Literature DB >> 22784299

Testing a Nursing-Specific Model of Electronic Patient Record documentation with regard to information completeness, comprehensiveness and consistency.

Gunn von Krogh1, Dagfinn Nåden, Olaf Gjerløw Aasland.   

Abstract

AIMS AND
OBJECTIVES: To present the results from the test site application of the documentation model KPO (quality assurance, problem solving and caring) designed to impact the quality of nursing information in electronic patient record (EPR).
BACKGROUND: The KPO model was developed by means of consensus group and clinical testing. Four documentation arenas and eight content categories, nursing terminologies and a decision-support system were designed to impact the completeness, comprehensiveness and consistency of nursing information.
DESIGN: The testing was performed in a pre-test/post-test time series design, three times at a one-year interval.
METHODS: Content analysis of nursing documentation was accomplished through the identification, interpretation and coding of information units. Data from the pre-test and post-test 2 were subjected to statistical analyses. To estimate the differences, paired t-tests were used.
RESULTS: At post-test 2, the information is found to be more complete, comprehensive and consistent than at pre-test.
CONCLUSIONS: The findings indicate that documentation arenas combining work flow and content categories deduced from theories on nursing practice can influence the quality of nursing information. RELEVANCE TO CLINICAL PRACTICE: The KPO model can be used as guide when shifting from paper-based to electronic-based nursing documentation with the aim of obtaining complete, comprehensive and consistent nursing information.
© 2012 Blackwell Publishing Ltd.

Entities:  

Mesh:

Year:  2012        PMID: 22784299     DOI: 10.1111/j.1365-2702.2012.04185.x

Source DB:  PubMed          Journal:  J Clin Nurs        ISSN: 0962-1067            Impact factor:   3.036


  1 in total

1.  Using a Text Mining Approach to Explore the Recording Quality of a Nursing Record System.

Authors:  Hsiu-Mei Chang; Ean-Weng Huang; I-Ching Hou; Hsiu-Yun Liu; Fang-Shan Li; Shwu-Fen Chiou
Journal:  J Nurs Res       Date:  2019-06       Impact factor: 1.682

  1 in total

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