A data driven approach to selecting outcome measures for musculoskeletal injury and disease

Clinicians and scientists working to improve the mobility, function and quality of life of individuals with function limiting lower extremity musculoskeletal disease or injury face the challenge of selecting the correct outcome measures. Hundreds of outcome measures and varied collection methods have been described and used across studies. Previous efforts to address this problem have been beneficial, but disagreements regarding measures and inconsistent implementation persists. This is a persistent barrier when conducting multi-site trials, limits the ability to make comparisons and results in large variability in outcome measures across clinical care sites.

Goal of pilot

The overarching purpose of this line of work is to improve the efficiency and data quality of physical performance outcomes assessment in multi-site clinical trials and clinical care, in individuals with lower limb musculoskeletal injury and disease. This pilot project aims to identify statistical and methodological approaches that can be used to allow objective data-driven selection of lower extremity performance measures to assess mobility and recovery. The end goal is to develop an objective approach for outcome measure selection for large-scale multi-site clinical trials and ultimately for determining healthcare reimbursement a part of a value-based care system.

Project plan

This research team will assemble a team of subject matter experts from multiple sites with NIH Clinical and Translational Science Awards to prepare a NIH grant submission that will leverage the NIH Trial Innovation Network.

Investigators will be supported by staff who will conduct data analysis on large existing data sets and identify and evaluate promising analysis approaches.