Affiliations 

  • 1 Department of Trauma and Reconstructive Surgery, Eberhard-Karls-University Tuebingen, BG Unfallklinik, 72076 Tuebingen, Germany
  • 2 Human Motion, Orthopaedics, Sports Medicine and Digital Methods Group, Department Precision Health, Luxembourg Institute of Health, 1445 Luxembourg, Luxembourg
  • 3 Department of Orthopaedic Surgery, Southern California Permanente Medical Group, Downey Medical Center, Kaiser Permanente Downey Medical Centre, Downey, CA 90242, USA
  • 4 Department of Orthopaedic Surgery, University of Ulm, 89081 Ulm, Germany
  • 5 ALTY Orthopaedic Hospital, Kuala Lumpur 50450, Malaysia
  • 6 Department of Orthopaedic Surgery, Division of Adult Orthopaedic Trauma, University of Virginia, Charlottesville, VA 22903, USA
  • 7 AO Research Institute Davos, 7270 Davos, Switzerland
  • 8 Orthopaedic Trauma Institute (OTI), San Francisco General Hospital, University of California, San Francisco, CA 94720, USA
Medicina (Kaunas), 2023 Feb 19;59(2).
PMID: 36837604 DOI: 10.3390/medicina59020403

Abstract

Background and Objectives: Outcome data from wearable devices are increasingly used in both research and clinics. Traditionally, a dedicated device is chosen for a given study or clinical application to collect outcome data as soon as the patient is included in a study or undergoes a procedure. The current study introduces a new measurement strategy, whereby patients' own devices are utilized, allowing for both a pre-injury baseline measure and ability to show achievable results. Materials and Methods: Patients with a pre-existing musculoskeletal injury of the upper and lower extremity were included in this exploratory, proof-of-concept study. They were followed up for a minimum of 6 weeks after injury, and their wearable outcome data (from a smartphone and/or a body-worn sensor) were continuously acquired during this period. A descriptive analysis of the screening characteristics and the observed and achievable outcome patterns was performed. Results: A total of 432 patients was continuously screened for the study, and their screening was analyzed. The highest success rate for successful inclusion was in younger patients. Forty-eight patients were included in the analysis. The most prevalent outcome was step count. Three distinctive activity data patterns were observed: patients recovering, patients with slow or no recovery, and patients needing additional measures to determine treatment outcomes. Conclusions: Measuring outcomes in trauma patients with the Bring Your Own Device (BYOD) strategy is feasible. With this approach, patients were able to provide continuous activity data without any dedicated equipment given to them. The measurement technique is especially suited to particular patient groups. Our study's screening log and inclusion characteristics can help inform future studies wishing to employ the BYOD design.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.