JMIR Publications

ABSTRACT

Background:

Falls in older people commonly occur at home. Home adaption modifications (HAM) can be effective in reducing falls, but there is some concern over the validity of findings. Routinely collected data could improve the quality of HAM evaluations and strengthen their evidence base.

Objective:

To review the evidence of the use of routinely collected data in HAM intervention evaluations.

Methods:

We searched the following databases from inception until 31st January 2020: PubMed, Ovid, CINAHL, OpenGrey, CENTRAL, LILACS, and Web of Knowledge. Eligible studies were evaluations of home adaption modifications designed to reduce falls involving participants aged 60 years or over. We included study protocols and full reports. Bias was assessed using the ROBINS-I tool.

Results:

We identified seven eligible studies reported in eight manuscripts. Government organisations provided the majority of data across studies, with healthcare providers and third sector organisations also providing data. Studies used a range of demographic, clinical/health, and administrative data. The purpose of using routinely collected data spanned recruiting/creating a sample, stratification, generating independent variables or covariates, and measuring key study-related outcomes.

Conclusions:

Routine data can be used successfully in many aspects of HAM evaluation, can reduce biases and improve other important design considerations. However, the use of these data in HAM intervention is currently not widespread. There are a number of governance barriers to be overcome to allow these types of linkage and to ensure that the use of routinely collected data in evaluations of HAM interventions is exploited to its full potential.