Adopting an American framework to optimize nursing admission documentation in an Australian health organization.

electronic clinical documentation electronic medical record health informatics nursing admission nursing informatics optimization

Journal

JAMIA open
ISSN: 2574-2531
Titre abrégé: JAMIA Open
Pays: United States
ID NLM: 101730643

Informations de publication

Date de publication:
Oct 2022
Historique:
received: 28 06 2021
revised: 18 05 2022
accepted: 04 07 2022
entrez: 13 7 2022
pubmed: 14 7 2022
medline: 14 7 2022
Statut: epublish

Résumé

Apply and modify the American Essential Clinical Dataset (ECD) approach to optimize the data elements of an electronic nursing admission assessment form in a metropolitan Australian local health district. We used the American ECD approach but made modifications. Our approach included (1) a review of data, (2) a review of current admission practice via consultations with nurses, (3) a review of evidence and policies, (4) workshops with nursing and informatics teams in partnership with the electronic medical record (eMR) vendor, and (5) team debrief sessions to consolidate findings and decide what data elements should be kept, moved, or removed from the admission form. Of 165 data elements in the form, 32% ( Application of a modified ECD approach allowed the team to identify opportunities for significantly reducing and reorganizing data elements in the eMR to enhance the utility, quality, visibility, and value of nursing admission data. We found the modified ECD approach effective for identifying data elements and work processes that were unnecessary and duplicated. Our findings and methodology can inform improvements in nursing clinical practice, information management, and governance in a digital health age.

Identifiants

pubmed: 35821796
doi: 10.1093/jamiaopen/ooac054
pii: ooac054
pmc: PMC9272497
doi:

Types de publication

Journal Article

Langues

eng

Pagination

ooac054

Informations de copyright

© The Author(s) 2022. Published by Oxford University Press on behalf of the American Medical Informatics Association.

Références

J Am Med Inform Assoc. 2020 May 1;27(5):798-807
pubmed: 32159770
Comput Inform Nurs. 2019 May;37(5):260-265
pubmed: 31094915
Health Informatics J. 2010 Mar;16(1):63-72
pubmed: 20413414
Int J Med Inform. 2021 Dec;156:104603
pubmed: 34628256
Appl Clin Inform. 2020 May;11(3):464-473
pubmed: 32643778
BMC Health Serv Res. 2019 Aug 9;19(1):558
pubmed: 31399096
J Clin Nurs. 2018 Feb;27(3-4):e578-e589
pubmed: 28981172
Crit Care Med. 2013 Jun;41(6):1502-10
pubmed: 23528804
Int J Med Inform. 2013 May;82(5):313-24
pubmed: 23254294
AMIA Annu Symp Proc. 2006;:629-33
pubmed: 17238417

Auteurs

Danielle Ritz Shala (DR)

Nursing and Midwifery Services, Sydney Local Health District, Camperdown, NSW, Australia.

Aaron Jones (A)

Nursing and Midwifery Services, Sydney Local Health District, Camperdown, NSW, Australia.

Greg Fairbrother (G)

The University of Sydney Susan Wakil School of Nursing and Midwifery, Faculty of Medicine and Health, Camperdown, NSW, Australia.

Jordanna Davis (J)

Cerner Corporation, North Sydney, NSW, Australia.

Alastair MacGregor (A)

MacGregor and Associates Consulting Group LLC, Lutz, FL, USA.

Melissa Baysari (M)

University of Sydney, Biomedical Informatics and Digital Health, School of Medical Sciences, Charles Perkins Centre, Faculty of Medicine and Health, Camperdown, NSW, Australia.

Classifications MeSH