Research That Matters (January 17 - 20, 2008)

PURPOSE. The literature suggests the relationship between health and health services use is bi-directional. To date, research has primarily focused on health status as a predictor of service use, largely showing that worsening health status leads to increased service utilization and consequently, greater healthcare costs. Alternately, improved access to health services and thus, higher levels of service use—especially preventive services—leads to improved health outcomes and reduced health expenditures. However, the effects of health service use on health outcomes, has not been extensively examined. Using a longitudinal approach, this study examines the effects of prior health services use on the change over time in self-reported health status and functional health. METHODS. The study used data from four waves of the Americans Changing Lives Study, i.e. W1 (1986), W2 (1989), W3 (1994), and W4 (2006). The analysis sample consisted of adults aged 18 and older (n=2,348). The primary predictor—health services use—was measured as whether the respondent visited a doctor during the past three months in the first two waves (W1&W2), i.e. a “yes” response in neither wave, one of the waves (one-time users), or both waves (two-time users). The health outcomes included self-reported health (SRH) and functional health (FH). Using Mplus 4.0, latent growth curve modeling was used to examine the trajectories for SRH and FH from W2 to W4. Other key factors that influence health outcomes were also tested, including age, gender, race, income, education, smoking, and number of chronic conditions. RESULTS. The latent growth curves predicting trajectories of self-rated health and functional health fit the data well (chi-square=34.35, CFI=0.98, RMSEA=.04) and the linear change of self-rated health (mean slope=-0.59) and functional health (mean slope= -1.37) were both significant. At baseline (i.e. intercept), health services use was negatively associated with both SRH (beta=-0.16 for one-time users and beta=-0.36 for two-time users) and FH (beta=-0.38 for two-time users). While health services use was not a predictor of the change in SRH (i.e. slope), it was positively related to the change in FH (beta=0.39 for two-time users). Health services use may indirectly affect the change in SRH, which was positively correlated with the change in FH (r = 0.84). Other predictors of the change in SRH included age (beta=-0.01) and number of chronic conditions (beta=0.22). Change in FH was affected by chronic conditions (beta=0.124), education (beta=0.03) and income (beta=-0.04). CONCLUSION. Although the trajectories of self-reported health status and functional health are expected to decline over time, results suggest that increasing health services use can have a direct effect on functional health and an indirect effect on self-reported health status (via improved functional health). This study extends the conceptual framework for services research in accounting for not only predictors of use but also the long-term impact on perceived health and functioning. Findings emphasize the need to target preventive services towards populations at risk for chronic conditions and with limited economic resources. Such efforts could improve functioning over the lifespan and potentially reduce healthcare expenditures in the long term.