ACCURACY OF MINIMUM DATA SET FALL ASSESSMENTS IN LONG-TERM CARE RESIDENTS

Laura Graham, Yongmei Li, Chintan Dave, Michelle Odden · 2024

Read ACCURACY OF MINIMUM DATA SET FALL ASSESSMENTS IN LONG-TERM CARE RESIDENTS by Laura Graham, Yongmei Li, Chintan Dave, Michelle Odden (2024) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-11693184.txt.

Description

Laura Graham and co-authors checked in 2024 how well a standard nursing-home assessment counts falls among long-term care residents in the Veterans Health system. Falls matter for safety and research, but the standard form is known to undercount them. The team built a rule-based text search of clinic notes to find falls.

The text method was checked against hand review of two hundred charts and proved highly accurate. Across more than forty-five thousand residents, it found nearly ten times as many falls as the standard form. That form caught only about three in ten of the text-found falls. The authors warn that research built on the form may misclassify fallers.

Catalog record

CREATORLaura Graham, Yongmei Li, Chintan Dave, Michelle Odden
YEAR2024
COLLECTIONPAPERS
FORMATTXT
FILE SIZE2 KB
VERSION1.0
LICENSECC BY 4.0
RIGHTSCC BY
SOURCEEurope PMC

Source: https://europepmc.org/articles/PMC11693184

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