Abstract
OBJECTIVE: To develop a sound method to identify patient and physician characteristics that influence specialty referrals.
DESIGN: A retrospective cohort analysis of medical claims data from 1996 supplemented with surveys of primary care physicians.
SETTING: A 600-member independent practice association in southeastern Michigan that provided care for 90,000 members of an HMO.
PATIENTS: Five cohorts, each of 2,000 to 6,000 patients with diagnoses that could be referred to cardiologists, ophthalmologists, pulmonologists, orthopedists, or general surgeons.
MAIN RESULTS: The referral rates for the different cohorts ranged from 1% to 7%. The discriminatory ability of the multivariate logistic models (c-statistic) ranged from 0.66 to 0.79. The likelihood of referral was associated with the patient’s diagnoses and medications and with the referring physician’s age, years out of medical school, satisfaction with the specialty being referred to, and the importance of making or confirming a diagnosis.
CONCLUSIONS: Because these methods were not difficult to implement and the results were credible, we believe that other organizations should be able to use them.
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Cowen, M.E., Zodet, M.W. Methods for analyzing referral patterns. J GEN INTERN MED 14, 474–480 (1999). https://doi.org/10.1046/j.1525-1497.1999.06368.x
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DOI: https://doi.org/10.1046/j.1525-1497.1999.06368.x