Greater Spending Associated with Improved Survival for Some Cancers in OCM-Defined Episodes.

BACKGROUND: Previous research finds significant variation in spending and utilization across regions, with little evidence of differences in outcomes. While such findings have been interpreted as evidence that spending can be reduced without compromising patient outcomes, the link between spending variation and outcomes remains a critical question.

OBJECTIVE: To use evidence from geographic variations in spending and an individual-level survival analysis to test whether spending within oncology care episodes is associated with survival, where episodes are defined as in the Center for Medicare and Medicaid Innovation's Oncology Care Model (OCM).

METHODS: In this retrospective cohort analysis, patient data from the Surveillance, Epidemiology and End Results Medicare (SEER-Medicare) database for 2007-2013 were linked to hospital referral regions (HRRs) using ZIP codes. Patients in the SEER program are a part of selected population-based cancer registries throughout the United States whose records are linked to Medicare enrollment and claims data (93% of elderly registry patients were successfully linked to Medicare data). Episodes of cancer care were defined as in the OCM: 6 months following a triggering chemotherapy claim. We analyzed episodes of care for 5 tumor types: advanced breast cancer (BC), non-small cell lung cancer (NSCLC), renal cell carcinoma (RCC), multiple myeloma (MM), and chronic myeloid leukemia (CML). We removed the effects of differentials in Medicare payment rates, which were mostly geographic. Regression analysis was then used to calculate standardized spending levels for each HRR, that is, spending adjusted for differences in patient and episode characteristics. To examine the effect of spending during OCM-defined episodes on individual-level survival, we used Cox regression with patient characteristics and standardized HRR spending per episode as covariates. To address concerns that may arise from multiple comparisons across the 5 tumor types, we used the Benjamini-Hochberg procedure to control the false discovery rate.

RESULTS: Our analysis showed significant differences in standardized spending across HRRs. Compared with spending at the 20th percentile episode, spending at the 80th percentile ranged from 25% higher ($57,392 vs. $45,995 for MM) to 47% higher ($36,920 vs. $24,127 for RCC), indicating practice style variation across regions. The hazard of dying for patients with NSCLC and MM statistically significantly decreased by 7% (HR = 0.93, P = 0.006) and 13% (HR = 0.87, P = 0.019), respectively, for a $10,000 increase in standardized spending (in 2013 U.S. dollars). For the 3 other cancers, spending effects were not statistically significant. After using the Benjamini-Hochberg procedure with a 5% false discovery rate, the effects of increased spending on improved survival for NSCLC and MM remained statistically significant.

CONCLUSIONS: The association we found between spending and survival suggests caution may be warranted for physicians, pharmacists, other health care professionals, and policymakers involved in efforts to reduce across-the-board spending within OCM-defined episodes for at least 2 of the 5 cancers studied.

DISCLOSURES: Funding for this research was provided by Novartis Pharmaceuticals to Precision Health Economics in support of research design, analysis, and technical writing services. The funder provided input on study design and comments on the draft report. Baumgardner, Shahabi, and Linthicum are employees of Precision Health Economics (PHE), a health care consultancy to the insurance and life science industries, including firms that market oncology therapies. Vine was an employee of PHE at the time of this research. Zacker is an employee of and shareholder in Novartis Pharmaceuticals. Lakdawalla is a consultant to PHE and holds equity in its parent company, Precision Medicine Group.