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Appl Clin Inform 2016; 07(04): 1107-1119
DOI: 10.4338/ACI-2016-07-RA-0119
Research Article
Schattauer GmbH

Metrics for Electronic-Nursing-Record-Based Narratives: cross-sectional analysis

Kidong Kim
1   Department of Obstetrics and Gynecology, Seoul National University Bundang Hospital, Seongnam, Gyeonggi-do, Korea
,
Suyeon Jeong
2   Medical Device Research and Development Center, Seoul National University Bundang Hospital, Seongnam, Gyeonggi-do, Korea
,
Kyogu Lee
3   Graduate School of Convergence Science and Technology, Seoul National University, Seoul, Korea
,
Hyeoun-Ae Park
4   College of Nursing and Systems Biomedical Informatics Research Center, Seoul National University, Seoul, Korea
,
Yul Ha Min
5   College of Nursing, Gachon University, Incheon, Korea
,
Joo Yun Lee
4   College of Nursing and Systems Biomedical Informatics Research Center, Seoul National University, Seoul, Korea
,
Yekyung Kim
3   Graduate School of Convergence Science and Technology, Seoul National University, Seoul, Korea
,
Sooyoung Yoo
6   Office of eHealth Research and Businesses, Seoul National University Bundang Hospital, Seongnam, Gyeonggi-do, Korea
,
Gippeum Doh
2   Medical Device Research and Development Center, Seoul National University Bundang Hospital, Seongnam, Gyeonggi-do, Korea
,
Soyeon Ahn
7   Division of Statistics, Medical Research Collaborating Center, Seoul National University Bundang Hospital, Seongnam, Gyeonggi-do, Korea
› Author Affiliations Funding Financial support for this study was provided by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT and Future Planning (NRF2013R1A1A3012306); no financial relationships with any organizations that might have an interest in the submitted work in the previous three years, no other relationships or activities that could appear to have influenced the submitted work.
Further Information

Publication History

received: 20. 20 July 2016

accepted: 04 October 2016

Publication Date:
18 December 2017 (online)

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Summary

ObjectivesWe aimed to determine the characteristics of quantitative metrics for nursing narratives documented in electronic nursing records and their association with hospital admission traits and diagnoses in a large data set not limited to specific patient events or hypotheses.

MethodsWe collected 135,406,873 electronic, structured coded nursing narratives from 231,494 hospital admissions of patients discharged between 2008 and 2012 at a tertiary teaching institution that routinely uses an electronic health records system. The standardized number of nursing narratives (i.e., the total number of nursing narratives divided by the length of the hospital stay) was suggested to integrate the frequency and quantity of nursing documentation.

ResultsThe standardized number of nursing narratives was higher for patients aged ≥ 70 years (median = 30.2 narratives/day, interquartile range [IQR] = 24.0–39.4 narratives/day), long (≥ 8 days) hospital stays (median = 34.6 narratives/day, IQR = 27.2–43.5 narratives/day), and hospital deaths (median = 59.1 narratives/day, IQR = 47.0–74.8 narratives/day). The standardized number of narratives was higher in “pregnancy, childbirth, and puerperium” (median = 46.5, IQR = 39.0–54.7) and “diseases of the circulatory system” admissions (median = 35.7, IQR = 29.0–43.4).

ConclusionsDiverse hospital admissions can be consistently described with nursing-documentderived metrics for similar hospital admissions and diagnoses. Some areas of hospital admissions may have consistently increasing volumes of nursing documentation across years. Usability of electronic nursing document metrics for evaluating healthcare requires multiple aspects of hospital admissions to be considered.

Citation: Kim K, Jeong S, Lee K, Park H-A, Min YH, Lee JY, Kim Y, Yoo S, Doh G, Ahn S. Metrics for electronicnursing-record-based narratives: cross-sectional analysis.

Keywords

Electronic health records - nursing informatics - nursing records - narrative evaluation - narrative analysis
 

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