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Predictive Modeling of 30-Day Emergency Hospital Transport of Patients Using a Personal Emergency Response System: Prognostic Retrospective Study.

Jorn Op den BuijsMariana SimonsSara Bersche GolasNils C FischerJennifer FelstedLinda SchertzerStephen Olusegun AgboolaJoseph C KvedarKamal Jethwani
Published in: JMIR medical informatics (2018)
Patient data collected remotely via PERS can be used to reliably predict 30-day emergency hospital transport. Clinical observations from the EHR showed that predicted high-risk patients had nearly four times higher rates of emergency encounters than did low-risk patients. Health care providers could benefit from our validated predictive model by targeting timely preventive interventions to high-risk patients. This could lead to overall improved patient experience, higher quality of care, and more efficient resource utilization.
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