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Identifying high-cost episodes in lower extremity joint replacement.

A new interesting article has been published in Health Serv Res. 2018 Nov 5. doi: 10.1111/1475-6773.13078. [Epub ahead of print] and titled:

Identifying high-cost episodes in lower extremity joint replacement.

Authors of this article are:

Philpot LM, Swanson KM, Inselman J, Schoellkopf WJ, Naessens JM, Borah BJ, Peterson S, Gladders B, Shah ND, Ebbert JO.

A summary of the article is shown below:

OBJECTIVES: To evaluate the ability of claims-based risk adjustment and incremental components of clinical data to identify 90-day episode costs among lower extremity joint replacement (LEJR) patients according to the Centers for Medicare & Medicaid Services (CMS) Comprehensive Care for Joint Replacement (CJR) program provisions.DATA SOURCES: Medicare fee-for-service (FFS) data for qualifying CJR episodes in the United States, and FFS data linked with clinical data from CJR-qualifying LEJR episodes performed at High Value Healthcare Collaborative (HVHC) and Mayo Clinic in 2013. HVHC and Mayo Clinic populations are subsets of the total FFS population to assess the additive value of additional pieces of clinical data in correctly assigning patients to cost groups.STUDY DESIGN: Multivariable logistic models identified high-cost episodes.DATA COLLECTION/EXTRACTION METHODS: Clinical data from participating health care systems merged with Medicare FFS data.PRINCIPAL FINDINGS: Our three populations consisted of 363 621 patients in the CMS population, 4881 in the HVHC population, and 918 in the Mayo population. When modeling per CJR specifications, we observed low to moderate model performance (CMS C-Stat = 0.714; HVHC C-Stat = 0.628; Mayo C-Stat = 0.587). Adding CMS-HCC categories improved identification of patients in the top 20% of episode costs (CMS C-Stat = 0.758, HVHC C-Stat = 0.692, Mayo C-Stat = 0.677). Clinical variables, particularly functional status in the population for which this was available (Mayo C-Stat = 0.783), improved ability to identify patients within cost groups.CONCLUSIONS: Policy makers could use these findings to improve payment adjustments for bundled LEJR procedures and in consideration of new data elements for reimbursement.© Health Research and Educational Trust.

Check out the article’s website on Pubmed for more information:

This article is a good source of information and a good way to become familiar with topics such as:

health care expenditures;health care reform;medicare;reimbursement


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