In response to the coronavirus disease 2019 (COVID-19) pandemic, Medicare temporarily expanded its coverage of telemedicine to all beneficiaries, included visits in the patient’s home, and began paying for audio-only visits at the same rate as video and in-person visits.^1,2 Previously, Medicare (with a few exceptions) limited telemedicine coverage to video visits for rural beneficiaries and required video visits to take place at a medical facility, such as a physician’s office, rather than at a patient’s home.³

When risk adjustment is inadequate and incentives are weak, pay-for-performance programs, such as the Value-Based Payment Modifier (Value Modifier [VM]) implemented by the Centers for Medicare & Medicaid Services, may contribute to health care disparities without improving performance on average. To estimate the association between VM exposure and performance on quality and spending measures and to assess the effects of adjusting for additional patient characteristics on performance differences between practices serving higher-risk and those serving lower-risk patients. Exploiting the phase-in of the VM on the basis of practice size, regression discontinuity analysis and 2014 Medicare claims were used to estimate differences in practice performance associated with exposure of practices with 100 or more clinicians to full VM incentives (bonuses and penalties) and exposure of practices with 10 or more clinicians to partial incentives (bonuses only). Analyses were repeated with 2015 claims to estimate performance differences associated with a second year of exposure above the threshold of 100 or more clinicians. Performance differences were assessed between practices serving higher- and those serving lower-risk patients after standard Medicare adjustments versus adjustment for additional patient characteristics. Fee-for-service Medicare. Random 20% sample of beneficiaries. Hospitalization for ambulatory care–sensitive conditions, all-cause 30-day readmissions, Medicare spending, and mortality. No statistically significant discontinuities were found at the threshold of 10 or more or 100 or more clinicians in the relationship between practice size and performance on quality or spending measures in either year. Adjustment for additional patient characteristics narrowed performance differences by 9.2% to 67.9% between practices in the highest and those in the lowest quartile of Medicaid patients and Hierarchical Condition Category scores. Observational design and administrative data. The VM was not associated with differences in performance on program measures. Performance differences between practices serving higher- and those serving lower-risk patients were affected considerably by additional adjustments, suggesting a potential for Medicare's pay-for-performance programs to exacerbate health care disparities. The Laura and John Arnold Foundation and National Institute on Aging.

The Multi-Ethnic Study of Atherosclerosis (MESA) showed that the addition of coronary artery calcium (CAC) to traditional risk factors improves risk classification, particularly in intermediate risk asymptomatic patients with LDL cholesterol levels <160 mg/dL. However, the cost-effectiveness of incorporating CAC into treatment decision rules has yet to be clearly delineated. To model the cost-effectiveness of CAC for cardiovascular risk stratification in asymptomatic, intermediate risk patients not taking a statin. Treatment based on CAC was compared to (1) treatment of all intermediate-risk patients, and (2) treatment on the basis of United States guidelines. We developed a Markov model of first coronary heart disease (CHD) and cardiovascular disease (CVD) events. We modeled statin treatment in intermediate risk patients with CAC≥1 and CAC≥100, with different intensities of statins based on the CAC score. We compared these CAC-based treatment strategies to a “treat all” strategy and to treatment according to the Adult Treatment Panel III (ATP III) guidelines. Clinical and economic outcomes were modeled over both five- and ten-year time horizons. Outcomes consisted of CHD and CVD events and Quality-Adjusted Life Years (QALYs). Sensitivity analyses considered the effect of higher event rates, different CAC and statin costs, indirect costs, and re-scanning patients with incidentalomas. We project that it is both cost-saving and more effective to scan intermediate-risk patients for CAC and to treat those with CAC≥1, compared to treatment based on established risk-assessment guidelines. Treating patients with CAC≥100 is also preferred to existing guidelines when we account for statin side effects and the disutility of statin use. Compared to the alternatives we assessed, CAC testing is both effective and cost saving as a risk-stratification tool, particularly if there are adverse effects of long-term statin use. CAC may enable providers to better tailor preventive therapy to patients' risks of CVD.

In attempting to explain why hospitals vary in the quality of care delivered to patients, a considerable body of health policy research points to differences in hospital characteristics such as ownership, safety-net status, and geographic location as the most important contributing factors. This article examines the extent to which a patient's type or lack of insurance may also play a role in determining the quality of care received at any given hospital. We compared within-hospital quality, as measured by risk-adjusted mortality rates, for patients according to their insurance status. We examined the Agency for Healthcare Research and Quality's innovative Inpatient Quality Indicators and pooled 2006-08 State Inpatient Database records from eleven states. We found that privately insured patients had lower risk-adjusted mortality rates than did Medicare enrollees for twelve out of fifteen quality measures examined. To a lesser extent, privately insured patients also had lower risk-adjusted mortality rates than those in other payer groups. Medicare patients appeared particularly vulnerable to receiving inferior care. These findings suggest that to help reduce care disparities, public payers and hospitals should measure care quality for different insurance groups and monitor differences in treatment practices within hospitals.

Importance In several pay-for-performance programs, Medicare ties payments to readmission rates but accounts only for a limited set of patient characteristics—and no measures of social risk—when assessing performance of health care providers (clinicians, practices, hospitals, or other organizations). Debate continues over whether accounting for social risk would mitigate inappropriate penalties or would establish lower standards of care for disadvantaged patients if they are served by lower-quality providers. Objectives To assess changes in hospital performance on readmission rates after adjusting for additional clinical and social patient characteristics by using methods that distinguish the association between patient characteristics and readmission from between-hospital differences in quality. Design, Setting, and Participants Using Medicare claims for admissions in 2013 through 2014 and linked US Census data, we assessed several clinical and social characteristics of patients that are not currently used for risk adjustment in the Hospital Readmission Reduction Program. We compared hospital readmission rates with and without adjustment for these additional characteristics, using only the average within-hospital associations between patient characteristics and readmission as the basis for adjustment, thereby appropriately excluding hospitals’ distinct contributions to readmission from the adjustment. Main Outcomes and Measures All-cause readmission within 30 days of discharge. Results The study sample consisted of 1 169 014 index admissions among 1 003 664 unique Medicare beneficiaries (41.5% men; mean [SD] age, 79.9 [8.3] years) in 2215 hospitals. Compared with adjustment for patient characteristics currently implemented by Medicare, adjustment for the additional characteristics reduced overall variation in hospital readmission rates by 9.6%, changed rates upward or downward by 0.37 to 0.72 percentage points for the 10% of hospitals most affected by the additional adjustments (±30.3% to ±58.9% of the hospital-level standard deviation), and would be expected to reduce penalties (in relative terms) by 52%, 46%, and 41% for hospitals with the largest 1%, 5%, and 10% of penalty reductions, respectively. The additional adjustments reduced the mean difference in readmission rates between hospitals in the top and bottom quintiles of high-risk patients by 0.53 percentage points (95% CI, 0.50-0.55;P < .001), or 54% of the difference estimated with CMS adjustments alone. Both clinical and social characteristics contributed to these reductions, and these reductions were considerably greater for conditions targeted by the Hospital Readmission Reduction Program. Adjustment for social characteristics resulted in greater changes in rates of readmission or death than in rates of readmission alone. Conclusions and Relevance Hospitals serving higher-risk patients may be penalized substantially because of the patients they serve rather than their quality of care. Adjusting solely for within-hospital associations may allow adjustment for additional patient characteristics to mitigate unintended consequences of pay for performance without holding hospitals to different standards because of the patients they serve.

BACKGROUND: Since the passage of the Affordable Care Act, Medicaid enrollment has increased by ∼17 million adults, including many low-income parents. One potentially important, but little studied, consequence of expanding health insurance for parents is its effect on children’s receipt of preventive services. METHODS: By using state Medicaid eligibility thresholds linked to the 2001–2013 Medical Expenditure Panel Surveys, we assessed the relationship between changes in adult Medicaid eligibility and children’s likelihood of receiving annual well-child visits (WCVs). In instrumental variable analyses, we used these changes in Medicaid eligibility to estimate the relationship between parental enrollment in Medicaid and children’s receipt of WCVs. RESULTS: Our analytic sample consisted of 50 622 parent-child dyads in families with incomes <200% of the federal poverty level, surveyed from 2001 to 2013. On average, a 10-point increase in a state’s parental Medicaid eligibility (measured relative to the federal poverty level) was associated with a 0.27 percentage point higher probability that a child received an annual WCV (95% confidence interval: 0.058 to 0.48 percentage points, P = .012). Instrumental variable analyses revealed that parental enrollment in Medicaid was associated with a 29 percentage point higher probability that their child received an annual WCV (95% confidence interval: 11 to 47 percentage points, P = .002). CONCLUSIONS: In our study, we demonstrate that Medicaid expansions targeted at low-income adults are associated with increased receipt of recommended pediatric preventive care for their children. This finding reveals an important spillover effect of parental insurance coverage that should be considered in future policy decisions surrounding adult Medicaid eligibility.