SPECIAL SYMPOSIUM: Unlocking High-value Rehabilitation: Routine Data, Remarkable Outcomes SS11

Thursday, October 30, 2025

1:15 PM - 2:15 PM

Location: ROOM: Continental Ballroom B DIRECTIONS: Lobby Level: From the Main Elevator Bank, proceed right toward the FedEx Office. At the Fed Ex Office, turn right and proceed past the ACRM Registration Desk and into the Continental Foyer. Continental B Lobby is directly adjacent to the center section of the Continental Ballroom.

Presenter(s)

Adam R. Kinney, PhD

Assistant Professor
University of Colorado Denver, VA Rocky Mountain MIRECC
Richmond, Vermont, United States

Slides Slides
Jennifer E. Stevens-Lapsley, PT, PhD (she/her/hers)

Professor
U. Colorado
Denver, Colorado, United States
Joshua Johnson, DPT, PhD

Assistant Professor
Duke University
Durham, NC, United States

Moderator(s)

Jessica Edelstein, PhD, OTR/L

Research Scientist I, Research Assistant Professor
Shirley Ryan AbilityLab, Northwestern University
Glenview, IL, United States

This Symposium will showcase how routinely collected healthcare data can be transformed into clinical insights that advance patient-centered, evidence-based rehabilitation. As the field confronts rising demands for high-value care—defined by the quintuple aim of enhancing patient and provider experience, improving population health, reducing costs, and achieving health equity—this session highlights the critical role of learning health systems.

Moderated by Jessica Edelstein, the symposium begins with an overview of how learning health systems align science, informatics, culture, and incentives to drive continuous improvement. Three presenters then share innovative tools that exemplify data-driven clinical decision support in action:

Adam Kinney introduces Sleep MAPP, a tool developed for Veterans with traumatic brain injury and sleep disorders. Using VA electronic medical record data, Sleep MAPP identifies patients in need of sleep assessment, administers automated screening, and delivers treatment recommendations aligned with clinical guidelines. Early implementation data reveal promising provider feedback on usability and feasibility.

Jennifer Stevens-Lapsley presents the People-Like-Me (PLM) tool, which harnesses historical recovery data to create personalized rehabilitation projections. Initially applied in total knee arthroplasty care, PLM empowers shared decision-making and individualized treatment planning—providing a scalable framework for high-value care.

Joshua Johnson discusses PT-PENCIL, a clinical decision support tool built to optimize inpatient therapy intensity. By predicting which patients benefit most from daily PT sessions, PT-PENCIL supports triage decisions and promotes timely discharges home. Developed and tested through a stepped-wedge pilot trial, this tool showcases how predictive analytics can guide resource-efficient, patient-focused care.

Together, these examples illustrate the transformative potential of using routine data to inform smarter clinical decisions, personalize care, and achieve system-wide improvements in rehabilitation outcomes. This session is a must-attend for clinicians, administrators, and researchers committed to advancing high-value rehabilitation.
Learning Objectives:
Explain the five key outcomes (patient experience, provider experience, population health, cost reduction, and health equity) that define high-value care in rehabilitation.
Outline how learning health systems integrate science, informatics, incentives, and culture to drive continuous improvement and embed best practices into care delivery.
Demonstrate how routinely collected healthcare data (e.g., diagnostic codes, patient-reported outcomes) can be transformed into actionable insights for patient-centered, evidence-based decision-making.
Critically assess research examples that illustrate the successful transformation of routinely collected data into a form that facilitates clinical decision-making in diverse rehabilitation settings.