Development of a comprehensive mobile assessment of pressure (CMAP) system for pressure injury prevention for veterans with spinal cord injury.
Christine M OlneyTamara L Vos-DraperJason EggintonJohn E FergusonGary GoldishByron EddyAndrew H HansenKatherine CarrollMelissa MorrowPublished in: The journal of spinal cord medicine (2019)
Objective: This paper reports the iterative redesign, feasibility and usability of the Comprehensive Mobile Assessment of Pressure (CMAP) system's mobile app used by Veterans with SCI.Design: This three-year, multi-staged study used a mixed-methods approach.Setting: Minneapolis VA Health Care System, Minneapolis, Minnesota.Participants: Veterans with spinal cord injury (N = 18).Interventions: Veterans with spinal cord injury engaged in iterative focus groups and personal interviews, sharing their needs and desires for the CMAP app redesign. App developers used these data for the redesign. The redesigned CMAP app was tested for six-weeks in users' homes.Outcome Measures: Quantitative (surveys) and qualitative (interviews) methods measured feasibility for self-management of seating pressure. Qualitative data were audio recorded, transcribed, anonymized, and coded. Survey data were analyzed using summary statistics.Results: After the CMAP system's redesign, the in-home use interview found: (1) any tool that can assist in prevention and monitoring of skin ulcers is important; (2) the desired key features are present in the app; (3) the main barrier to CMAP use was inconsistent functionality; (4) when functioning as expected, the live pressure map was the central feature, with reminders to weight shift also of high importance. The survey found: power wheelchair users tended to score closer than manual wheelchair users to the positive response end ranges on two separate surveys.Conclusions: Overall both the power and manual wheelchair users reported that they wanted to use the system, felt confident using the system, and that the functions of the system were well integrated.
Keyphrases
- electronic health record
- cross sectional
- big data
- physical activity
- healthcare
- machine learning
- spinal cord injury
- high resolution
- emergency department
- magnetic resonance imaging
- body mass index
- social media
- computed tomography
- clinical trial
- deep learning
- image quality
- soft tissue
- weight gain
- body weight
- gestational age
- double blind