Are Mobile Gait Sensors a Better Tool at Predicting Elder Falls in the Emergency Department Setting Than the Current Screening Questionnaire?

Huber, James (2021) Are Mobile Gait Sensors a Better Tool at Predicting Elder Falls in the Emergency Department Setting Than the Current Screening Questionnaire? Master's Thesis, University of Pittsburgh. (Unpublished)

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Abstract

Elder falls are becoming an increasing area of concern for rising Medicare expenditures in the United States, especially as Medicare-eligible individuals continue to make up a larger proportion of the total population. One way to reduce these expenditures is to improve our ability to predict future falls in this population, thereby allowing clinicians to provide fall-prevention strategies before an injurious (and costly) fall occurs. While current recommendations for fall prediction strategies in the Emergency Department setting primarily focus on fall risk questionnaires, mobile gait assessments may offer greater predictive potential. This study aimed to compare several different fall assessment strategies to gauge which strategy offers the greatest potential for elder fall risk identification.

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Details

Item Type:	University of Pittsburgh ETD
Status:	Unpublished
Creators/Authors:	Creators Email Pitt Username ORCID Huber, James jah265@pitt.edu jah265
ETD Committee:	Title Member Email Address Pitt Username ORCID Committee Chair Degenholtz, Howard howard.degenholtz@pitt.edu howard.degenholtz Committee Member Albert, Steven smalbert@pitt.edu smalbert Committee Member Frisch, Adam frischan@upmc.edu
Date:	14 May 2021
Date Type:	Publication
Defense Date:	20 April 2021
Approval Date:	14 May 2021
Submission Date:	29 April 2021
Access Restriction:	No restriction; Release the ETD for access worldwide immediately.
Number of Pages:	52
Institution:	University of Pittsburgh
Schools and Programs:	School of Public Health > Health Policy & Management
Degree:	MPH - Master of Public Health
Thesis Type:	Master's Thesis
Refereed:	Yes
Uncontrolled Keywords:	Elder Falls, Emergency Department, Mobile Gait Sensors
Date Deposited:	14 May 2021 18:09
Last Modified:	14 May 2021 18:09
URI:	http://d-scholarship.pitt.edu/id/eprint/41083

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