Publications by authors named "Michael McWilliams"

126 Publications

ACO Investment Model Produced Savings, But The Majority Of Participants Exited When Faced With Downside Risk.

Health Aff (Millwood) 2022 Jan;41(1):138-146

Brant Morefield, Aledade, Inc., Bethesda, Maryland.

Medicare's Accountable Care Organization (ACO) Investment Model (AIM) provided up-front funding to forty-one small, rurally located ACOs to encourage their participation in the Medicare Shared Savings Program. We estimate net savings to Medicare of $381.5 million over three years, driven by utilization reductions in inpatient and other institutional care and by the absence of shared risk for potential increases in Medicare spending incurred by participants. These savings suggest that population-based payment models can enable providers to better meet the needs of rural populations through greater flexibility in care delivery. However, nearly two-thirds of AIM ACOs exited the Medicare Shared Savings Program when faced with the requirement to assume downside financial risk, starting in year four of participation. As the Centers for Medicare and Medicaid Services builds on AIM and rural hospital global payment models, our findings suggest that new payment models can support more efficient use of resources to meet the health care needs of rural populations. However, the findings also caution against the vigorous pursuit of savings as a primary goal of payment models in traditionally underserved communities.
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http://dx.doi.org/10.1377/hlthaff.2020.01819DOI Listing
January 2022

Residual Confounding in Health Plan Performance Assessments: Evidence From Randomization in Medicaid.

Ann Intern Med 2022 Jan 4. Epub 2022 Jan 4.

Yale School of Public Health, New Haven, Connecticut (J.W., A.L., C.D.N.).

Background: Risk adjustment is used widely in payment systems and performance assessments, but the extent to which it distinguishes plan or provider effects from confounding due to patient differences is typically unknown.

Objective: To assess the degree to which risk-adjusted measures of health plan performance adequately adjust for the variation across plans that arises because of differences in patient characteristics (residual confounding).

Design: Comparison between plan performance estimates based on enrollees who made plan choices (observational population) and estimates based on enrollees assigned to plans (randomized population).

Setting: Natural experiment in which more than two thirds of a state's Medicaid population in 1 region was randomly assigned to 1 of 5 plans.

Participants: 137 933 enrollees in 2013 to 2014, of whom 31.1% selected a plan and 68.9% were randomly assigned to 1 of the same 5 plans.

Measurements: Annual total spending (that is, payments to providers), primary care use, dental care use, and avoidable emergency department visits, all scored as plan-specific deviations from the "average" plan performance within each population.

Results: Enrollee characteristics were appreciably imbalanced across plans in the observational population, as expected, but were not in the randomized population. Annual total spending varied across plans more in the observational population (SD, $147 per enrollee) than in the randomized population (SD, $70 per enrollee) after accounting for baseline differences in the observational and randomized populations and for differences across plans. On average, a plan's spending score (its deviation from the "average" performance) in the observational population differed from its score in the randomized population by $67 per enrollee in absolute value (95% CI, $38 to $123), or 4.2% of mean spending per enrollee ( = 0.009, rejecting the null hypothesis that this difference would be expected from sampling error). The difference was reduced modestly by risk adjustment to $62 per enrollee ( = 0.012). Residual confounding was similarly substantial for most other performance measures. Further adjustment for social factors did not materially change estimates.

Limitation: Potential heterogeneity in plan effects between the 2 populations.

Conclusion: Residual confounding in risk-adjusted performance assessments can be substantial and should caution policymakers against assuming that risk adjustment isolates real differences in plan performance.

Primary Funding Source: Arnold Ventures.
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http://dx.doi.org/10.7326/M21-0881DOI Listing
January 2022

An analysis of Medicare accountable care organization expense reports.

Am J Manag Care 2021 Dec;27(12):569-572

Abt Associates, 10 Fawcett St, Cambridge, MA 02138. Email:

Objectives: To understand the investments that Medicare Shared Savings Program accountable care organizations (ACOs) in the ACO Investment Model (AIM) made to participate in the program and the costs that they incurred as a result of their efforts to lower spending and improve quality.

Study Design: We conducted a systematic review and categorization of all available and approved quarterly expenses reported by AIM ACOs.

Methods: We reviewed final approved quarterly expense reports submitted by ACOs detailing how they spent funds in the quarter. All distinct line-item descriptions were classified into a more informative and consistent set of categories. We then applied higher conceptual dimensions (type of care input and type of ACO strategy) to these newly categorized expenses to facilitate additional analysis of spending patterns.

Results: AIM ACOs reported expenses of $264.8 million over the 3 performance years (2016-2018). The majority of the $264.8 million in expenditures was incurred for personnel (55.5%), followed by infrastructure (22.3%), management firm expenses (15.3%), and internal programs and systems (6.9%). The dominant identifiable ACO strategy was care coordination and management, accounting for 52.9% of related ACO expenses.

Conclusions: AIM ACOs invested most heavily in personnel, information technology, and care management, with less than half of the investments explicitly tied to a strategy for improving quality or reducing spending. Efforts to change clinician practice patterns, alter the way patients access the health care system, and institute other practice redesigns were not primary targets for investment.
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http://dx.doi.org/10.37765/ajmc.2021.88795DOI Listing
December 2021

Coding-Driven Changes In Measured Risk In Accountable Care Organizations.

Health Aff (Millwood) 2021 Dec;40(12):1909-1917

Mary Beth Landrum is a professor of health care policy in the Department of Health Care Policy, Harvard Medical School.

Claims data, which form the foundation of risk adjustment in payment for health care services, may reflect efforts to capture more-or more severe-clinical conditions rather than true changes in health status. This can distort payments. We quantify this in the context of Medicare's accountable care organization (ACO) program by comparing risk scores derived from two different measurement approaches. One approach uses diagnoses coded on claims based on Centers for Medicare and Medicaid Services Hierarchical Condition Categories (HCC), and the other uses self-reported, survey-based health data from the Consumer Assessment of Healthcare Providers and Systems (CAHPS). During 2013-16 HCC-based risk scores grew faster than CAHPS-based risk scores (2.1 percent versus 0.3 percent annually), and the gap in HCC- and CAHPS-based risk score growth varied widely across ACOs. The average gap in risk score growth appears to be the result primarily of HCC coding practices rather than poor performance of the CAHPS model, suggesting that coding practices (not necessarily driven by ACO contracts) may account for most of the observed risk score growth for ACO beneficiaries.
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http://dx.doi.org/10.1377/hlthaff.2021.00361DOI Listing
December 2021

Changes in patient experiences and assessment of gaming among large clinician practices in precursors of the Merit-Based Incentive Payment System.

JAMA Health Forum 2021 Oct 8;2(10). Epub 2021 Oct 8.

Department of Health Care Policy, Harvard Medical School in Boston, MA; Division of General Internal Medicine and Primary Care, Brigham and Women's Hospital in Boston.

Importance: Medicare's Merit-Based Incentive Payment System (MIPS), a public reporting and pay-for-performance program, adjusts clinician payments based on publicly reported measures that are chosen primarily by clinicians or their practices. However, measure selection raises concerns that practices could earn bonuses or avoid penalties by selecting measures on which they already perform well, rather than by improving care-a form of gaming. This has prompted calls for mandatory reporting on a smaller set of measures including patient experiences.

Objectives: Within precursor programs of the MIPS, this study examined 1) practices' selection of Consumer Assessment of Healthcare Providers and Systems (CAHPS) patient experience measures for quality scoring under pay-for-performance and 2) the association between mandated public reporting on CAHPS measures and performance on those measures.

Design Setting And Participants: This study included 2 analyses. The first analysis examined the association between the baseline CAHPS scores of large practices (≥100 clinicians) and practices' selection of these measures for quality scoring under pay-for-performance up to 2 years later. The second analysis examined changes in patient experiences associated with a requirement that large practices publicly report CAHPS measures starting in 2014. A difference-in-differences analysis of 2012-2017 fee-for-service Medicare CAHPS data was conducted to compare changes in patient experiences between large practices (111-150 clinicians) that became subject to this reporting mandate and smaller unaffected practices (50-89 clinicians). Analyses were conducted between October 1, 2020 and July 30, 2021.

Main Outcomes And Measures: CAHPS measures.

Results: Among 301 large practices that publicly reported patient experience measures, the mean age of patients at baseline was 71.6 years (interquartile range [IQR] across practices: 70.4-73.2 years) and 55.8% of patients were female (IQR: 54.3%-57.7%). Large practices in the top vs. bottom quintile of patient experience scores at baseline were more likely to voluntarily include these scores in the pay-for-performance program two years later (96.3% vs. 67.9%), a difference of 28.4 percentage points (95% CI: 9.4,47.5 percentage points; =0.004). After 2-3 years of the reporting mandate, patient experiences did not differentially improve in affected vs. unaffected practices (difference-in-differences estimate: -0.03 practice-level standard deviations of the composite score; 95% CI: -0.64,0.58; =0.92).

Conclusions: In this study of US physician practices that participated in precursors of the MIPS, large practices were found to select measures on which they were already performing well for a pay-for-performance program, consistent with gaming. However, mandating public reporting was not associated with improved patient experiences. These findings support recommendations to end optional measures in the MIPS but also suggest that public reporting on mandated measures may not improve care.
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http://dx.doi.org/10.1001/jamahealthforum.2021.3105DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8623747PMC
October 2021

340B Drug Pricing Program and hospital provision of uncompensated care.

Am J Manag Care 2021 10;27(10):432-437

Department of Population Health, New York University School of Medicine, 227 E 30th St #635, New York, NY 10016. Email:

Objectives: To evaluate whether hospital entry into the 340B Drug Pricing Program, which entitles eligible hospitals to discounts on drug purchases and intends for hospitals to use associated savings to devote more resources to the care of low-income populations, is associated with changes in hospital provision of uncompensated care.

Study Design: We analyzed secondary data on 340B participation and uncompensated care provision among general acute care hospitals and critical access hospitals from 2003 to 2015. We constructed an annual, hospital-level data set on hospital 340B participation from the Office of Pharmacy Information Systems and on uncompensated care provision from the Hospital Cost Reporting Information System.

Methods: Focusing on 2 periods of program expansion, we separately analyzed trends in uncompensated care costs for 340B-eligible general acute care hospitals and critical access hospitals, stratified by year of 340B program entry, including a stratum of eligible hospitals that never participated. We used a differences-in-differences approach to quantify whether there were differential changes in provision of uncompensated care after hospitals enter the 340B program relative to hospitals that did not participate or had not yet entered.

Results: We do not find evidence that hospitals increased provision of uncompensated care after entry into the 340B program differentially more than hospitals that never entered or had not yet entered the program.

Conclusions: Relying on hospitals to invest surplus into care for the underserved without marginal incentives to do so or strong oversight may not be an effective strategy to expand safety-net care.
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http://dx.doi.org/10.37765/ajmc.2021.88761DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8544813PMC
October 2021

Analysis of Consistency in Emergency Department Physician Variation in Propensity for Admission Across Patient Sociodemographic Groups.

JAMA Netw Open 2021 09 1;4(9):e2125193. Epub 2021 Sep 1.

Department of Emergency Medicine, University of Massachusetts Medical School, Worcester.

Importance: Sociodemographic disparities in health care and variation in physician practice patterns have been well documented; however, the contribution of variation in individual physician care practices to health disparities is challenging to quantify. Emergency department (ED) physicians vary in their propensity to admit patients. The consistency of this variation across sociodemographic groups may help determine whether physician-specific factors are associated with care differences between patient groups.

Objective: To estimate the consistency of ED physician admission propensities across categories of patient sex, race and ethnicity, and Medicaid enrollment.

Design, Setting, And Participants: This cross-sectional study analyzed Medicare fee-for-service claims for ED visits from January 1, 2016, to December 31, 2019, in a 10% random sample of hospitals. The allocation of patients to ED physicians in the acute care setting was used to isolate physician-level variation in admission rates that reflects variation in physician decision-making. Multi-level models with physician random effects and hospital fixed effects were used to estimate the within-hospital physician variation in admission propensity for different patient sociodemographic subgroups and the covariation in these propensities between subgroups (consistency), adjusting for primary diagnosis and comorbidities.

Main Outcomes And Measures: Admission from the ED.

Results: The analysis included 4 567 760 ED visits involving 2 334 361 beneficiaries and 15 767 physicians in 396 EDs. The mean (SD) age of the beneficiaries was 78 (8.2) years, 2 700 661 visits (59.1%) were by women, and most patients (3 839 055 [84.1%]) were not eligible for Medicaid. Of 4 473 978 race and ethnicity reports on enrollment, 103 699 patients (2.3%) were Asian/Pacific Islander, 421 588 (9.4%) were Black, 257 422 (5.8%) were Hispanic, and 3 691 269 (82.5%) were non-Hispanic White. Within hospitals, adjusted rates of admission were higher for men (36.8%; 95% CI, 36.8%-36.9%) than for women (33.7%; 95% CI, 33.7%-33.8%); higher for non-Hispanic White (36.0%; 95% CI, 35.9%-36.0%) than for Asian/Pacific Islander (33.6%; 95% CI, 33.3%-33.9%), Black (30.2%; 95% CI, 30.0%-30.3%), or Hispanic (31.1%; 95% CI, 30.9%-31.2%) beneficiaries; and higher for beneficiaries dually enrolled in Medicaid (36.3%; 95% CI, 36.2%-36.5%) than for those who were not (34.7%; 95% CI, 34.7%-34.8%). Within hospitals, physicians varied in the percentage of patients admitted, ranging from 22.4% for physicians at the 10th percentile to 47.6% for physicians at the 90th percentile of the estimated distribution. Physician admission propensities were correlated between men and women (r = 0.99), Black and non-Hispanic White patients (r = 0.98), and patients who were dually enrolled and not dually enrolled in Medicaid (r = 0.98).

Conclusions And Relevance: This cross-sectional study indicated that, although overall rates of admission differ systematically by patient sociodemographic factors, an individual physician's propensity to admit relative to other physicians appears to be applied consistently across sociodemographic groups of patients.
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http://dx.doi.org/10.1001/jamanetworkopen.2021.25193DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8456378PMC
September 2021

National Trends In ED Visits, Hospital Admissions, And Mortality For Medicare Patients During The COVID-19 Pandemic.

Health Aff (Millwood) 2021 09;40(9):1457-1464

Bruce E. Landon is a professor of health care policy in the Department of Health Care Policy at Harvard Medical School and a professor of medicine and practicing internist at Beth Israel Deaconess Medical Center.

Concerns about avoidance or delays in seeking emergency care during the COVID-19 pandemic are widespread, but national data on emergency department (ED) visits and subsequent rates of hospitalization and outcomes are lacking. Using data on all traditional Medicare beneficiaries in the US from October 1, 2018, to September 30, 2020, we examined trends in ED visits and rates of hospitalization and thirty-day mortality conditional on an ED visit for non-COVID-19 conditions during several stages of the pandemic and for areas that were considered COVID-19 hot spots versus those that were not. We found reductions in ED visits that were largest by the first week of April 2020 (52 percent relative decrease), with volume recovering somewhat by mid-June (25 percent relative decrease). These reductions were of similar magnitude in counties that were and were not designated as COVID-19 hot spots. There was an early increase in hospitalizations and in the relative risk for thirty-day mortality, starting with the first surge of the pandemic, peaking at just over a 2-percentage-point increase. These results suggest that patients were presenting with more serious illness, perhaps related to delays in seeking care.
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http://dx.doi.org/10.1377/hlthaff.2021.00561DOI Listing
September 2021

Using Consistently Low Performance to Identify Low-Quality Physician Groups.

JAMA Netw Open 2021 07 1;4(7):e2117954. Epub 2021 Jul 1.

Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts.

Importance: There has been a growth in the use of performance-based payment models in the past decade, but inherently noisy and stochastic quality measures complicate the assessment of the quality of physician groups. Examining consistently low performance across multiple measures or multiple years could potentially identify a subset of low-quality physician groups.

Objective: To identify low-performing physician groups based on consistently low performance after adjusting for patient characteristics across multiple measures or multiple years for 10 commonly used quality measures for diabetes and cardiovascular disease (CVD).

Design, Setting, And Participants: This cross-sectional study used medical and pharmacy claims and laboratory data for enrollees ages 18 to 65 years with diabetes or CVD in an Aetna health insurance plan between 2016 and 2019. Each physician group's risk-adjusted performance for a given year was estimated using mixed-effects linear probability regression models. Performance was correlated across measures and time, and the proportion of physician groups that performed in the bottom quartile was examined across multiple measures or multiple years. Data analysis was conducted between September 2020 and May 2021.

Exposures: Primary care physician groups.

Main Outcomes And Measures: Performance scores of 6 quality measures for diabetes and 4 for CVD, including hemoglobin A1c (HbA1c) testing, low-density lipoprotein testing, statin use, HbA1c control, low-density lipoprotein control, and hospital-based utilization.

Results: A total of 786 641 unique enrollees treated by 890 physician groups were included; 414 655 (52.7%) of the enrollees were men and the mean (SD) age was 53 (9.5) years. After adjusting for age, sex, and clinical and social risk variables, correlations among individual measures were weak (eg, performance-adjusted correlation between any statin use and LDL testing for patients with diabetes, r = -0.10) to moderate (correlation between LDL testing for diabetes and LDL testing for CVD, r = .43), but year-to-year correlations for all measures were moderate to strong. One percent or fewer of physician groups performed in the bottom quartile for all 6 diabetes measures or all 4 cardiovascular disease measures in any given year, while 14 (4.0%) to 39 groups (11.1%) were in the bottom quartile in all 4 years for any given measure other than hospital-based utilization for CVD (1.1%).

Conclusions And Relevance: A subset of physician groups that was consistently low performing could be identified by considering performance measures across multiple years. Considering the consistency of group performance could contribute a novel method to identify physician groups most likely to benefit from limited resources.
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http://dx.doi.org/10.1001/jamanetworkopen.2021.17954DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8319756PMC
July 2021

Variation in Rates of Hospital Admission from the Emergency Department Among Medicare Patients at the Regional, Hospital, and Physician Levels.

Ann Emerg Med 2021 10 18;78(4):474-483. Epub 2021 Jun 18.

Department of Health Care Policy, Harvard Medical School and Division of General Internal Medicine, Beth Israel Deaconess Medical Center, Boston, MA.

Study Objective: Rates of admission from the emergency department (ED) vary widely across regions of the country, hospitals within regions, and physicians within hospitals. Our objective was to determine the extent to which variation in admission decisions was described by differences in admission rates at these 3 levels. This understanding will serve to better target interventions to modify rates of admission where appropriate.

Methods: In this cross-sectional observational cohort study, we analyzed Medicare fee-for-service claims for ED visits from 2012 to 2015 in a 20% random sample of beneficiaries. We first estimated the total regional-, hospital-, and physician-level variations in rates of admission and their proportions of the total variation after adjusting for patient and each level's covariates. We then estimated the extent to which each level's characteristics accounted for variation at that respective level.

Results: Our study sample included 5,778,218 visits with 45,491 physicians at 3,480 EDs across 306 hospital referral regions. The mean rate of admission was 38.9% and ranged from 21.4% to 53.0% for physicians at the 10 and 90 percentile of the distribution, respectively. The residual (unexplained) variations at the regional, hospital, and physician levels were 13.3% (95% confidence interval [CI], 11.2 to 15.5%), 60.1% (57.1 to 62.9%), and 26.7% (26.4 to 26.9%), respectively. Regional, hospital, and physician characteristics accounted for 9.1% (95% CI, -5.6 to 23.8%), 51.1% (48.8 to 53.5%), and 2.7% (1.3 to 4.1%), respectively, of the explained variation at their respective levels.

Conclusion: Within-area variation, both across hospitals within a region and across physicians within a hospital, is a more substantial component of observed variation in admission rates from the ED than regional level variation. These findings suggest that variation in admission rates is at least in part related to institutional norms and cultures as well as heterogeneity of physician decisionmaking within hospitals, both of which could be targets of interventions to modify rates of admission.
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http://dx.doi.org/10.1016/j.annemergmed.2021.03.020DOI Listing
October 2021

Early Hospital Compliance With Federal Requirements for Price Transparency.

JAMA Intern Med 2021 10;181(10):1396-1397

Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts.

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http://dx.doi.org/10.1001/jamainternmed.2021.2531DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8204253PMC
October 2021

Soft Consolidation In Medicare ACOs: Potential For Higher Prices Without Mergers Or Acquisitions.

Health Aff (Millwood) 2021 06;40(6):979-988

J. Michael McWilliams is the Warren Alpert Foundation Professor of Health Care Policy in the Department of Health Care Policy at Harvard Medical School and a professor of medicine and general internist at Brigham and Women's Hospital, in Boston, Massachusetts.

Antitrust guidance specifies that participation in Medicare accountable care organizations (ACOs) is sufficient to meet clinical integration standards for separately owned providers to jointly negotiate with insurers. Accordingly, ACO participation may facilitate price increases through a less conventional, "softer" consolidation that would not be categorically challenged as price fixing. Using commercial claims and data on health system membership and ACO participation, we found some abrupt, large price increases for independent primary care practices that joined health system-led ACOs but were not acquired by systems. These price jumps were rare, however, increasing prices by just 4 percent, on average, among all independent practices in system-led ACOs. Additional analyses suggested minimal increases in health systems' primary care prices or market shares from ACO contracting. Thus, the price jumps were more consistent with an extension of existing pricing power from systems to some independent practices than with a major expansion of system market power. Nevertheless, the potential for growth of these arrangements through ACOs argues for closer monitoring and evaluation.
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http://dx.doi.org/10.1377/hlthaff.2020.02449DOI Listing
June 2021

Association of Low-Value Care Exposure With Health Care Experience Ratings Among Patient Panels.

JAMA Intern Med 2021 07;181(7):941-948

Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts.

Importance: Patient reviews of health care experiences are increasingly used for public reporting and alternative payment models. Critics have argued that this incentivizes physicians to provide more care, including low-value care, undermining efforts to reduce wasteful practices.

Objective: To assess associations between rates of low-value service provision to a primary care professional (PCP) patient panel and patients' ratings of their health care experiences.

Design, Setting, And Participants: This quality improvement study used Medicare fee-for-service claims from January 1, 2007, to December 31, 2014, for a random 20% sample of beneficiaries to identify beneficiaries for whom each of 8 low-value services could be ordered but would be considered unnecessary. The study also used health care experience reports from independently sampled beneficiaries who responded to the 2010-2015 Consumer Assessment of Healthcare Providers and Systems (CAHPS) Medicare fee-for-service survey. Statistical analysis was performed from January 1, 2019, to December 9, 2020.

Main Outcomes And Measures: The main outcomes were health care experience ratings from Medicare beneficiaries who responded to the CAHPS survey from 2 domains, namely "Your Health Care in the Last 6 Months" (overall health care, office wait time, timely access to nonurgent care, and timely access to urgent care) and "Your Personal Doctor" (overall personal physician and a composite score for interactions with personal physician). Beneficiaries in both samples were attributed to the PCP with whom they had the most spending. For each PCP, a composite score of low-value service exposure was constructed using the 20% sample; this score represented the adjusted relative propensity of the PCP patient panel to receive low-value care. The association between low-value service exposure and health care experience ratings reported by the CAHPS respondents in the PCP patient panel was estimated using regression analysis.

Results: The final sample had 100 743 PCPs, with a mean of approximately 258 patients per PCP. Only 1 notable association was found; more low-value care exposure was associated with more frequent reports of having to wait more than 15 minutes after the scheduled time of an appointment (a mean of 0.448 points lower CAHPS score on a 10-point scale for PCP patient panels who received the most low-value care vs the least low-value care). Although some other associations were statistically significant, their magnitudes were substantially smaller than those typically considered meaningful in other CAHPS literature and were inconsistent in direction across levels of low-value service exposure.

Conclusions And Relevance: This quality improvement study found that more low-value care exposure for a PCP patient panel was not associated with more favorable patient ratings of their health care experiences.
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http://dx.doi.org/10.1001/jamainternmed.2021.1974DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8261613PMC
July 2021

Hospital Responses to Incentives in Episode-Based Payment for Joint Surgery: A Controlled Population-Based Study.

JAMA Intern Med 2021 07;181(7):932-940

Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts.

Importance: Medicare's Comprehensive Care for Joint Replacement (CJR) model, initiated in 2016, is a national episode-based payment model for lower-extremity joint replacement (LEJR). Metropolitan statistical areas (MSAs) were randomly assigned to participation. In the third year of the program, Medicare made hospital participation voluntary in half of the MSAs and enabled LEJRs for knees to be performed in the outpatient setting without being subject to episode-based payment. How these changes affected program savings is unclear.

Objective: To estimate savings from the CJR program over time and assess how responses by hospitals to changing incentives were associated with those savings.

Design, Participants, And Setting: This controlled population-based study used Medicare claims data from January 1, 2014, to December 31, 2019, to analyze the spending for beneficiaries who received LEJR in 171 MSAs randomized to CJR vs typical payment. One-quarter of beneficiaries before and after the April 1, 2016, start date were excluded as a 6-month washout period (January 1 to June 30, 2016) to allow time in the evaluation period for hospitals to respond to the program rules.

Main Outcomes And Measures: The main outcomes were episode spending and, starting in year 3 of the program, the hospitals' decision to no longer participate in CJR and perform LEJRs in the outpatient setting.

Results: Data from 1 087 177 patients (mean [SD] age, 74.4 [8.4] years; 692 604 women [63.7%]; 980 635 non-Hispanic White patients [90.2%]) were analyzed. Over the first 4 years of CJR, 321 038 LEJR episodes were performed at 702 CJR hospitals, and 456 792 episodes were performed at 826 control hospitals. From the second to the fourth year of the program, savings in CJR vs control MSAs diminished from -$976 per LEJR episode (95% CI, -$1340 to -$612) to -$331 (95% CI, -$792 to $130). In MSAs where hospital participation was made voluntary in the third year, more hospitals in the highest quartile of baseline spending dropped out compared with the lowest quartile (56 of 60 [93.3%] vs 29 of 56 [51.8%]). In MSAs where participation remained mandatory, CJR hospitals shifted fewer knee replacements to the outpatient setting in years 3 to 4 than controls (12 571 of 59 182 [21.2%] vs 21 650 of 68 722 [31.5%] of knee LEJRs). In these mandatory MSAs, 75% of the reduction in savings per episode from years 1 to 2 to years 3 to 4 of the program ($455; 95% CI, $137-$722) was attributable to CJR hospitals' decision on which patients would undergo surgery or whether the surgical procedure would occur in the outpatient setting.

Conclusions And Relevance: This controlled population-based study found that savings observed in the second year of CJR largely dissipated by the fourth year owing to a combination of responses among hospitals to changes in the program. These results suggest a need for caution regarding the design of new alternative payment models.
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http://dx.doi.org/10.1001/jamainternmed.2021.1897DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8129900PMC
July 2021

Outcomes After Shortened Skilled Nursing Facility Stays Suggest Potential For Improving Postacute Care Efficiency.

Health Aff (Millwood) 2021 05;40(5):745-753

J. Michael McWilliams is the Warren Alpert Foundation Professor of Health Care Policy in the Department of Health Care Policy at Harvard Medical School and a professor of medicine and general internist at Brigham and Women's Hospital, in Boston, Massachusetts.

Reducing postacute care in skilled nursing facilities (SNFs) in favor of home-based care is a leading cost-saving strategy in new payment models. Yet the extent to which SNF stays can be safely shortened remains unclear. We leveraged the exposure of fee-for-service Medicare beneficiaries without supplemental coverage to cost sharing after SNF benefit day 20 as a cause of shortened stays. Marked reductions in length-of-stay because of cost sharing shifted patients to home more than a week earlier than expected without cost sharing, producing a discharge spike. These reductions were not associated with clear evidence of compromised patient safety as measured by death, hospitalization for fall-related injuries, or all-cause hospitalization within nine days of the spike. Adverse consequences requiring hospitalization could not be excluded for a small proportion of shortened stays. These findings suggest potential for improving postacute care efficiency, as SNF stays may be unnecessarily long to ensure safety.
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http://dx.doi.org/10.1377/hlthaff.2020.00649DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8130553PMC
May 2021

Medicaid Coverage 'Cliff' Increases Expenses And Decreases Care For Near-Poor Medicare Beneficiaries.

Health Aff (Millwood) 2021 04;40(4):552-561

Lindsay M. Sabik is an associate professor in the Department of Health Policy and Management, University of Pittsburgh Graduate School of Public Health.

Cost sharing in traditional Medicare can consume a substantial portion of the income of beneficiaries who do not have supplemental insurance from Medicaid, an employer, or a Medigap plan. Near-poor Medicare beneficiaries (with incomes more than 100 percent but less than 200 percent of the federal poverty level) are ineligible for Medicaid but frequently lack alternative supplemental coverage, resulting in a supplemental coverage "cliff" of 25.8 percentage points just above the eligibility threshold for Medicaid (100 percent of poverty). We estimated that beneficiaries affected by this supplemental coverage cliff incurred an additional $2,288 in out-of-pocket spending over the course of two years, used 55 percent fewer outpatient evaluation and management services per year, and filled fewer prescriptions. Lower prescription drug use was partly driven by low take-up of Part D subsidies, which Medicare beneficiaries automatically receive if they have Medicaid. Expanding eligibility for Medicaid supplemental coverage and increasing take-up of Part D subsidies would lessen cost-related barriers to health care among near-poor Medicare beneficiaries.
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http://dx.doi.org/10.1377/hlthaff.2020.02272DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8068502PMC
April 2021

Exploiting Clinical Decision-making Thresholds to Recover Causal Effects From Observational Data: Randomization Without Trials.

JAMA Intern Med 2021 06;181(6):774-775

Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts.

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http://dx.doi.org/10.1001/jamainternmed.2021.0923DOI Listing
June 2021

Impact of the Medicare Shared Savings Program on utilization of mental health and substance use services by eligibility and race/ethnicity.

Health Serv Res 2021 08 5;56(4):581-591. Epub 2021 Feb 5.

Health Equity Research Lab, Department of Psychiatry, Cambridge Health Alliance, Cambridge, Massachusetts, USA.

Objective: To assess the impact of the Medicare Shared Savings Program (MSSP) ACOs on mental health and substance use services utilization and racial/ethnic disparities in care for these conditions.

Data Sources: Five percent random sample of Medicare claims from 2009 to 2016.

Study Design: We compared Medicare beneficiaries in MSSP ACOs to non-MSSP beneficiaries, stratifying analyses by Medicare eligibility (disability vs age 65+). We estimated difference-in-difference models of MSSP ACOs on mental health and substance use visits (outpatient and inpatient), medication fills, and adequate care for depression adjusting for age, sex, race/ethnicity, region, and chronic medical and behavioral health conditions. To examine the differential impact of MSSP on our outcomes by race/ethnicity, we used a difference-in-difference-in-differences (DDD) design.

Data Collection/extraction Methods: Not applicable.

Principal Findings: MSSP ACOs were associated with small reductions in outpatient mental health (Coeff: -0.012, P < .001) and substance use (Coeff: -0.001, P < .01) visits in the disability population, and in adequate care for depression for both the disability- and age-eligible populations (Coeff: -0.028, P < .001; Coeff: -0.012, P < .001, respectively). MSSP ACO's were also associated with increases in psychotropic medications (Coeff: 0.007 and Coeff: 0.0213, for disability- and age-eligible populations, respectively, both P < .001) and reductions in inpatient mental health stays (Coeff:-0.004, P < .001, and Coeff:-0.0002, P < .01 for disability- and age-eligible populations, respectively) and substance use-related stays for disability-eligible populations (Coeff:-0.0005, P<.05). The MSSP effect on disparities varied depending on type of service.

Conclusions: We found small reductions in outpatient and inpatient stays and in rates of adequate care for depression associated with MSSP ACOs. As MSSP ACOs are placed at more financial risk for population-based treatment, it will be important to include more robust behavioral health quality measures in their contracts and to monitor disparities in care.
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http://dx.doi.org/10.1111/1475-6773.13625DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8313953PMC
August 2021

Variation In Emergency Department Admission Rates Among Medicare Patients: Does The Physician Matter?

Health Aff (Millwood) 2021 02;40(2):251-257

Bruce E. Landon is a professor of health care policy in the Department of Health Care Policy at Harvard Medical School and a professor of medicine and practicing internist at Beth Israel Deaconess Medical Center.

Hospitalizations account for the largest share of health care spending. New payment models increasingly encourage health care providers to reduce hospital admissions. Although emergency department (ED) physicians play a major role in the decision to admit a patient, the extent to which admission rates vary among ED physicians even within the same hospital remains poorly understood. In this study we examined physician-level variation in ED admission rates for Medicare patients. We found meaningful variation in admission rates: The mean physician-level adjusted admission rate was 38.9 percent and ranged from 32.2 percent to 45.6 percent for physicians at the tenth and ninetieth percentiles, respectively, of the estimated distribution within the same hospital. In contrast, the predicted risk for admission based on patient characteristics varied little among these physicians, suggesting that the variation in admission rates was not due to differences in patients seen. Our results suggest that strategies targeting physician decision making could modify (by either increasing or decreasing when appropriate) rates of admissions.
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http://dx.doi.org/10.1377/hlthaff.2020.00670DOI Listing
February 2021

Setting Expectations for Clinical Research During the COVID-19 Pandemic.

JAMA Intern Med 2020 10;180(10):1400-1401

Associate Editor, JAMA Internal Medicine.

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http://dx.doi.org/10.1001/jamainternmed.2020.2882DOI Listing
October 2020

Hospital Investments in Housing-Banner of Change or Red Flag?

JAMA Intern Med 2020 09;180(9):1143-1144

Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts.

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http://dx.doi.org/10.1001/jamainternmed.2020.2348DOI Listing
September 2020

Savings or Selection? Initial Spending Reductions in the Medicare Shared Savings Program and Considerations for Reform.

Milbank Q 2020 09 22;98(3):847-907. Epub 2020 Jul 22.

Harvard Medical School.

Policy Points Concerns have been raised about risk selection in the Medicare Shared Savings Program (MSSP). Specifically, turnover in accountable care organization (ACO) physicians and patient panels has led to concerns that ACOs may be earning shared-savings bonuses by selecting lower-risk patients or providers with lower-risk panels. We find no evidence that changes in ACO patient populations explain savings estimates from previous evaluations through 2015. We also find no evidence that ACOs systematically manipulated provider composition or billing to earn bonuses. The modest savings and lack of risk selection in the original MSSP design suggest opportunities to build on early progress. Recent program changes provide ACOs with more opportunity to select providers with lower-risk patients. Understanding the effect of these changes will be important for guiding future payment policy.

Context: The Medicare Shared Savings Program (MSSP) establishes incentives for participating accountable care organizations (ACOs) to lower spending for their attributed fee-for-service Medicare patients. Turnover in ACO physicians and patient panels has raised concerns that ACOs may be earning shared-savings bonuses by selecting lower-risk patients or providers with lower-risk panels.

Methods: We conducted three sets of analyses of Medicare claims data. First, we estimated overall MSSP savings through 2015 using a difference-in-differences approach and methods that eliminated selection bias from ACO program exit or changes in the practices or physicians included in ACO contracts. We then checked for residual risk selection at the patient level. Second, we reestimated savings with methods that address undetected risk selection but could introduce bias from other sources. These included patient fixed effects, baseline or prospective assignment, and area-level MSSP exposure to hold patient populations constant. Third, we tested for changes in provider composition or provider billing that may have contributed to bonuses, even if they were eliminated as sources of bias in the evaluation analyses.

Findings: MSSP participation was associated with modest and increasing annual gross savings in the 2012-2013 entry cohorts of ACOs that reached $139 to $302 per patient by 2015. Savings in the 2014 entry cohort were small and not statistically significant. Robustness checks revealed no evidence of residual risk selection. Alternative methods to address risk selection produced results that were substantively consistent with our primary analysis but varied somewhat and were more sensitive to adjustment for patient characteristics, suggesting the introduction of bias from within-patient changes in time-varying characteristics. We found no evidence of ACO manipulation of provider composition or billing to inflate savings. Finally, larger savings for physician group ACOs were robust to consideration of differential changes in organizational structure among non-ACO providers (eg, from consolidation).

Conclusions: Participation in the original MSSP program was associated with modest savings and not with favorable risk selection. These findings suggest an opportunity to build on early progress. Understanding the effect of new opportunities and incentives for risk selection in the revamped MSSP will be important for guiding future program reforms.
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http://dx.doi.org/10.1111/1468-0009.12468DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7482384PMC
September 2020

Changes in Quality of Care after Hospital Mergers and Acquisitions. Reply.

N Engl J Med 2020 05;382(19):1868

Harvard Medical School, Boston, MA.

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http://dx.doi.org/10.1056/NEJMc2001367DOI Listing
May 2020

Spending variation among ACOs in the Medicare Shared Savings Program.

Am J Manag Care 2020 04;26(4):170-175

Harvard Interfaculty Initiative in Health Policy, 14 Story St, Cambridge, MA 02138. Email:

Objectives: Understanding variation in spending across organizations, rather than across geographic areas, is important because care is delivered by organizations and interventions increasingly focus on organizations. Accountable care organizations (ACOs) are particularly important to study given their incentives to reduce spending. Analyzing spending differences across ACOs may help identify cost savings opportunities.

Study Design: Cross-sectional analysis of Medicare claims.

Methods: We stratified ACOs into quartiles based on the deviation between each ACO's risk-adjusted spending and average risk-adjusted fee-for-service spending in the same market (hospital referral region). We compared spending between top- and bottom-quartile ACOs on each of 7 major service categories and 10 clinical condition groups to identify areas of potential savings. We simulated spending reductions if ACOs with high adjusted spending reduced spending to the levels of lower-spending ACOs.

Results: In 2016, geographically adjusted and risk-adjusted total per-beneficiary spending for the highest-spending quartile of ACOs was 14% higher than for ACOs in the lowest quartile. Variation between high- and low-spending ACOs was greatest, at 27%, in the use of skilled nursing facilities-a service category in which ACOs have reduced spending by the greatest percentage. Inpatient care was the largest driver of absolute dollar differences in spending, however, accounting for 37% of the total spread. If spending in ACOs above median adjusted spending were brought down to the median, savings would be 3% to 4%.

Conclusions: By extending the variations literature to focus on ACOs, we illustrated that meaningful further savings opportunities exist both within and across markets.
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http://dx.doi.org/10.37765/ajmc.2020.42834DOI Listing
April 2020

Getting Incentives Right in Payment Reform: Thinking Beyond Financial Risk.

Ann Intern Med 2020 03 18;172(6):423-424. Epub 2020 Feb 18.

University of Pittsburgh Graduate School of Public Health, Pittsburgh, Pennsylvania (E.T.R.).

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http://dx.doi.org/10.7326/M19-3178DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7422702PMC
March 2020

Physician Organization and the Role of Workforce Turnover.

Ann Intern Med 2020 04 14;172(8):568-570. Epub 2020 Jan 14.

Harvard Medical School, Boston, Massachusetts (M.E.C.).

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http://dx.doi.org/10.7326/M19-2838DOI Listing
April 2020

Medicaid Expansion Slowed Rates Of Health Decline For Low-Income Adults In Southern States.

Health Aff (Millwood) 2020 01;39(1):67-76

J. Michael McWilliams is the Warren Alpert Foundation Professor of Health Care Policy, Department of Health Care Policy, Harvard Medical School.

Of the fourteen states that have not expanded eligibility for Medicaid, nine are in the southern census region, and two others border that region. Ongoing debate over the merits of Medicaid expansion in these states has focused, in part, on whether the safety net provides sufficient access for uninsured low-income Americans. We analyzed longitudinal survey and vital status data from the twelve-state Southern Community Cohort Study (SCCS) for 15,356 nonelderly adult participants with low incomes, 86 percent of whom were enrolled at community health centers. In difference-in-differences analyses, we compared changes in self-reported health between participants in four expansion and eight nonexpansion states before (2008-13) and after (2015-17) Medicaid expansion. We found that a higher proportion of SCCS participants in expansion states reported increases in Medicaid coverage (a differential change of 7.6 percentage points), a lower proportion experienced a health status decline (-1.8 percentage points), and a higher proportion maintained their baseline health status (1.4 percentage points). The magnitude of estimated reductions in health declines would meaningfully affect a nonexpansion state's health ranking in our sample if that state elected to expand Medicaid. Our results suggest that for low-income adults in the South, Medicaid expansion yielded health benefits-even for those with established access to safety-net care.
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http://dx.doi.org/10.1377/hlthaff.2019.00929DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7169046PMC
January 2020

Changes in Quality of Care after Hospital Mergers and Acquisitions.

N Engl J Med 2020 01;382(1):51-59

From the Department of Health Care Policy, Harvard Medical School (N.D.B., B.E.L., J.B.D., J.M.M.), Harvard Business School and the National Bureau of Economic Research (L.S.D.), the Division of General Internal Medicine and Primary Care, Department of Medicine, Beth Israel Deaconess Medical Center (B.E.L.), and the Division of General Internal Medicine, Department of Medicine, Brigham and Women's Hospital (I.K., J.M.M.) - all in Boston.

Background: The hospital industry has consolidated substantially during the past two decades and at an accelerated pace since 2010. Multiple studies have shown that hospital mergers have led to higher prices for commercially insured patients, but research about effects on quality of care is limited.

Methods: Using Medicare claims and Hospital Compare data from 2007 through 2016 on performance on four measures of quality of care (a composite of clinical-process measures, a composite of patient-experience measures, mortality, and the rate of readmission after discharge) and data on hospital mergers and acquisitions occurring from 2009 through 2013, we conducted difference-in-differences analyses comparing changes in the performance of acquired hospitals from the time before acquisition to the time after acquisition with concurrent changes for control hospitals that did not have a change in ownership.

Results: The study sample included 246 acquired hospitals and 1986 control hospitals. Being acquired was associated with a modest differential decline in performance on the patient-experience measure (adjusted differential change, -0.17 SD; 95% confidence interval [CI], -0.26 to -0.07; P = 0.002; the change was analogous to a fall from the 50th to the 41st percentile) and no significant differential change in 30-day readmission rates (-0.10 percentage points; 95% CI, -0.53 to 0.34; P = 0.72) or in 30-day mortality (-0.03 percentage points; 95% CI, -0.20 to 0.14; P = 0.72). Acquired hospitals had a significant differential improvement in performance on the clinical-process measure (0.22 SD; 95% CI, 0.05 to 0.38; P = 0.03), but this could not be attributed conclusively to a change in ownership because differential improvement occurred before acquisition.

Conclusions: Hospital acquisition by another hospital or hospital system was associated with modestly worse patient experiences and no significant changes in readmission or mortality rates. Effects on process measures of quality were inconclusive. (Funded by the Agency for Healthcare Research and Quality.).
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http://dx.doi.org/10.1056/NEJMsa1901383DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7080214PMC
January 2020

Delivery system performance as financial risk varies.

Am J Manag Care 2019 12 1;25(12):e388-e394. Epub 2019 Dec 1.

Harvard University, 180 Longwood Ave, Boston, MA 02115. Email:

Objectives: Banner Health, a large delivery system in Maricopa County, Arizona, entered into both Medicare and commercial insurance contracts that varied the amount of financial risk that Banner assumed. Rates of utilization and spending under these various contracts were investigated.

Study Design: Prior to 2012, Banner held Medicare Advantage (MA) contracts, and in 2012 it began as a Medicare Pioneer accountable care organization (ACO). Banner also introduced a commercial ACO contract in that year. We compared risk-adjusted healthcare utilization and spending in the MA plan, the ACO, and a local traditional Medicare (TM) comparison group. We also compared risk-adjusted utilization and spending in Banner's commercial ACO with that of a comparison group drawn from the same employment groups who were not attributed to Banner providers.

Methods: We used claims and encounter data to measure utilization and spending. We risk adjusted using CMS and HHS Hierarchical Condition Categories.

Results: Within Medicare, MA enrollees had lower risk-adjusted utilization and total spending than either the Pioneer ACO participants or a local TM comparison group. Participation in the Pioneer ACO program was associated with a greater reduction in hospitalization rates for ACO patients relative to local TM patients served by non-ACO providers, but the effect on total medical spending was ambiguous. Risk-adjusted differences between the commercial ACO group and the fee-for-service comparison group were generally small.

Conclusions: The results are consistent with CMS' efforts to shift reimbursement away from pure fee-for-service reimbursement.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7412600PMC
December 2019
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