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Patient attribution: why the method matters
Rozalina G McCoy1, Kari S Bunkers, Priya Ramar
1Division of Health Care Policy & Research, Mayo Clinic, 200 First St SW, Rochester, MN 55905.
The American Journal of Managed Care
|December 27, 2018
Summary
Patient attribution methods significantly impact healthcare cost and utilization metrics, but not quality measures. Standardizing these methods is crucial for accurate healthcare evaluation and improvement.
Area of Science:
- Healthcare Management
- Health Services Research
- Medical Informatics
Background:
- Accurate patient attribution is essential for evaluating healthcare performance.
- Existing patient attribution methods vary, potentially leading to inconsistent performance metrics.
- Integrated healthcare delivery systems face challenges in assigning patients to primary care providers (PCPs).
Purpose of the Study:
- To compare the impact of five common patient attribution methods on healthcare cost, quality, and utilization.
- To assess the concordance of attribution methods with primary care provider (PCP) empanelment.
- To identify variations in patient attribution within an integrated healthcare delivery system.
Main Methods:
- Retrospective analysis of administrative data from Mayo Clinic Rochester (MCR) for 2010-2011.
- Application of five distinct patient attribution methodologies.
- Comparison of attributed patients based on PCP empanelment, quality metrics, utilization, and costs.
Main Results:
- Five attribution methods assigned between 42% and 72% of patients to a PCP.
- Significant variations in healthcare utilization and total costs were observed across different attribution methods.
- Quality measures showed no significant differences based on attribution method.
- Patients with higher primary care visit frequency were more likely to be attributed by all methods.
Conclusions:
- Patient attribution methods influence the measurement of healthcare costs and utilization.
- Quality metrics were less affected by the choice of attribution method.
- Standardization and optimization of patient attribution methods are necessary for reliable healthcare system evaluation and value assessment.
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