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Can Claims Data Algorithms Identify the Physician of Record?
Eva H DuGoff1, Emily Walden2, Katie Ronk3
1Departments of Population Health Sciences.
Insights
Claims algorithms identify primary care physicians (PCPs) but perform poorly for vulnerable Medicare beneficiaries. Focusing on primary care visits improves accuracy but still struggles with fragmented care patients.
Area of Science:
- Health Services Research
- Health Informatics
- Geriatric Medicine
Background:
- Administrative claims data are commonly used to identify primary care physicians (PCPs).
- The accuracy of these claims-based algorithms in the US Medicare population remains unassessed.
Purpose of the Study:
- To evaluate the agreement between PCPs identified by claims-based algorithms and the PCP of record in electronic health record (EHR) data.
- To assess the validity of claims-based algorithms for identifying PCPs in older adults with diabetes.
Main Methods:
- Utilized EHR and Medicare claims data from 3,658 Medicare fee-for-service beneficiaries aged 65+ with diabetes.
- Employed algorithms based on visit plurality and majority, with tie-breakers including last visit, cost, or time span.
- Analyzed 15,624 patient-years of data.
Main Results:
- Algorithms focusing on primary care visits showed higher agreement (78.0%-85.9%) compared to those using all visits (25.4%-63.3%).
- Lower agreement was observed in nonwhite individuals, Medicaid enrollees, patients with PCP changes, and those with over 10 physician visits.
Conclusions:
- Claims-based algorithms focusing on primary care visits may improve PCP identification accuracy.
- These algorithms exhibit reduced performance in vulnerable populations and individuals with fragmented care.
- Further research is needed to refine algorithms for diverse and complex patient groups.
Background:
Claims-based algorithms based on administrative claims data are frequently used to identify an individual's primary care physician (PCP). The validity of these algorithms in the US Medicare population has not been assessed.
Objective:
To determine the agreement of the PCP identified by claims algorithms with the PCP of record in electronic health record data.
Data:
Electronic health record and Medicare claims data from older adults with diabetes.
Subjects:
Medicare fee-for-service beneficiaries with diabetes (N=3658) ages 65 years and older as of January 1, 2008, and medically housed at a large academic health system.
Measures:
Assignment algorithms based on the plurality and majority of visits and tie breakers determined by either last visit, cost, or time from first to last visit.
Results:
The study sample included 15,624 patient-years from 3658 older adults with diabetes. Agreement was higher for algorithms based on primary care visits (range, 78.0% for majority match without a tie breaker to 85.9% for majority match with the longest time from first to last visit) than for claims to all visits (range, 25.4% for majority match without a tie breaker to 63.3% for majority match with the amount billed tie breaker). Percent agreement was lower for nonwhite individuals, those enrolled in Medicaid, individuals experiencing a PCP change, and those with >10 physician visits.
Conclusions:
Researchers may be more likely to identify a patient's PCP when focusing on primary care visits only; however, these algorithms perform less well among vulnerable populations and those experiencing fragmented care.
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