title: Predictors of health care utilization in the chronically ill: a review of the literature.
abstract: The objective of this paper is to identify predictors of health care utilization in the chronically ill. This paper reviews 53 studies on hospitalizations and physician visits, published between 1966 and 1997 and identified by MEDLINE and ClinPSYCH databases. Studies with both univariate and multivariate analyses were included. On the basis of the Andersen-Newman model of health care utilization, the effects of predisposing, enabling and need variables are examined. Most studies reviewed indicate that predisposing factors such as age, sex, and marital status are not predictors of hospital utilization in the chronically ill. The enabling factors income, insurance and social support have not been shown to affect health care utilization, but characteristics of the hospitals could have an effect. Need factors such as disease severity, symptom severity and complications adversely affected health care utilization in the chronically ill, while disease duration and comorbidity do not have such an effect. Quality of life and perceived health might affect hospital utilization and physician use. Finally, depression and psychological distress proved to be among the strongest predictors of hospitalizations and physician visits. In conclusion, both disease severity and psychological well-being are most important in health care utilization. Intervention programs to support depressed or psychologically distressed patients should be considered. These could both help the patient and reduce health care utilization costs.
authors.affiliation: Academic Medical Center, University of Amsterdam, The Netherlands. a.g.deboer@amc.uva.nl
authors.forename: A G
authors.initials: AG
authors.lastname: de Boer
authors.forename: W
authors.initials: W
authors.lastname: Wijker
authors.forename: H C
authors.initials: HC
authors.lastname: de Haes
mesh_terms: D000367:Age Factors; D002908:Chronic Disease / Q000453:epidemiology*; D003710:Demography; D004198:Disease Susceptibility; D005260:Female; D006296:Health Services / Q000706:statistics & numerical data*; D006761:Hospitals / Q000706:statistics & numerical data; D006801:Humans; D008297:Male; D008962:Models, Theoretical; D010342:Patient Acceptance of Health Care / Q000706:statistics & numerical data*; D010820:Physicians / Q000706:statistics & numerical data; D011788:Quality of Life