Using Patient-Reported Outcome Measures (PROMs) to Support Adherence to Falls Prevention Clinic

Project Summary

The goal of this project was to create an approach that utilizes Patient-Reported Outcome Measures (PROMs) data to help improve patients’ adherence to falls prevention recommendations. Better adherence would lead to fewer falls over time, and thus, save health care dollars.

  1. We conducted a qualitative study, designed with patient partners who received care previously from the Falls Prevention Clinic. Our goal was to understand whether individualized PROMs data, such as the“EuroQol 5 domain – 5 level” (EQ-5D-5L) PROM, could be used to facilitate improved adherence to Falls Prevention Clinic recommendations.

    The purpose of improving adherence to evidence based recommendations was to prevent more falls. This study explored Falls Prevention Clinic patient participants’ perspectives on PROMs, and how PROMs might impact their own adherence to multimodal fall prevention recommendations.

  2. We gained valuable feedback from the patient partners on their views of the EQ-5D-5L PROM, as well as their perspectives on our focus group questions. Access a summary of our findings here.

Project Findings

This project revealed key considerations for implementing PROMs in this setting:

  • Communication with the patient’s health care provider is important. It is especially important to provide understandable feedback along with other clinical feedback. This will support patient adherence when using the EQ-5D-5L PROM.

  • Timely feedback on a patient’s health status, assessed using the EQ-5D-5L, is important.

  •  Completing the EQ-5D-5L PROM may increase patients’ self-awareness, through receiving its results. This may also support patient adherence.


  • Tai D, Li E, Liu-Ambrose T, Bansback N, Sadatsafavi M, Davis JC. Patient-Reported Outcome Measures (PROMs) to Support Adherence to Falls Prevention Clinic Recommendations: A Qualitative Study. Patient Prefer Adherence. 2020;14:2105-2121

This project is part of the Health Economics and Simulation Modelling Cluster.


Jennifer Davis, PI
Daria Tai
Teresa Liu-Ambrose
Mohsen Sadatsafavi
Eric Li
Joan Burrows
Pamela Warield
Daphne Harwood
Nellie Villenueva
Nick Bansback

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