Using passively collected sedentary behavior to predict hospital readmission

Sangwon Bae, Anind K. Dey, Carissa A. Low

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    30 Scopus citations

    Abstract

    Hospital readmissions are a major problem facing health care systems today, costing Medicare alone US$26 billion each year. Being readmitted is associated with significantly shorter survival, and is often preventable. Predictors of readmission are still not well understood, particularly those under the patient's control: behavioral risk factors. Our work evaluates the ability of behavioral risk factors, specifically Fitbit-assessed behavior, to predict readmission for 25 postsurgical cancer inpatients. Our results show that sum of steps, maximum sedentary bouts, frequency, and low breaks in sedentary times during waking hours are strong predictors of readmission. We built two models for predicting readmissions: Steps-only and Behavioral model that adds information about sedentary behaviors. The Behavioral model (88.3%) outperforms the Steps-only model (67.1%), illustrating the value of passively collected information about sedentary behaviors. Indeed, passive monitoring of behavior data, i.e., mobility, after major surgery creates an opportunity for early risk assessment and timely interventions.

    Original languageEnglish
    Title of host publicationUbiComp 2016 - Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing
    Pages616-621
    Number of pages6
    ISBN (Electronic)9781450344616
    DOIs
    StatePublished - 12 Sep 2016
    Event2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp 2016 - Heidelberg, Germany
    Duration: 12 Sep 201616 Sep 2016

    Publication series

    NameUbiComp 2016 - Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing

    Conference

    Conference2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp 2016
    Country/TerritoryGermany
    CityHeidelberg
    Period12/09/1616/09/16

    Keywords

    • Colorectal cancer surgery
    • Healthcare outcomes
    • Physical activity
    • Sedentary behavior
    • Wearable tracker

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