Patterns of Health-Related Behavior as Predictors of Medical Expenditures
Abstract
Increasing medical expenditures is a major economic challenge for the United States. From 1990 to 2009, total per capita health care expenditures increased 284% and are expected to exceed $12,000 per capita by 2020. Although previous research has tested the impact of a single health behavior on medical expenditures, no empirical studies have examined the link between patterns of health-related behavior and medical expenditures. The current research was grounded in typological methods, complex systems, dynamic systems, and complex adaptive systems theories. The research question assessed the predictive validity of an individual’s probabilistic distance from patterns of health-related behavior at the center of cluster groups identified typologically on medical expenditures while controlling for the predictive effects of an individual’s probabilistic distance from remaining central patterns of health-related behavior, age, and sex. A random sample of 3,955 adults was taken from a 2003 Florida commercial health plan database. Participant probabilistic distance from patterns of health-related behavior was assessed using posterior probabilities derived from discriminant function analysis. Multiple regression analysis was used to analyze the research question and results supported the positive predictive effects of patterns of health-related behavior on medical expenditures as participants emulated the patterns with increasing acuteness. This research supports positive social change by demonstrating the need for policy development to address health behavior pattern contributions to increasing expenditures at national, regional, community, and individual levels. This research expands the predictive effects of single health-related behaviors on medical expenditures to multiple health-related behaviors.
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Increasing medical expenditures is a major economic challenge for the United States. From 1990 to 2009, total per capita health care expenditures increased 284% and are expected to exceed $12,000 per capita by 2020. Although previous research has tested the impact of a single health behavior on medical expenditures, no empirical studies have examined the link between patterns of health-related behavior and medical expenditures. The current research was grounded in typological methods, complex systems, dynamic systems, and complex adaptive systems theories. The research question assessed the predictive validity of an individual’s probabilistic distance from patterns of health-related behavior at the center of cluster groups identified typologically on medical expenditures while controlling for the predictive effects of an individual’s probabilistic distance from remaining central patterns of health-related behavior, age, and sex. A random sample of 3,955 adults was taken from a 2003 Florida commercial health plan database. Participant probabilistic distance from patterns of health-related behavior was assessed using posterior probabilities derived from discriminant function analysis. Multiple regression analysis was used to analyze the research question and results supported the positive predictive effects of patterns of health-related behavior on medical expenditures as participants emulated the patterns with increasing acuteness. This research supports positive social change by demonstrating the need for policy development to address health behavior pattern contributions to increasing expenditures at national, regional, community, and individual levels. This research expands the predictive effects of single health-related behaviors on medical expenditures to multiple health-related behaviors.
Get Full Paper