Improving prediction of fall risk among nursing home residents using electronic medical records | Zendy

Allison Marier | Zendy; Lauren E.W. Olsho | Zendy; William Rhodes | Zendy; William D. Spector | Zendy

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Improving prediction of fall risk among nursing home residents using electronic medical records

Author(s) -

Allison Marier,

Lauren E.W. Olsho,

William Rhodes,

William D. Spector

Publication year - 2015

Publication title -

journal of the american medical informatics association

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.614

H-Index - 150

eISSN - 1527-974X

pISSN - 1067-5027

DOI - 10.1093/jamia/ocv061

Subject(s) - nursing homes , medical record , medicine , nursing , electronic health record , gerontology , health care , economics , radiology , economic growth

Falls are physically and financially costly, but may be preventable with targeted intervention. The Minimum Data Set (MDS) is one potential source of information on fall risk factors among nursing home residents, but its limited breadth and relatively infrequent updates may limit its practical utility. Richer, more frequently updated data from electronic medical records (EMRs) may improve ability to identify individuals at highest risk for falls.

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