Interpreting oncology care model data to drive value-based care: A prostate cancer analysis

Ronald D. Ennis, Anish B. Parikh, Mark Sanderson, Mark Liu, Luis Isola

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

PURPOSE The Oncology Care Model (OCM) must be clinically relevant, accurate, and comprehensible to drive value-based care. METHODS We studied OCM data detailing observed and expected expenses for 6-month-long episodes of care for patients with prostate cancer. We constructed seven disease state–treatment dyads into which we grouped each episode on the bases of diagnoses, procedures, and medications in OCM claims data. We used this clinical-administrative stratification model to facilitate a comparative cost analysis, and we evaluated emergency department and hospital utilization and drug therapy as potential drivers of cost. RESULTS We examined 377 episodes of care, pertaining to 210 patients, that took place within our health system from January 2012 to June 2015. Ninety-six percent of episodes were assigned to clinically meaningful dyads. Excessive expenses were seen in metastatic, castration-resistant dyads containing second-line hormone therapy (ratio of observed to expected expenses [O/E], 2.66), chemotherapy (O/E, 2.09), and radium-223/sipuleucel-T (O/E, 3.01). An OCM update correcting for castration-resistant prostate cancer led to small differences in observed expenses (0% to +2%) but large changes in expected expenses (217% to 227% for hormone-sensitive dyads and +136% to +141% for castration-resistant dyads). O/E increased up to 38% for hormone-sensitive dyads and decreased up to 58% for castration-resistant dyads. Emergency department and hospital utilization seems to drive cost for castration-resistant dyads but not for hormone-sensitive dyads. In the revised OCM model, overall O/E for all episodes improved by 22%, from 1.48 to 1.15. CONCLUSION Our experience with OCM highlights the limitations of administrative claims data within this model and illustrates a method of translating these data into clinically meaningful information to improve value.

Original languageEnglish
Pages (from-to)E238-E246
JournalJournal of Oncology Practice
Volume15
Issue number3
DOIs
StatePublished - 1 Mar 2019

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