Automatic population of eMeasurements from EHR systems for inpatient falls | Zendy

Insook Cho | Zendy; Eun-Hee Boo | Zendy; SooYoun Lee | Zendy; Patricia C. Dykes | Zendy

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Automatic population of eMeasurements from EHR systems for inpatient falls

Author(s) -

Insook Cho,

Eun-Hee Boo,

SooYoun Lee,

Patricia C. Dykes

Publication year - 2018

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/ocy018

Subject(s) - identifier , computer science , minimum data set , unique identifier , process (computing) , health care , nursing minimum data set , event (particle physics) , population , data science , medicine , nursing outcomes classification , nursing , nursing research , nursing homes , physics , environmental health , quantum mechanics , economics , programming language , economic growth , operating system , team nursing

Representing nursing data sets in a standard way will help to facilitate sharing relevant information across settings. We aimed to populate nursing process and outcome metrics with electronic health record (EHR) data and then compare the results with event reporting systems.

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