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Potential Winners and Losers: Understanding How the Oncology Care Model May Differentially Affect Hospitals.
- Source :
- JCO Oncology Practice; Aug2021, Vol. 17 Issue 8, p501-e1161, 13p
- Publication Year :
- 2021
-
Abstract
- PURPOSE: With the introduction of the Oncology Care Model and plans for the transition to Oncology Care First, alternative payment models (APMs) are an increasingly important piece of the oncology care landscape. Evidence is mixed on the Oncology Care Model's impact on utilization and costs, but as policymakers consider expansion of similar models, it is critical to understand the characteristics of hospitals that may be differentially affected. METHODS: We used 2007-2016 SEER-Medicare data to identify patients with breast and prostate cancer receiving chemotherapy, endocrine therapy (breast), or androgen deprivation therapy (prostate). For each hospital, we calculated 6-month expected mortality, emergency department (ED) visits, inpatient admissions, and costs, all commonly collected APM outcomes. After calculating observed-to-expected rates for each outcome by hospital, we estimated the association between observed-to-expected rates and characteristics of each hospital to understand hospital characteristics that might be associated with higher- or lower-than-expected rates of each outcome. RESULTS: Hospitals with > 15% rural patients had significantly higher-than-expected mortality (0.31 points higher, P < .001) and ED visit rates (0.10 points higher, P = .029) as well as significantly lower costs (0.06 points lower, P = .004). Hospitals unaffiliated with a medical school also experienced significantly higher-than-expected mortality and ED visits. Hospitals eligible for disproportionate share hospital payment experienced significantly higher ED visits but lower costs. For-profit hospitals experienced higher-than-expected mortality. CONCLUSION: Rural hospitals and those unaffiliated with a medical school may require special consideration as APMs expand in oncology care. Designated cancer centers and larger hospitals may be advantaged. [ABSTRACT FROM AUTHOR]
- Subjects :
- HOSPITALS & economics
MATHEMATICAL models
MULTIPLE regression analysis
MEDICAL care costs
POPULATION geography
HEALTH insurance reimbursement
MEDICAL care use
HOSPITAL mortality
THEORY
HEALTH insurance
DESCRIPTIVE statistics
RESEARCH funding
POLICY sciences
CANCER patient medical care
BREAST tumors
PROSTATE tumors
Subjects
Details
- Language :
- English
- ISSN :
- 26881527
- Volume :
- 17
- Issue :
- 8
- Database :
- Complementary Index
- Journal :
- JCO Oncology Practice
- Publication Type :
- Academic Journal
- Accession number :
- 151844992
- Full Text :
- https://doi.org/10.1200/OP.21.00050