The current demographic transition will lead to increasing demands on health services. However, debate exists as to the role age plays relative to co-morbidity in terms of health services utilization. While age has been identified as a critical factor in health services utilization, health services utilization is not simply an outcome of ill health, nor is it an inevitable outcome of aging. Most data on health service utilization studies assess utilization at one point in time, and does not examine transitions in health service utilization. We sought to measure health services utilization and to investigate patterns in the transition of levels of utilization and outcomes associated with different levels of utilization.
We conducted a population-based retrospective cohort study of all Ontario residents aged 65+ eligible for public healthcare coverage from January 1998-December 2006. The main outcome measure was total number of utilization events. The total is computed by summing, on a per annum basis, the number of family physician visits, specialist visits, Emergency Department visits, drug claims, lab claims, X-rays, CT scans, MRI scans, and inpatient admissions. Three categories of utilization were created: low, moderate, and high.
There is heterogeneity in health services utilization across the late lifespan. Utilization increased consistently in the 9-year study period. The probability of remaining at the high utilization category when the person was in the high category the previous year was more than 0.70 for both males and females and for all age groups. Overall healthcare utilization increases more rapidly among the high users compared to the low users. There was negligible probability for moving from high to low utilization category. Probability of death increased exponentially as age increased. Older adults in the low utilization category had the lowest probability of death. The number of male nonagenarians increased more rapidly than female nonagenarians.
There are measurable and identifiable differences in the patterns of health services utilization among older adults. This data will permit clinicians and policy makers to tailor interventions appropriate to the risk class of patients.