Both clinical diagnoses and self-rated measures of mental illness are associated with a variety of outcomes, including physical well-being, health utilization, and expenditure. However, much of current literature primarily utilizes clinically diagnosed data.
This cross-sectional study explores the impact of mental illness and health care expenditure using 2 self-rated measures: self-rated measured of perceived mental health status (SRMH) and Kessler Screening Scale for Psychological Distress (K6).
Data from the 2011 Medical Expenditure Panel Survey Household Component, a nationally representative sample of noninstitutionalized individuals (n = 18,295), were analyzed using bivariate χ2 tests and a 2-part model (logistics regression and generalized linear model regression for the first and second stages, respectively).
Although predictive of any health expenditure, SRMH alone was not highly predictive of the dollar value of that health expenditure conditional on any spending. By comparison, the K6 measure was significantly and positively associated with the probability of any health expenditure as well as the dollar value of that spending. Taken together, both the K6 and SRMH measures suggest a positive relationship between poor mental health and the probability of any health expenditure and total expenditure conditional on any spending, even when adjusting for other confounding factors such as race/ethnicity, sex, age, educational attainment, insurance status, and some regional characteristics.
Our results suggest that psychological distress and SRMH may represent potential pathways linking poor mental health to increased health care expenditure. Further research exploring the nuances of these relationships may aid researchers, practitioners, and policy makers in addressing issues of inflated health care expenditure in populations at risk for poor mental health.
Nguyen, M. T., Chan, W. Y., & Keeler, C. (2015). The Association Between Self-Rated Mental Health Status and Total Health Care Expenditure: A Cross-Sectional Analysis of a Nationally Representative Sample. Medicine, 94(35), e1410. http://doi.org/10.1097/MD.0000000000001410