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A Closed-Loop Falls Monitoring and Prevention App for Multiple Sclerosis Clinical Practice: Human-Centered Design of the Multiple Sclerosis Falls InsightTrack.

Valerie J BlockKanishka KoshalJaeleene WijangcoNicolette A MillerNarender SaraKyra HendersonJennifer R PearceArpita GopalSonam D MohanJeffrey Marc GelfandChu-Yueh GuoLauren OommenAlyssa N NylanderJames A RowsonEthan G BrownStephen SandersKatherine P RankinCourtney Rees LylesIda SimRiley M Bove
Published in: JMIR human factors (2024)
To our knowledge, this is the first falls app designed using human-centered design to prioritize behavior change and, while being accessible at home for patients, to deliver actionable data to clinicians at the point of care. MS-FIT streamlines data delivery to clinicians via an electronic health record-embedded window, aligning with the 5 rights approach. Leveraging MS-FIT for data processing and algorithms minimizes clinician load while boosting care quality. Our innovation seamlessly integrates real-world patient-generated data as well as clinical and community-level factors, empowering self-care and addressing the impact of falls in people with MS. Preliminary findings indicate wider relevance, extending to other neurological conditions associated with falls and their consequences.
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