Literature DB >> 27901174

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

Kidong Kim, Suyeon Jeong, Kyogu Lee, Hyeoun-Ae Park, Yul Ha Min, Joo Yun Lee, Yekyung Kim, Sooyoung Yoo, Gippeum Doh, Soyeon Ahn1.   

Abstract

OBJECTIVES: We 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.
METHODS: We 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.
RESULTS: The 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).
CONCLUSIONS: Diverse hospital admissions can be consistently described with nursing-document-derived 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.

Entities:  

Keywords:  Electronic health records; narrative analysis; narrative evaluation; nursing informatics; nursing records

Mesh:

Year:  2016        PMID: 27901174      PMCID: PMC5228146          DOI: 10.4338/ACI-2016-07-RA-0119

Source DB:  PubMed          Journal:  Appl Clin Inform        ISSN: 1869-0327            Impact factor:   2.342


  22 in total

Review 1.  Reconsidering the conceptualization of nursing workload: literature review.

Authors:  Roisin Morris; Padraig MacNeela; Anne Scott; Pearl Treacy; Abbey Hyde
Journal:  J Adv Nurs       Date:  2007-03       Impact factor: 3.187

2.  Use of narrative nursing records for nursing research.

Authors:  Hyeoun-Ae Park; Insook Cho; Hee-Jung Ahn
Journal:  NI 2012 (2012)       Date:  2012-06-23

3.  Quantifying clinical narrative redundancy in an electronic health record.

Authors:  Jesse O Wrenn; Daniel M Stein; Suzanne Bakken; Peter D Stetson
Journal:  J Am Med Inform Assoc       Date:  2010 Jan-Feb       Impact factor: 4.497

4.  Development of a 5 year life expectancy index in older adults using predictive mining of electronic health record data.

Authors:  Jason Scott Mathias; Ankit Agrawal; Joe Feinglass; Andrew J Cooper; David William Baker; Alok Choudhary
Journal:  J Am Med Inform Assoc       Date:  2013-03-28       Impact factor: 4.497

5.  The inevitable application of big data to health care.

Authors:  Travis B Murdoch; Allan S Detsky
Journal:  JAMA       Date:  2013-04-03       Impact factor: 56.272

6.  Real-time prediction of mortality, readmission, and length of stay using electronic health record data.

Authors:  Xiongcai Cai; Oscar Perez-Concha; Enrico Coiera; Fernando Martin-Sanchez; Richard Day; David Roffe; Blanca Gallego
Journal:  J Am Med Inform Assoc       Date:  2015-09-15       Impact factor: 4.497

7.  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

8.  Sentiment Measured in Hospital Discharge Notes Is Associated with Readmission and Mortality Risk: An Electronic Health Record Study.

Authors:  Thomas H McCoy; Victor M Castro; Andrew Cagan; Ashlee M Roberson; Isaac S Kohane; Roy H Perlis
Journal:  PLoS One       Date:  2015-08-24       Impact factor: 3.240

9.  Describing the relationship between cat bites and human depression using data from an electronic health record.

Authors:  David A Hanauer; Naren Ramakrishnan; Lisa S Seyfried
Journal:  PLoS One       Date:  2013-08-01       Impact factor: 3.240

10.  Stratification of risk for hospital admissions for injury related to fall: cohort study.

Authors:  Victor M Castro; Thomas H McCoy; Andrew Cagan; Hannah R Rosenfield; Shawn N Murphy; Susanne E Churchill; Isaac S Kohane; Roy H Perlis
Journal:  BMJ       Date:  2014-10-24
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.