Web-Based System to Capture Consistent and Complete Real-world Data of Physical Therapy Interventions Following Total Knee Replacement: Design and Evaluation Study

JMIR Rehabilitation and Assistive Technologies, vol. 9, pp. e37714

Abstract

BACKGROUND: Electronic health records (EHRs) have the potential to facilitate consistent clinical data capture to support excellence in patient care, quality improvement, and knowledge generation. Despite widespread EHR use, the vision to transform health care system and its data to a "learning health care system" generating knowledge from real-world data is limited by the lack of consistent, structured clinical data. OBJECTIVE: The purpose of this paper was to demonstrate the design of a web-based structured clinical intervention data capture system and its evaluation in practice. The use case was ambulatory physical therapy (PT) treatment after total knee replacement (TKR), one of the most common and costly procedures today. METHODS: To identify the PT intervention type and intensity (or dose) used to treat patients with knee arthritis following TKR, an iterative user-centered design process refined an initial list of PT interventions generated during preliminary chart reviews. Input from practicing physical therapists and national and international experts refined and categorized the interventions. Next, a web-based, hierarchical structured system for intervention and intensity documentation was designed and deployed. RESULTS: The PT documentation system was implemented by 114 physical therapists agreeing to record all interventions at patient visits. Data for 161 patients with 2615 PT visits were entered by 83 physical therapists. No technical problems with data entry were reported, and data entry required less than 2 minutes per visit. A total of 42 (2%) interventions could not be categorized and were recorded using free text. CONCLUSIONS: The use of user-centered design principles provides a road map for developing clinically feasible data capture systems that employ structured collection of uniform data for use by multiple practitioners across institutions to complement and augment existing EHRs. Secondarily, these data can be analyzed to define best practices and disseminate knowledge to practice.

Authors 8

1. Patricia D. Franklin corresponding

   Northwestern University

   Affiliation as printed

   Department of Medical Social Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States

2. Carol A. Oatis

   Arcadia University

   Affiliation as printed

   Arcadia University, Glenside, PA, United States

3. Hua Zheng

   University of Massachusetts Chan Medical School

   Affiliation as printed

   Department of Orthopedics and Physical Rehabilitation, University of Massachusetts Medical School, Worcester, MA, United States

4. Marie Deanna Westby

   Vancouver Coastal Health Research Institute · Centre for Aging SMART

   Affiliation as printed

   Centre for Hip Health and Mobility, Vancouver Coastal Health Research Institute, Vancouver, BC, Canada

5. Wilfred F. Peter Aachen Department of Orthopedics, Rehabilitation and Physical Therapy

   Leiden University Medical Center

   Affiliation as printed

   Department of Orthopedics, Rehabilitation, and Physical Therapy, Leiden University Medical Center, Leiden, Netherlands

6. Jeremie Laraque-Two Elk
   Affiliation as printed

   HealthPRO Heritage, Bellevue, WA, United States

7. Ellen Benbow

   Magee Rehabilitation Hospital

   Affiliation as printed

   Magee Rehabilitation Hospital, Philadelphia, PA, United States

8. Wenjun Li

   University of Massachusetts Lowell

   Affiliation as printed

   Department of Public Health, University of Massachusetts-Lowell, Lowell, MA, United States