ArticleHealth services research2021
Improving target price calculations in Medicare bundled payment programs.
Article in Health services research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- Win-Win Pricing of Follow-Up Policies Under Healthcare Warranties for Chronic Diseases: A Mathematical Modeling Approach.Healthcare (Basel, Switzerland) · 2025Article
- Physician Group Practices Accrued Large Bonuses Under Medicare's Bundled Payment Model, 2018-20.Health affairs (Project Hope) · 2024Article
- Article
- Improving target price calculations in Medicare bundled payment programs.Health services research · 2021Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo compare the predictive accuracy of two approaches to target price calculations under Bundled Payments for Care Improvement-Advanced (BPCI-A): the traditional Centers for Medicare and Medicaid Services (CMS) methodology and an empirical Bayes approach designed to mitigate the effects of regression to the mean. DATA SOURCES: Medicare fee-for-service claims for beneficiaries discharged from acute care hospitals between 2010 and 2016. STUDY
designWe used data from a baseline period (discharges between January 1, 2010 and September 30, 2013) to predict spending in a performance period (discharges between October 1, 2015 and June 30, 2016). For 23 clinical episode types in BPCI-A, we compared the average prediction error across hospitals associated with each statistical approach. We also calculated an average across all clinical episode types and explored differences by hospital size. DATA COLLECTION/EXTRACTION
methodsWe used a 20% sample of Medicare claims, excluding hospitals and episode types with small numbers of observations. PRINCIPAL
findingsThe empirical Bayes approach resulted in significantly more accurate episode spending predictions for 19 of 23 clinical episode types. Across all episode types, prediction error averaged $8456 for the CMS approach versus $7521 for the empirical Bayes approach. Greater improvements in accuracy were observed with increasing hospital size.
conclusionsCMS should consider using empirical Bayes methods to calculate target prices for BPCI-A.
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