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Predicting Persistently High Primary Care Use

¹ Department of Health Sciences Research, Division of Health Care Policy & Research, Mayo Clinic College of Medicine, Rochester, Minn
² Department of Family Medicine and Community Health, University of Minnesota, Minneapolis, Minn
³ Department of Population Health Sciences, University of Wisconsin, Madison, Wisc
⁴ Department of Health Systems Management, School of Public Health and Tropical Medicine, Tulane University, New Orleans, La

CORRESPONDING AUTHOR: James M. Naessens, MPH, Division of Health Care Policy & Research, Mayo Clinic 200 First Street SW, Rochester, MN 55905, naessens.james{at}mayo.edu

PURPOSE We wanted to identify risk factors for persistently high use of primary care.

METHODS We analyzed outpatient office visits to practitioners in family medicine, general internal medicine, general pediatrics, and obstetrics for 1997–1999 among patients in a small Midwestern city covered by a fee-for-service insurance plan with no co-payments for physician visits and no requirement for referral to specialty care. Logistic regression was used to predict which patients with 10 or more primary care visits in 1997 would repeat high use in 1998 based on demographic and diagnostic categories (adjusted clinical groups [ACGs]). A confirmatory data set (high primary care use in 1998 persistent into 1999) was used to evaluate the model.

RESULTS Two percent of the 54,074 patients had 10 or more primary care visits in 1997, and of these, almost 19% had 10 or more visits in the next year. Among adults, 4 ambulatory diagnosis groups (ADGs) were simultaneously positive predictors of repeated high primary care visits: unstable chronic medical conditions, see and reassure conditions, minor time-limited psychosocial conditions, and minor signs and symptoms. Meanwhile, pregnancy was negatively associated. The area under the receiver operating characteristic (ROC) curve was 0.794 for adults in the developmental data set and 0.752 in the confirmatory data set, indicating a moderately accurate assessment. A satisfactory model was not developed for pediatric patients.

CONCLUSIONS Many persistently high primary care users appear to be overserviced but underserved, with underlying problems not addressed by a medical approach. Some may benefit from psychosocial support, whereas others may be good candidates for disease management interventions.

Key Words: Ambulatory care diagnosis groups • forecasting • primary health care/utilization • clinic visits

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