Sukruth A Shashikumar1, R J Waken1, Alina A Luke1,2, David R Nerenz3, Karen E Joynt Maddox1,4. 1. Cardiovascular Division, Department of Medicine, Washington University School of Medicine in St Louis, St Louis, Missouri. 2. Behavioral, Social, and Health Education Sciences Division, Rollins School of Public Health, Emory University, Atlanta, Georgia. 3. Center for Health Policy and Health Services Research, Henry Ford Health System, Detroit, Michigan. 4. Center for Health Economics and Policy, Institute for Public Health at Washington University in St Louis, St Louis, Missouri.
Abstract
Importance: The Hospital-Acquired Condition Reduction Program (HACRP) is a value-based payment program focused on safety events. Prior studies have found that the program disproportionately penalizes safety-net hospitals, which may perform more poorly because of unmeasured severity of illness rather than lower quality. A similar program, the Hospital Readmissions Reduction Program, stratifies hospitals into 5 peer groups for evaluation based on the proportion of their patients dually enrolled in Medicare and Medicaid, but the effect of stratification on the HACRP is unknown. Objective: To characterize the hospitals penalized by the HACRP and the distribution of financial penalties before and after stratification. Design, Setting, and Participants: This economic evaluation used publicly available data on HACRP performance and penalties merged with hospital characteristics and cost reports. A total of 3102 hospitals participating in the HACRP in fiscal year 2020 (covering data from July 1, 2016, to December 31, 2018) were studied. Exposures: Hospitals were divided into 5 groups based on the proportion of patients dually enrolled, and penalties were assigned to the lowest-performing quartile of hospitals in each group rather than the lowest-performing quartile overall. Main Outcomes and Measures: Penalties in the prestratification vs poststratification schemes. Results: The study identified 3102 hospitals evaluated by the HACRP. Safety-net hospitals received $111 333 384 in penalties before stratification compared with an estimated $79 087 744 after stratification-a savings of $32 245 640. Hospitals less likely to receive penalties after stratification included safety-net hospitals (33.6% penalized before stratification vs 24.8% after stratification, Δ = -8.8 percentage points [pp], P < .001), public hospitals (34.1% vs 30.5%, Δ = -3.6 pp, P = .003), hospitals in the West (26.8% vs 23.2%, Δ = -3.6 pp, P < .001), hospitals in Medicaid expansion states (27.3% vs 25.6%, Δ = -1.7 pp, P = .003), and hospitals caring for the most patients with disabilities (32.2% vs 28.3%, Δ = -3.9 pp, P < .001) and from racial/ethnic minority backgrounds (35.1% vs 31.5%, Δ = -3.6 pp, P < .001). In multivariate analyses, safety-net status and treating patients with highly medically complex conditions were associated with higher odds of moving from penalized to nonpenalized status. Conclusions and Relevance: This economic evaluation suggests that stratification of hospitals would be associated with a narrowing of disparities in penalties and a marked reduction in penalties for safety-net hospitals. Policy makers should consider adopting stratification for the HACRP.
Importance: The Hospital-Acquired Condition Reduction Program (HACRP) is a value-based payment program focused on safety events. Prior studies have found that the program disproportionately penalizes safety-net hospitals, which may perform more poorly because of unmeasured severity of illness rather than lower quality. A similar program, the Hospital Readmissions Reduction Program, stratifies hospitals into 5 peer groups for evaluation based on the proportion of their patients dually enrolled in Medicare and Medicaid, but the effect of stratification on the HACRP is unknown. Objective: To characterize the hospitals penalized by the HACRP and the distribution of financial penalties before and after stratification. Design, Setting, and Participants: This economic evaluation used publicly available data on HACRP performance and penalties merged with hospital characteristics and cost reports. A total of 3102 hospitals participating in the HACRP in fiscal year 2020 (covering data from July 1, 2016, to December 31, 2018) were studied. Exposures: Hospitals were divided into 5 groups based on the proportion of patients dually enrolled, and penalties were assigned to the lowest-performing quartile of hospitals in each group rather than the lowest-performing quartile overall. Main Outcomes and Measures: Penalties in the prestratification vs poststratification schemes. Results: The study identified 3102 hospitals evaluated by the HACRP. Safety-net hospitals received $111 333 384 in penalties before stratification compared with an estimated $79 087 744 after stratification-a savings of $32 245 640. Hospitals less likely to receive penalties after stratification included safety-net hospitals (33.6% penalized before stratification vs 24.8% after stratification, Δ = -8.8 percentage points [pp], P < .001), public hospitals (34.1% vs 30.5%, Δ = -3.6 pp, P = .003), hospitals in the West (26.8% vs 23.2%, Δ = -3.6 pp, P < .001), hospitals in Medicaid expansion states (27.3% vs 25.6%, Δ = -1.7 pp, P = .003), and hospitals caring for the most patients with disabilities (32.2% vs 28.3%, Δ = -3.9 pp, P < .001) and from racial/ethnic minority backgrounds (35.1% vs 31.5%, Δ = -3.6 pp, P < .001). In multivariate analyses, safety-net status and treating patients with highly medically complex conditions were associated with higher odds of moving from penalized to nonpenalized status. Conclusions and Relevance: This economic evaluation suggests that stratification of hospitals would be associated with a narrowing of disparities in penalties and a marked reduction in penalties for safety-net hospitals. Policy makers should consider adopting stratification for the HACRP.
Authors: Anders Chen; Arnab Ghosh; Kendrick B Gwynn; Celeste Newby; Tracey L Henry; Jackson Pearce; Marshall Fleurant; Stacie Schmidt; Jennifer Bracey; Elizabeth A Jacobs Journal: J Gen Intern Med Date: 2022-06-29 Impact factor: 6.473