Identifying high-cost episodes in lower extremity joint replacement

Lindsey M. Philpot, Kristi M. Swanson, Jonathan Inselman, William J. Schoellkopf, James M. Naessens, Bijan J. Borah, Stephanie Peterson, Barbara Gladders, Nilay D. Shah, Jon O. Ebbert

Research output: Contribution to journalArticle

Abstract

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.

Original languageEnglish (US)
Pages (from-to)117-127
Number of pages11
JournalHealth Services Research
Volume54
Issue number1
DOIs
StatePublished - Feb 1 2019

Keywords

  • health care expenditures
  • health care reform
  • medicare
  • reimbursement

ASJC Scopus subject areas

  • Health Policy

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