medicare Program.

This cross-sectional study examines upper bound and lower bound annualized Medicare costs for administering aducanumab to beneficiaries with the approved indications of mild cognitive impairment or mild dementia.

Physician Compensation Arrangements and Financial Performance Incentives in US Health Systems.

Importance: Public and private payers continue to expand use of alternative payment models, aiming to use value-based payment to affect the care delivery of their contracted health system partners. In parallel, health systems and their employment of physicians continue to grow. However, the degree to which health system physician compensation reflects an orientation toward value, rather than volume, is unknown. Objective: To characterize primary care physician (PCP) and specialist compensation arrangements among US health system-affiliated physician organizations (POs) and measure the portion of total physician compensation based on quality and cost performance. Design Setting and Participants: This study was a cross-sectional mixed-methods analysis of in-depth multimodal data (compensation document review, interviews with 40 PO leaders, and surveys conducted between November 2017 and July 2019) from 31 POs affiliated with 22 purposefully selected health systems in 4 states. Data were analyzed from June 2019 to September 2020. Main Outcomes and Measures: The frequency of PCP and specialist compensation types and the percentage of compensation when included, including base compensation incentives, quality and cost performance incentives, and other financial incentives. The top 3 actions physicians could take to increase their compensation. The association between POs' percentage of revenue from fee-for-service and their physicians' volume-based compensation percentage. Results: Volume-based compensation was the most common base compensation incentive component for PCPs (26 POs [83.9%]; mean, 68.2% of compensation; median, 81.4%; range, 5.0%-100.0% when included) and specialists (29 POs [93.3%]; mean, 73.7% of compensation; median, 90.5%; range, 2.5%-100.0% when included). While quality and cost performance incentives were common (included by 83.9%-56.7% of POs for PCPs and specialists, respectively), the percentage of compensation based on quality and cost performance was modest (mean, 9.0% [median, 8.3%; range, 1.0%-25.0%] for PCPs and 5.3% [median, 4.5%; range, 0.5%-16.0%] for specialists when included). Increasing the volume of services was the most commonly cited action for physicians to increase compensation, reported as the top action by 22 POs (70.0%) for PCPs and specialists. We observed a very weak, nonsignificant association between the percentage of revenue of POs from fee for service and the PCP and specialist volume-based compensation percentage (r = 0.08; P = .78 and r = -0.04; P = .89, respectively). Conclusions and Relevance: The results of this cross-sectional study suggest that PCPs and specialists despite receiving value-based reimbursement incentives from payers, the compensation of health system PCPs and specialists was dominated by volume-based incentives designed to maximize health systems revenue.

Predicting Race And Ethnicity To Ensure Equitable Algorithms For Health Care Decision Making.

Algorithms are currently used to assist in a wide array of health care decisions. Despite the general utility of these health care algorithms, there is growing recognition that they may lead to unintended racially discriminatory practices, raising concerns about the potential for algorithmic bias. An intuitive precaution against such bias is to remove race and ethnicity information as an input to health care algorithms, mimicking the idea of "race-blind" decisions. However, we argue that this approach is misguided. Knowledge, not ignorance, of race and ethnicity is necessary to combat algorithmic bias. When race and ethnicity are observed, many methodological approaches can be used to enforce equitable algorithmic performance. When race and ethnicity information is unavailable, which is often the case, imputing them can expand opportunities to not only identify and assess algorithmic bias but also combat it in both clinical and nonclinical settings. A valid imputation method, such as Bayesian Improved Surname Geocoding, can be applied to standard data collected by public and private payers and provider entities. We describe two applications in which imputation of race and ethnicity can help mitigate potential algorithmic biases: equitable disease screening algorithms using machine learning and equitable pay-for-performance incentives.

Is Bigger Better?: A Closer Look at Small Health Systems in the United States.

BACKGROUND: Research on US health systems has focused on large systems with at least 50 physicians. Little is known about small systems. OBJECTIVES: Compare the characteristics, quality, and costs of care between small and large health systems. RESEARCH DESIGN: Retrospective, repeated cross-sectional analysis. SUBJECTS: Between 468 and 479 large health systems, and between 608 and 641 small systems serving fee-for-service Medicare beneficiaries, yearly between 2013 and 2017. MEASURES: We compared organizational, provider and beneficiary characteristics of large and small systems, and their geographic distribution, using multiple Medicare and Internal Revenue Service administrative data sources. We used mixed-effects regression models to estimate differences between small and large systems in claims-based Healthcare Effectiveness Data and Information Set (HEDIS) quality measures and HealthPartners' Total Cost of Care measure using a 100% sample of Medicare fee-for-service claims. We fit linear spline models to examine the relationship between the number of a system's affiliated physicians and its quality and costs. RESULTS: The number of both small and large systems increased from 2013 to 2017. Small systems had a larger share of practice sites (43.1% vs. 11.7% for large systems in 2017) and beneficiaries (51.4% vs. 15.5% for large systems in 2017) in rural areas or small towns. Quality performance was lower among small systems than large systems (-0.52 SDs of a composite quality measure) and increased with system size up to ∼75 physicians. There was no difference in total costs of care. CONCLUSIONS: Small systems are a growing source of care for rural Medicare populations, but their quality performance lags behind large systems. Future studies should examine the mechanisms responsible for quality differences.

Trends in US Ambulatory Care Patterns During the COVID-19 Pandemic, 2019-2021.

Importance: Following reductions in US ambulatory care early in the pandemic, it remains unclear whether care consistently returned to expected rates across insurance types and services. Objective: To assess whether patients with Medicaid or Medicare-Medicaid dual eligibility had significantly lower than expected return to use of ambulatory care rates than patients with commercial, Medicare Advantage, or Medicare fee-for-service insurance. Design, Setting, and Participants: In this retrospective cohort study examining ambulatory care service patterns from January 1, 2019, through February 28, 2021, claims data from multiple US payers were combined using the Milliman MedInsight research database. Using a difference-in-differences design, the extent to which utilization during the pandemic differed from expected rates had the pandemic not occurred was estimated. Changes in utilization rates between January and February 2020 and each subsequent 2-month time frame during the pandemic were compared with the changes in the corresponding months from the year prior. Age- and sex-adjusted Poisson regression models of monthly utilization counts were used, offsetting for total patient-months and stratifying by service and insurance type. Exposures: Patients with Medicaid or Medicare-Medicaid dual eligibility compared with patients with commercial, Medicare Advantage, or Medicare fee-for-service insurance, respectively. Main Outcomes and Measures: Utilization rates per 100 people for 6 services: emergency department, office and urgent care, behavioral health, screening colonoscopies, screening mammograms, and contraception counseling or HIV screening. Results: More than 14.5 million US adults were included (mean age, 52.7 years; 54.9% women). In the March-April 2020 time frame, the combined use of 6 ambulatory services declined to 67.0% (95% CI, 66.9%-67.1%) of expected rates, but returned to 96.7% (95% CI, 96.6%-96.8%) of expected rates by the November-December 2020 time frame. During the second COVID-19 wave in the January-February 2021 time frame, overall utilization again declined to 86.2% (95% CI, 86.1%-86.3%) of expected rates, with colonoscopy remaining at 65.0% (95% CI, 64.1%-65.9%) and mammography at 79.2% (95% CI, 78.5%-79.8%) of expected rates. By the January-February 2021 time frame, overall utilization returned to expected rates as follows: patients with Medicaid at 78.4% (95% CI, 78.2%-78.7%), Medicare-Medicaid dual eligibility at 73.3% (95% CI, 72.8%-73.8%), commercial at 90.7% (95% CI, 90.5%-90.9%), Medicare Advantage at 83.2% (95% CI, 81.7%-82.2%), and Medicare fee-for-service at 82.0% (95% CI, 81.7%-82.2%; P < .001; comparing return to expected utilization rates among patients with Medicaid and Medicare-Medicaid dual eligibility, respectively, with each of the other insurance types). Conclusions and Relevance: Between March 2020 and February 2021, aggregate use of 6 ambulatory care services increased after the preceding decrease in utilization that followed the onset of the COVID-19 pandemic. However, the rate of increase in use of these ambulatory care services was significantly lower for participants with Medicaid or Medicare-Medicaid dual eligibility than for those insured by commercial, Medicare Advantage, or Medicare fee-for-service.

Actions to improve quality: results from a national hospital survey.

OBJECTIVES: CMS measures and reports hospital performance to drive quality improvement (QI), but information on actions that hospitals have taken in response to quality measurement is lacking. We aimed to develop national estimates of QI actions undertaken by hospitals and to explore their relationship to performance on CMS quality measures. STUDY DESIGN: Nationally representative cross-sectional survey of acute care hospitals in 2016 (n = 1313 respondents; 64% response rate). METHODS: We assessed 23 possible QI changes. Using multivariate linear regression, we estimated the relationship between reported QI changes and performance on composite measures derived from 26 Hospital Inpatient Quality Reporting Program measures (scaled 0-100), controlling for case mix and facility characteristics. RESULTS: Hospitals reported implementing a mean of 17 QI changes (median [interquartile range], 17 [15-20]). Large hospitals reported significantly higher adoption rates than small hospitals for 18 QI changes. Most hospitals that reported making QI changes (63%-96% for the 23 changes) responded that the specific change made helped improve performance. In multivariate regression analyses, adoption of 92% of QI changes (90th percentile among hospitals), compared with adoption of 50% of QI changes (10th percentile), was associated with a 2.3-point higher overall performance score (95% CI, 0.7-4.0) and higher process (8.7 points; 95% CI, 5.7-11.7) and patient experience (3.0 points; 95% CI, 0.1-5.9) composite scores. CONCLUSIONS: Hospitals reported widespread adoption of QI changes in response to CMS quality measurement and reporting. Higher QI adoption rates were associated with modestly higher process, patient experience, and overall performance composite scores.

Alignment Between Objective and Subjective Assessments of Health System Performance: Findings From a Mixed-Methods Study.

EXECUTIVE SUMMARY: The article examines whether subjective performance assessments from health system executives match objective performance assessments and qualitatively explores ways to achieve high performance. We interviewed 138 C-suite executives of 24 health systems in California, Minnesota, Washington, and Wisconsin between 2017 and 2019. We used maximum variation sampling to select health systems to achieve diversity in performance on objective measures of clinical performance. Our interviews focused on executives' perceptions of their own health system's performance and factors they thought generally contributed to high performance. In our analysis, we grouped health systems based on objective performance levels (high, medium, and low) used in sampling, compared objective performance ratings with executives' subjective performance assessments, and used thematic analysis to identify reasons for subjective assessment of health system performance and levers of high performance in general. There was poor agreement between objective and subjective performance assessments (kappa = 0.082). Subjective assessments were higher than objective assessments and captured more factors than are typically considered in performance accountability and value-based payment initiatives. Executives whose views were inconsistent with objective performance assessments did not cite clinical care quality per se as the basis for their assessment, focusing instead on market competition, financial performance, and high customer satisfaction and loyalty. Executives who cited clinical quality metrics as the basis of their assessment offered subjective ratings consistent with objective ratings. Executives identified organizational culture, organizational governance, and staff engagement as levers for achieving high performance. Future research should explore the benefits and drawbacks of considering subjective performance assessments in value-based payment initiatives.

Home health agency adoption of quality improvement activities and association with performance.

BACKGROUND: The Centers for Medicare & Medicaid Services (CMS) Home Health Quality Reporting Program (HHQRP) uses performance measurement to spur improvements in home health agencies' (HHAs') quality of care. We examined quality improvement (QI) activities HHAs reported making to improve on HHQRP quality measures, and whether reported QI activities were associated with better measure performance. METHODS: We used responses (N = 1052) from a Web- and mail-based survey of a stratified random sample of HHAs included in CMS Home Health Compare in October 2019. We estimated national adoption rates for 27 possible QI activities related to organizational culture, health information technology, care process redesign, provider incentives, provider training, changes to staffing responsibilities, performance monitoring, and measure-specific QI initiatives and technical assistance. We used multivariate linear regression to examine the associations between HHA characteristics and QI adoption, and between QI adoption and CMS Home Health Quality of Patient Care Star Rating. RESULTS: HHAs reported implementing an average of 16 QI activities (interquartile range 11-19 activities). Larger HHA size was associated with adopting 1.6 additional QI activities (p < 0.001). HHAs with higher proportions of disabled, black, or Hispanic patients adopted QI activities at similar or higher rates as other HHAs. Of the 27 QI activities, 23 were considered helpful by more than 80% of adopting HHAs. Compared with adopting 44% of QI activities (10th percentile among HHAs), adopting 89% of QI activities (90th percentile) was associated with a 0.4-star higher Star Rating (95% confidence interval 0.2-0.6). CONCLUSIONS: HHAs report implementing a significant number of QI activities in response to CMS measurement programs; implementation of a greater number of activities is associated with better performance on publicly reported measures. To guide future HHA QI investments, work is needed to identify the optimal combination of QI activities and the specific QI activities that yield the greatest performance improvements.

Higher Medicare Spending On Imaging And Lab Services After Primary Care Physician Group Vertical Integration.

In recent years direct ownership of physician practices by hospitals and health systems (that is, vertical integration) has become a prominent feature of the US health care system. One unexplored impact of vertical integration is the impact on referral patterns for common diagnostic tests and procedures and the associated spending. Using a 100 percent sample of 2013-16 Medicare fee-for-service claims data, we examined whether hospital and health system ownership of physician practices was associated with changes in site of care and Medicare reimbursement rates for ten common diagnostic imaging and laboratory services. After vertical integration, the monthly number of diagnostic imaging tests per 1,000 attributed beneficiaries performed in a hospital setting increased by 26.3 per 1,000, and the number performed in a nonhospital setting decreased by 24.8 per 1,000. Hospital-based laboratory tests increased by 44.5 per 1,000 attributed beneficiaries, and non-hospital-based laboratory tests decreased by 36.0 per 1,000. Average Medicare reimbursement rose by $6.38 for imaging tests and $0.57 for laboratory tests, which translates to $40.2 million and $32.9 million increases in Medicare spending, respectively, for the entire study period. This study highlights how the growing trend of vertical integration, combined with differences in Medicare payment between hospitals and nonhospital providers, leads to higher Medicare spending.