Literature DB >> 34628256

Completion of electronic nursing documentation of inpatient admission assessment: Insights from Australian metropolitan hospitals.

Danielle Ritz Shala1, Aaron Jones2, Greg Fairbrother3, Duong Thuy Tran4.   

Abstract

INTRODUCTION: Electronic nursing documentation is an essential aspect of inpatient care and multidisciplinary communication. Analysing data in electronic medical record (eMR) systems can assist in understanding clinical workflows, improving care quality, and promoting efficiency in the healthcare system. This study aims to assess timeliness of completion of an electronic nursing admission assessment form and identify patient and facility factors associated with form completion in three metropolitan hospitals.
MATERIALS AND METHODS: Records of 37,512 adult inpatient admissions (November 2018-November 2019) were extracted from the hospitals' eMR system. A dichotomous variable descriptive of completion of the nursing assessment form (Yes/No) was created. Timeliness of form completion was calculated as the interval between date and time of admission and form completion. Univariate and multivariate multilevel logistic regression were used to identify factors associated with form completion.
RESULTS: An admission assessment form was completed for 78.4% (n = 29,421) of inpatient admissions. Of those, 78% (n = 22,953) were completed within the first 24 h of admission, 13.3% (n = 3,910) between 24 and 72 h from admission, and 8.7% (n = 2,558) beyond 72 h from admission. Patient length of hospital stay, admission time, and admitting unit's nursing hours per patient day were associated with form completion. Patient gender, age, and admitting unit type were not associated with form completion. DISCUSSION: Form completion rate was high, though more emphasis needs to be placed on the importance of timely completion to allow for adequate patient care planning. Staff education, qualitative understanding of delayed form completion, and streamlined guidelines on nursing admission and eMR use are recommended.
Copyright © 2021 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Data science; Electronic clinical documentation; Health informatics; Nursing admission; Nursing informatics; eMR data

Mesh:

Year:  2021        PMID: 34628256     DOI: 10.1016/j.ijmedinf.2021.104603

Source DB:  PubMed          Journal:  Int J Med Inform        ISSN: 1386-5056            Impact factor:   4.046


  2 in total

1.  Improving the Quality of Electronic Medical Record Documentation: Development of a Compliance and Quality Program.

Authors:  Rebecca M Jedwab; Michael Franco; Denise Owen; Anna Ingram; Bernice Redley; Naomi Dobroff
Journal:  Appl Clin Inform       Date:  2022-09-07       Impact factor: 2.762

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

Authors:  Danielle Ritz Shala; Aaron Jones; Greg Fairbrother; Jordanna Davis; Alastair MacGregor; Melissa Baysari
Journal:  JAMIA Open       Date:  2022-07-11
  2 in total

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