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PURPOSE:To improve care coordination for complex cancers, it is critical to establish a more nuanced understanding of the types of providers involved. As the number of provider types increases, strategies to support cancer care coordination must adapt to a greater variety of information needs, communication styles, and treatment strategies. METHODS:We categorized providers into 11 types, using National Provider Identifier specialties. Using Medicare claims, we counted the number of unique combinations of provider types billed during preoperative, operative, and postdischarge care for colon cancer surgery and assessed how this count varies across hospitals. The study included 70,567 beneficiaries in fee-for-service Medicare A and B for 6 months before and 60 days after an admission for colectomy for colon cancer between 2008 and 2011. RESULTS:We observed 1,554 preoperative provider-type combinations, 975 operative combinations, and 1,571 postdischarge combinations. The three most common combinations in the preoperative phase were general medicine only, other medical specialists only, and general medicine and other medical specialists. In the operative phase, the three most common combinations were primary surgery, anesthesiology, and pathology; general medicine, other medical specialists, radiology, primary surgery, anesthesiology, and pathology; and other medical specialists, radiology, primary surgery, anesthesiology, and pathology. In the postdischarge phase, the three most common combinations were general medicine, general medicine and other medical specialists, and general medicine and oncology. On average, each hospital had 15 preoperative, 11 operative, and 15 postoperative combinations. High-volume, larger, teaching, urban, and noncritical access hospitals had more combinations in all phases. CONCLUSION:Many provider-type combinations are involved in colon cancer surgery care. Substantial variation exists across hospitals types, suggesting that certain hospitals need additional resources and more flexible infrastructure to coordinate care.

OBJECTIVES: To understand hospitals' approaches to spending reduction in commercial episode-based payment programs and inform incentive design. STUDY DESIGN: Qualitative arm of an explanatory sequential mixed-methods study involving semistructured interviews with hospital leaders participating in a statewide quality improvement collaborative with novel episode-based incentive payments introduced by the state's largest commercial payer. METHODS: We recruited 21 leaders from 8 purposively selected, diverse hospitals with both high and low performance. Video teleconference--based interviews followed a standardized protocol and addressed 4 domains: choice of clinical condition for evaluation, strategies for episode spending reduction, best practices for success in earning incentives, and barriers to achievement. Rapid qualitative analysis with purposeful data reduction was employed to generate a matrix of key themes within the study domains. RESULTS: Strategies were similar between high- and low-performing hospitals. When selecting conditions, some hospitals focused on areas of underperformance, aiming for improvement opportunities, whereas others chose conditions already achieving highest efficiency. Many tried to synergize with other ongoing improvement initiatives and clinical areas with established leaders and champions. Key strategies included data-driven improvement, care standardization, and protocol dissemination. Best practices for success included readmission prevention and postacute care spending containment. CONCLUSIONS: The findings highlighted hospitals' most common strategies and approaches, providing several insights into optimal design of commercial episode-based incentives: They must be lucrative enough to earn attention or consistent with larger federal programs; hospitals need opportunities to succeed through both improved performance and sustained excellence; and programs may incur malalignment between hospitals and credentialed physicians. [ABSTRACT FROM AUTHOR]