Health resources use and outcomes in patients with asthma.

Abstract

The Behavioral Model of Health Services Use was used as the basis for this cross-sectional examination of the factors associated with health resources use (HRU) and outcomes in patients with asthma. The model as implemented in this research suggests that population characteristics, which are composed of predisposing, enabling, and need measures, predict HRU, which in turn lead to the outcomes of health-related quality of life (HRQOL) and productivity. Study patients were all members of the M-CARE managed care organization (MCO) and were previously diagnosed asthmatics. A one-time survey gathered information on the population characteristics, HRQOL, and productivity. The MCO claims database provided HRU data. Previous general population studies demonstrated that need or disease severity is the most important predictor of HRU. In this study of asthma patients, perceived severity was the most powerful predictor of HRU; it remained significant after controlling for the effects of predisposing and enabling factors, but evaluated severity did not remain significant. As perceived asthma severity increased, HRU increased. In addition to the traditional measures, the effects of moderating variables on the relationship between asthma severity and HRU were examined. No moderating effects were found for proper use of the patient's metered dose inhaler, but compliance and prescribing appropriateness were significant moderators for some HRU measures. Moderating effects were generally stronger for patients with higher asthma-related costs. The best models of HRU were those with significant interactions and explained 15.7% of the variance in asthma-related costs and 29.5% of the variance in number of prescription asthma drugs filled. HRQOL outcomes were measured by the SF-36 and the Asthma Quality of Life Questionnaire, and both quantitative and perceived qualitative productivity were measured. The best outcomes model was developed for the AQLQ and explained almost 67% of the total variance. Increased in HRU usually led to decreased HRQOL and productivity. The most powerful relationships occurred for the physical component summary score of the SF-36 in which three of the HRU measures remained significant after controlling for all other main effects. The relationships between the outcomes measures showed that increased HRQOL led to increased quantitative and qualitative productivity. In conclusion, despite limitations of this cross-sectional study, it points to future research and suggests how an MCO might improve asthma patients health and reduce expenditures. First, better measures of severity are needed and should be incorporated into a longitudinal study design to further elucidate the effects of HRU on HRQOL and productivity. Second, the effects of compliance and prescribing appropriateness on moderating the relationship between severity and HRU need to be further characterized, particularly in patients with high asthma costs who presumably have more severe asthma. This study suggests that identifying (and correcting) inappropriate prescribing may be especially important in reducing asthma-related costs.