Using Claims-Based Estimates of Post-Operative Visits to Revalue Procedures with 10- and 90-Day Global Periods: Updated Results Using Calendar Year 2019 Data.

Health Care Costs Health Care Payment Approaches Medicare Physicians

Journal

Rand health quarterly
ISSN: 2162-8254
Titre abrégé: Rand Health Q
Pays: United States
ID NLM: 101622976

Informations de publication

Date de publication:
Jun 2022
Historique:
entrez: 15 7 2022
pubmed: 16 7 2022
medline: 16 7 2022
Statut: epublish

Résumé

Medicare payment for many health care procedures covers not only the procedure itself but also most post-operative care over a fixed period of time (the ""global period""). The Centers for Medicare & Medicaid Services (CMS) sets payment rates assuming that a certain number and type of post-operative visits specific to each procedure typically occur. This article describes how CMS might use claims-based data on the number of post-operative visits to adjust valuation for procedures with 10- and 90-day global periods. There are links between the number of bundled post-operative visits and the components of valuation addressed in this study: work, practice expense (PE), and malpractice relative value units (RVUs). There is some ambiguity regarding how a reduction in post-operative visits translates into changes in work RVUs. In contrast, a reduction in post-operative visits has clear implications on physician time and direct PE. Changes in physician work, physician time, and direct PE will, in turn, affect the allocation of pools of PE and malpractice RVUs to individual services. The idiosyncrasies of the resource-based relative value scale system used to determine payment for Medicare services result in some ambiguity about how procedures should be revalued to reflect reductions in post-operative visits. These results may inform further policy development around revaluation for global procedures.

Identifiants

pubmed: 35837532
pmc: PMC9242560

Types de publication

Journal Article

Langues

eng

Pagination

10

Informations de copyright

Copyright © 2022 RAND Corporation.

Auteurs

Classifications MeSH