|Start Page Number:||112|
|End Page Number:||121|
|Publication Date:||Jul 2017|
|Authors:||Capan Muge, Wu Pan, Campbell Michele, Mascioli Susan, Jackson Eric V|
|Keywords:||computers: information, statistics: regression|
As health‐care organizations transition from paper to electronic documentation systems, capturing the nursing assessment electronically can play a fundamental role in transforming health‐care delivery. Especially in preventive health, electronic capture of nursing assessment, combined with vital sign‐based monitoring, can support early detection of physiological deterioration of patients. While vital sign‐based Early Warning Systems have the potential to detect signals of physiological deterioration, their clinical interpretation and integration into the workflow in hospital‐based care setting remain a challenge. This study presents a clinical early recognition algorithm using electronic health records (EHRs) coupled with an electronic Nurse Screening Assessment (NSA) that targets various health assessment categories and its integration into the nursing workflow. Data was collected retrospectively from a single institution (N=2,405 visits). χ 2 tests showed significant differences between algorithms with and without NSA (P<0.01). This study provides a practical framework for facilitating the meaningful use of EHRs in hospitals.