Literature DB >> 34171662

Identifying nursing documentation patterns associated with patient deterioration and recovery from deterioration in critical and acute care settings.

Kumiko O Schnock1, Min-Jeoung Kang2, Sarah Collins Rossetti3, Jose Garcia4, Graham Lowenthal4, Chris Knaplund5, Frank Chang6, David Albers5, Tom Z Korach2, Li Zhou2, Jeffrey G Klann7, Kenrick Cato8, David W Bates2, Patricia C Dykes2.   

Abstract

OBJECTIVES: Nursing documentation behavior within electronic health records may reflect a nurse's concern about a patient and can be used to predict patient deterioration. Our study objectives were to quantify variations in nursing documentation patterns, confirm those patterns and variations with clinicians, and identify which patterns indicate patient deterioration and recovery from clinical deterioration events in the critical and acute care settings.
METHODS: We collected patient data from electronic health records and conducted a regression analysis to identify different nursing documentation patterns associated with patient outcomes resulting from clinical deterioration events in the intensive care unit (ICU) and acute care unit (ACU). The primary outcome measures were whether patients were discharged alive from the hospital or expired during their hospital encounter. Secondary outcome measures were clinical deterioration events.
RESULTS: In the ICU, the increased documentation of heart rate, body temperature, and withheld medication administrations were significantly associated with inpatient mortality. In the ACU, the documentation of blood pressure, respiratory rate with comments, singular vital signs, and withheld medications were significantly related to inpatient mortality. In contrast, the documentation of heart rate and "as needed" medication administrations were significantly associated with patient survival to discharge in the ACU.
CONCLUSION: We successfully identified and confirmed the clinical relevancy of the nursing documentation patterns indicative of patient deterioration and recovery from clinical deterioration events in both the ICU and ACU.
Copyright © 2021 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Health information technology; Patient safety; Quality improvement

Mesh:

Year:  2021        PMID: 34171662      PMCID: PMC8390439          DOI: 10.1016/j.ijmedinf.2021.104525

Source DB:  PubMed          Journal:  Int J Med Inform        ISSN: 1386-5056            Impact factor:   4.730


  21 in total

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Journal:  QJM       Date:  2001-10

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5.  A clinical deterioration prediction tool for internal medicine patients.

Authors:  Lisa L Kirkland; Michael Malinchoc; Megan O'Byrne; Joanne T Benson; Deanne T Kashiwagi; M Caroline Burton; Prathibha Varkey; Timothy I Morgenthaler
Journal:  Am J Med Qual       Date:  2012-07-19       Impact factor: 1.852

6.  Leveraging Clinical Expertise as a Feature - not an Outcome - of Predictive Models: Evaluation of an Early Warning System Use Case.

Authors:  Sarah Collins Rossetti; Chris Knaplund; Dave Albers; Abdul Tariq; Kui Tang; David Vawdrey; Natalie H Yip; Patricia C Dykes; Jeffrey G Klann; Min Jeoung Kang; Jose Garcia; Li-Heng Fu; Kumiko Schnock; Kenrick Cato
Journal:  AMIA Annu Symp Proc       Date:  2020-03-04

7.  Nurse concern: a predictor of patient deterioration.

Authors:  Gary Kenward; Timothy Hodgetts
Journal:  Nurs Times       Date:  2002 May 28-Jun 3

Review 8.  A new, evidence-based estimate of patient harms associated with hospital care.

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Journal:  J Patient Saf       Date:  2013-09       Impact factor: 2.844

9.  Relationship between nursing documentation and patients' mortality.

Authors:  Sarah A Collins; Kenrick Cato; David Albers; Karen Scott; Peter D Stetson; Suzanne Bakken; David K Vawdrey
Journal:  Am J Crit Care       Date:  2013-07       Impact factor: 2.228

Review 10.  Nurses' worry or concern and early recognition of deteriorating patients on general wards in acute care hospitals: a systematic review.

Authors:  Gooske Douw; Lisette Schoonhoven; Tineke Holwerda; Getty Huisman-de Waal; Arthur R H van Zanten; Theo van Achterberg; Johannes G van der Hoeven
Journal:  Crit Care       Date:  2015-05-20       Impact factor: 9.097

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  1 in total

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  1 in total

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