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Relative Impact of Patient and Clinic Factors on Adherence to Primary Care Preventive Service Guidelines: An Exploratory Study
Scott D. Ramsey, Allen D. Cheadle, William E. Neighbor, Ed Gore, Patricia Temple, Thomas Staiger and Harold I. Goldberg
Vol. 39, No. 9 (Sep., 2001), pp. 979-989
Published by: Lippincott Williams & Wilkins
Stable URL: http://www.jstor.org/stable/3767777
Page Count: 11
You can always find the topics here!Topics: Mammography, Cancer screening, Health insurance, Cholesterols, Medicaid, Modeling, Primary health care, Cigarette smoking, Medicare, Demography
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Background. Preventive care service use is commonly compared across health plans, clinics, or individual providers, yet little is known about the influence of the clinic versus patient factors on utilization of these services. Objectives. To measure the relative influence of the facility (clinic) versus patient factors (demographic, behavioral and functional characteristics) on patients' utilization of mammography, Pap smears, cholesterol screening, and retinal exams for those with diabetes. Research Design. Retrospective analysis, using administrative and patient survey data Subjects. Enrollees in 2 University-based clinics and a county hospital-based clinic serving a predominantly low-income population with limited access to health care. Eligibility for cervical cancer screening, screening mammography, cholesterol screening, or annual retinal exam (diabetes) was defined by age, sex, and diagnosis. Measures. Multivariate models, one using readily available administrative data, and another using detailed health status and behavior data gathered from a clinics-wide survey. Results. Unadjusted screening rates for three of four procedures were significantly and substantially lower at the county hospital based clinic than the two University-based clinics. After adjusting for patient characteristics, utilization of three screening services at the county hospital remained significantly below the University-based clinics (Odds Ratios [95% CI]: mammogram 0.15 [0.06-0.35]; Pap smear 0.32 [0.21-0.50]; cholesterol 0.19 [0.09-0.38]; diabetes retinal exam10.68 [0.93-3.01]). The models with detailed survey data performed only marginally better than the models using only administrative data. Conclusions. Patient characteristics were much less important than the clinic for predicting whether patients received primary care preventive services. Our results suggest that case mix adjustment is unlikely to explain away discrepancies in performance between clinics or provider groups.
Medical Care © 2001 Lippincott Williams & Wilkins