Outpatient physical therapy population has been aging faster than the general population: a total population register-based study

Abstract

Background The Icelandic population is aging like other populations in the world, the life expectancy is high, and the national focus is to help people to age in their own homes. The objectives of this research was to describe 17 years of demographic changes among outpatient physical therapy (OPT) clients and to determine if these changes reflect aging in the total population. Methods Data was obtained from a national registry with information on all OPT clients reimbursed by Icelandic Health Insurance from 1999 to 2015, and general population data from the Statistics Iceland registry covering the same 17 years. Simple counts, proportions, Rate Ratios (RR) and 95 % Confidence Intervals (CI) were used to describe and compare the two time-points (1999 and 2015) in both populations, and regression analyses were used to estimate linear changes for each of these 17 years. Results Comparing the endpoints of the 17-year period, the proportion of older adults within the total OPT clientele increased by 23 % (from 18.3 % to 1999 to 23.5 % in 2015; RR 1.23; 95 %CI 1.19–1.27).) while in the general Icelandic population, the proportion of older adults increased by 15 % (from 11.6 % to 1999 to 13.5 % in 2015; RR 1.15; 95 % CI 1.1–1.21). For each of these 17 years, there was an overall 5 % yearly increase in the rate of older adults from the general older Icelandic population who used an OPT (accounting for population aging), and an overall 3.5 % yearly increase in the proportional contribution of older adults to the total OPT clientele. Adjusting for sex and older age group revealed that this increase in rate and proportion was most pronounced among ≥ 85-year-old men. Conclusions This case of Iceland is an example of how health-related and population-based registers may potentially be used to routinely inform and facilitate optimal planning of future health care services for older adults.

A Tool for Low-Cost, Quantitative Assessment of Shoulder Function Using Machine Learning

“…However, prior to referring patients for either operative or non-operative interventions, patients are first triaged based on their exact MSK pathology, which not only requires an in-person physical exam but also often demands costly and resource-intensive imaging, such as an MRI scan. Unfortunately, the elderly, patients in rural communities, and groups historically underrepresented in medicine face the greatest demographic and socioeconomic barriers 6,7 to seeking in-person care, thus accounting for significant deficits in quality-of-life 8 . These groups are therefore hindered in their ability to rehabilitate from MSK injuries by dual obstacles: (1) the diagnosis of their MSK injury and (2) regular follow-up to track recovery.…”