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.
The burden of chronic disorders on hospital admissions prompts the need for new modalities of care: A cross-sectional analysis in a tertiary hospital
