Healthcare utilization and costs among older adult female drivers and former drivers

J Safety Res. 2012 Apr;43(2):141-4. doi: 10.1016/j.jsr.2012.01.001. Epub 2012 Feb 12.

Abstract

Purpose: This study compared the healthcare utilization and costs for specific types of medical services among older adult women who currently drive and those who no longer drive.

Methods: This study included 347 women aged 65 or older who were either former (had stopped driving) or current drivers, randomly sampled from a large U.S. health plan to participate in a telephone survey, and who had automated health records with healthcare utilization and cost data. Bivariate analyses and generalized linear modeling were used to examine associations between driving status and healthcare utilization and costs.

Results: Adjusting for age, income, and marital status, former drivers were more likely than current drivers to use mental health care services (RR=3.37; 95% CI: 1.03, 10.98). Former drivers also tended to use more inpatient (RR=1.85; 95% CI: 0.88, 3.87) and emergency services (RR=1.89; 95% CI: 0.96, 3.70), but results did not reach statistical significance. Total annual healthcare costs in 2005 were almost twice as high for former drivers compared with current drivers ($13,046 vs. $7,054; mean difference=$5,992; 95% CI: -$360, $12,344), although this relationship was not statistically significant (CR=1.61; 95% CI: 0.88, 2.96).

Impact on industry: Former drivers were more than three times as likely as current drivers to use mental health services, and tended to use more emergency and inpatient services. Further research on factors that potentially mediate the relationship between driving status and health service use is warranted.

Publication types

  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Aged
  • Aged, 80 and over
  • Analysis of Variance
  • Automobile Driving / statistics & numerical data*
  • Costs and Cost Analysis
  • Female
  • Health Care Surveys
  • Health Services / economics*
  • Health Services / statistics & numerical data*
  • Humans
  • Linear Models
  • United States / epidemiology