Merit-Based Incentive Payment System (MIPS) Participation in Radiation Oncology Practices - A Simple Survey.

PURPOSE: Our purpose was to survey nationwide radiation oncology practices on their participation in, burden of, and satisfaction with the Medicare Access and Children's Health Insurance Program Reauthorization Act of 2015 (MACRA) payment programs. METHODS AND MATERIALS: All radiation oncology practices accredited by a national specialty organization were invited to participate in a voluntary online survey from December 2018 to January 2019. Questions focused on participation in the Merit-based Incentive Payment System (MIPS) in 2017 and 2018, as by the time of this survey, radiation oncology did not yet have a specialty-specific advanced Alternative Payment Model. RESULTS: Of n = 705 solicited practices, n = 199 completed the survey for an overall response rate of 28.2%. Practices varied significantly in their duration of participation in MACRA programs, means of data submission, and reported improvement activities under MIPS. Forty-nine percent of respondents described being either somewhat or extremely dissatisfied with the ease of submitting measures and data in 2018. The estimated cost to the practices of compliance with MACRA was queried in bins; of users able to estimate the cost of compliance for 2018, the median reported bin was $10,001 to $20,000 (range, less than $1000-100,000 or more). CONCLUSIONS: The participation style in MACRA among radiation oncology practices varied substantially in the years 2017 and 2018. The Center for Medicare & Medicaid Services gave no precise estimates on the cost of compliance for MIPS, but estimated a $3019.47 cost of compliance with the mandated Radiation Oncology Alternative Payment Model in the 2020 Final Rule for selected practices. In this survey, respondents commonly reported the cost of compliance with MACRA significantly exceeded this estimate.

Association of Implementing an Incentive Metric in the Oregon Medicaid Program With Effective Contraceptive Use.

Importance: Reducing unintended pregnancy is a national public health priority. Incentive metrics are increasingly used by health systems to improve health outcomes and reduce costs, but limited data exist on the association of incentive metrics with contraceptive use. Objective: To evaluate whether an association exists between implementing an incentive metric and effective contraceptive use within the Oregon Medicaid program. Design, Setting, and Participants: In this state-level, claims-based cohort study, a comparative interrupted time series design was used to evaluate whether the implementation of an effective contraceptive use incentive metric on January 1, 2015, was associated with changes in contraceptive use among Oregon Medicaid adult enrollees when compared with commercially insured women. The participants were adult women at risk of pregnancy (18-50 years of age) living in Oregon from January 1, 2012, through December 31, 2017, and enrolled in Medicaid (532 337 person-years) or in commercial health insurance (1 131 738 person-years). Exposure: Implementation of an effective contraceptive use incentive metric as defined using the 2019 Oregon Health Authority specifications. Main Outcomes and Measures: International Classification of Diseases, Ninth Revision codes; International Statistical Classification of Diseases and Related Health Problems, Tenth Revision codes; and Current Procedural Terminology codes were used to identify contraceptive use. Annual rates of effective contraceptive use were measured through health insurance claims. Results: The final analyses included 532 337 Medicaid person-years and 1 131 738 privately insured person-years. Women enrolled in Medicaid were younger than those with private insurance (47.5% vs 33.2% of women in 2013 younger than 30 years), and approximately 40% of Medicaid enrollees (vs fewer than 10% of women with private insurance) resided in rural locations. Demographic characteristics within each group remained similar before and after the incentive metric was implemented. In the comparative interrupted time series model, relative to the commercially insured comparison group, effective contraceptive use among Medicaid enrollees for all ages combined increased 3.6% (95% CI, 3.1%-4.1%) 1 year after the start of the incentive metric, 7.5% (95% CI, 6.8%-8.2%) at the end of 2 years, and 11.5% (95% CI, 10.5%-12.4%) at the end of 3 years. Prior to the introduction of the incentive, contraceptive use rates among the youngest cohort of Medicaid enrollees (18-24 years of age) were decreasing; following the introduction of the incentive, contraceptive use increased steadily among all enrollees. Among women aged 18 to 24 years, the effective contraceptive use rate increased 16.5 percentage points (95% CI, 14.4-18.6 percentage points) after 3 years. The largest initial increase in contraceptive use was among women enrolled in Medicaid who were 30 to 34 years of age (4.9%; 95% CI, 3.4%-6.3%). Conclusions and Relevance: Implementation of the effective contraceptive use incentive metric was associated with a significant increase in contraceptive use among Medicaid enrollees relative to a commercially insured comparison group. This finding is relevant given national efforts aimed at adopting a similar metric for widespread use.

Is mortality readmissions bias a concern for readmission rates under the Hospital Readmissions Reduction Program?

OBJECTIVE: To determine whether the exclusion of patients who die from adjusted 30-day readmission rates influences readmission rate measures and penalties under the Hospital Readmission Reduction Program (HRRP). DATA SOURCES/STUDY SETTING: 100% Medicare fee-for-service claims over the period July 1, 2012, until June 30, 2015. STUDY DESIGN: We examine the 30-day readmission risk across the three conditions targeted by the HRRP: acute myocardial infarction (AMI), congestive heart failure (CHF), and pneumonia. Using logistic regression, we estimate the readmission risk for three samples of patients: those who survived the 30-day period after their index admission, those who died over the 30-day period, and all patients who were admitted to see how they differ. DATA COLLECTION/EXTRACTION METHODS: We identified and extracted data for Medicare fee-for-service beneficiaries admitted with primary diagnoses of AMI (N = 497 931), CHF (N = 1 047 552), and pneumonia (N = 850 552). RESULTS: The estimated hospital readmission rates for the survived and nonsurvived patients differed by 5%-8%, on average. Incorporating these estimates into overall readmission risk for all admitted patients changes the likely penalty status for 9% of hospitals. However, this change is randomly distributed across hospitals and is not concentrated amongst any one type of hospital. CONCLUSIONS: Not accounting for variations in mortality may result in inappropriate penalties for some hospitals. However, the effect of this bias is low due to low mortality rates amongst incentivized conditions and appears to be randomly distributed across hospital types.

Examining Misaligned Incentives for Payers and Manufacturers in Value-Based Pharmaceutical Contracts.

Value-based pharmaceutical contracts (VBPCs) are performance-based reimbursement agreements between health care payers and pharmaceutical manufacturers in which the price, quantity, or nature of reimbursement is tied to value-based outcomes. As value-based payment models have permeated through much of the health care payment landscape via reimbursement to payers and providers, VBPCs offer opportunities for manufacturers to similarly engage in performance-based models. This article compares 2 VBPC schemes: "pay-for-failure" schemes, in which manufacturers offer rebates or discounts to payers for treatment failure, and "pay-for-success" schemes, in which manufacturers offer rebates or discounts to payers for treatment success. Each method has its own short-term and long-term trade-offs, and both lead to some degree of misaligned incentives between payers and manufacturers. These incentive differences have important downstream effects, influencing patient selection, provision of wraparound services, and nature of reimbursements. This analysis contrasts potential benefits and disadvantages for each of these approaches and offers potential solutions to address misalignment. For example, although pay-for-success models may be more aligned between payers and manufacturers, pay-for-failure contracts can be innovative and effective in controlling costs and/or improving outcomes. To illustrate, VBPCs aimed to reduce costs could incorporate total cost of care reduction as a value-based outcome. The authors encourage payers and manufacturers to consider a blended alternative where pay-for-failure and pay-for-success outcomes could be incorporated as VBPC outcomes. Since little is known about the effect of each scheme on outcomes, further research on VBPCs is necessary to fully understand how differing incentives ultimately affect clinical outcomes and costs. DISCLOSURES: No outside funding supported the writing of this article. Good and Kelly are employed by the UPMC Centers for Value-Based Pharmacy Initiatives and High-Value Health Care, and Parekh was employed by the UPMC Centers for Value-Based Pharmacy Initiatives and High-Value Health Care at the time of this study. The authors have no other disclosures to report.

Trends in the Use of Skilled Nursing Facility and Home Health Care Under the Hospital Readmissions Reduction Program: An Interrupted Time-series Analysis.

BACKGROUND: Medicare's Hospital Readmission Reduction Program (HRRP) penalizes hospitals with elevated 30-day readmission rates for acute myocardial infarction (AMI), heart failure (HF), or pneumonia. To reduce readmissions, hospitals may have increased referrals to skilled nursing facilities (SNFs) and home health care. RESEARCH DESIGN: Outcomes included 30-day postdischarge utilization of SNF and home health care, including any use as well as days of use. Subjects included Medicare fee-for-service beneficiaries aged 65 years and older who were admitted with AMI, HF, or pneumonia to hospitals subject to the HRRP. Using an interrupted time-series analysis, we compared utilization rates observed after the announcement of the HRRP (April 2010 through September 2012) and after the imposition of penalties (October 2012 through September 2014) with projected utilization rates that accounted for pre-HRRP trends (January 2008 through March 2010). Models included patient characteristics and hospital fixed effects. RESULTS: For AMI and HF, utilization of SNF and home health care remained stable overall. For pneumonia, observed utilization of any SNF care increased modestly (1.0%, P<0.001 during anticipation; 2.4%, P<0.001 after penalties) and observed utilization of any home health care services declined modestly (-0.5%, P=0.008 after announcement; -0.7%, P=0.045 after penalties) relative to projections. Beneficiaries with AMI and pneumonia treated at penalized hospitals had higher rates of being in the community 30 days postdischarge. CONCLUSIONS: Hospitals might be shifting to more intensive postacute care to avoid readmissions among seniors with pneumonia. At the same time, penalized hospitals' efforts to prevent readmissions may be keeping higher proportions of their patients in the community.

Association of the New Peer Group-Stratified Method With the Reclassification of Penalty Status in the Hospital Readmission Reduction Program.

Importance: Since the introduction of the Hospital Readmission Reduction Program (HRRP), readmission penalties have been applied disproportionately to institutions that serve low-income populations. To address this concern, the US Centers for Medicare & Medicaid introduced a new, stratified payment adjustment method in fiscal year (FY; October 1 to September 30) 2019. Objective: To determine whether the introduction of a new, stratified payment adjustment method was associated with an alteration in the distribution of penalties among hospitals included in the HRRP. Design, Setting, and Participants: In this retrospective cross-sectional study, US hospitals included in the HRRP for FY 2018 and FY 2019 were identified. Penalty status of participating hospitals for FY 2019 was determined based on nonstratified HRRP methods and the new, stratified payment adjustment method. Hospitals caring for the highest proportion of patients enrolled in both Medicare and Medicaid based on quintile were assigned to the low-socioeconomic status (SES) group. Exposures: Nonstratified and stratified Centers for Medicare & Medicaid payment adjustment methods. Main Outcomes and Measures: Net reclassification of penalties among all hospitals and hospitals in the low-SES group, in states participating in Medicaid expansion, and for 4 targeted medical conditions (acute myocardial infarction, heart failure, chronic obstructive pulmonary disease, and pneumonia). Results: Penalty status by both payment adjustment methods (nonstratified and stratified) was available for 3173 hospitals. For FY 2019, the new, stratified payment method was associated with penalties for 75.04% of hospitals (2381 of 3173), while the old, nonstratified method was associated with penalties for 79.07% (2509 hospitals), resulting in a net down-classification in penalty status for all hospitals by 4.03 percentage points (95% CI, 2.95-5.11; P < .001). For the 634 low-SES hospitals in the sample, the new method was associated with penalties for 77.60% of hospitals (492 of 634), while the old method was associated with penalties for 91.64% (581 hospitals), resulting in a net down-classification in penalty status of 14.04 percentage points (95% CI, 11.18-16.90; P < .001). Among hospitals that were not low SES (quintiles 1-4), the new payment method was associated with a small decrease in penalty status (1928 vs 1889; net down-classification, 1.54 percentage points; 95% CI, 0.38-2.69; P = .01). Among target medical conditions, the greatest reduction in penalties was observed among cardiovascular conditions (net down-classification, 6.18 percentage points; 95% CI, 4.96-7.39; P < .001). Conclusions and Relevance: The new, stratified payment adjustment method for the HRRP was associated with a reduction in penalties across hospitals included in the program; the greatest reductions were observed among hospitals in the low-SES group, lessening but not eliminating the previously unbalanced penalty burden carried by these hospitals. Additional public policy research efforts are needed to achieve equitable payment adjustment models for all hospitals.