60 Background: Attribution is the term that describes how payers and employers determine which provider is responsible for a member’s care, when prospective patient selection is not available. Several claims-based attribution models exist for primary care. The challenges of attribution become salient in oncology because cancer care is often multidisciplinary—involving medical oncologists, surgeons, and radiation oncologists—rendering it difficult to discern which practice should be held accountable. Given the uniqueness of the population the generic primary care attribution model does not fit well. Methods: The objective of this study was to propose and compare methods that attribute patients to hospitals using administrative databases. The models were defined as pre-specified rules that determine the specific patients, types of health care services, and the duration of care for which providers are responsible. Both National Medicare database and Statewide All Payers Claims Database (2014-2015) were used for the purpose to analyze Medicare and commercial population. Two different methods with 6 and 12-months episodes were compared. Method 1 defined episode trigger as first diagnosis of cancer and Method 2 as first treatment of cancer, both with no prior 12 months of cancer diagnosis. Patients were attributed to a hospital based on plurality of claims (including both outpatient and inpatient) with a minimum threshold of 2 claims from the same hospital. Ties were broken with the most recent visit, if not, the highest cost. Success measure was defined as highest attribution rate vs. lowest feasible unassigned rate. Results: A total of 1.7 million patients were included in the Medicare cohort and 98,005 from All Payers Claims database (APCD). Results suggested for a 6 months episode, Method 1 vs. Method 2 attributed 94% vs. 98% to a hospital. For a 12-months episode, Method 1 vs. Method 2 attributed 96% vs. 98% to a hospital. Similar results were evident from APCD. It was evident attribution of patients were higher towards their first diagnosed hospital. Also, longer the duration of care, better the attribution. The outcome of the study was a tool in tableau. Conclusions: Attribution is not a problem to be solved and left alone; it requires ongoing work, enhancements. This study results in a framework for attribution that can be used as a mechanism to link indicators of patient-level health care quality and spending to specific providers for the purpose of profiling and accountability. Better systems will seek to identify specific care for a condition based on the types of doctors a patient is seeing (chemotherapy), and identify who is delivering most of that care vs. who is delivering different types of care (surgery, radiation, primary care).
Understanding Public Expectations of Healthcare Quality and Safety Regulation in Australia
