Are Health Risks Related to Medical Care Charges in the Short-Term? Challenging Traditional Assumptions

Abstract

PURPOSE: This study examines the association between self-reported health risks and short-term use of medical resources. DESIGN: Cross-sectional study comparing responses from a mailed survey with medical encounter and expenditure data. Bivariate analyses and multivariate linear and logistic regressions controlling for age, gender, and health status were conducted to illustrate the relationship between selected risk factors and resource use. SETTING: A group network model health maintenance organization (HMO) in Minneapolis, Minnesota. SUBJECTS: The study population was comprised of a randomly selected sample of nonsenior adults (18 to 64 years old, n = 3825) and seniors (65 years and older, n = 1955) who were enrolled in an HMO. The response rate was 72%. MEASURES: Five independent variables: smoking, alcohol use, obesity, lack of physical activity, and unhappiness were derived from a questionnaire designed to assess health status and health risks. Outcome measures were medical care charges and use of hospital services. RESULTS: Obesity, physical inactivity, and unhappiness were related to higher charges among seniors. These relationships dissipated to some degree after controlling for age, gender, and health status. Unexpected differences were found for alcohol use among both age groups, with those considered to be "not at risk" accruing higher charges and demonstrating a higher likelihood of using inpatient hospital services than those defined to be at risk. CONCLUSIONS: Bivariate and multivariate regression results demonstrated that traditional risk factors are weak and inconsistent predictors of short-term medical charges. Charging smokers and other high risk individuals a higher annual insurance premium than is offered for those at low risk raises questions about fairness when such risk factors are not necessarily good predictors of short-term resource use. The rationale for insurance cost-shifting should be supported with reliable data connecting risks to charges.