The Impact of Nursing Diagnoses on the Length of Stay for Trauma Patients by Hospitalization Type in South Korea

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Publication Details

Journal
International Journal of Nursing Knowledge
Published
2026-09-17
DOI
https://doi.org/10.1177/20473087261486380
Primary Topic
Nursing Diagnosis and Documentation
Type
article
Field-Weighted Citation Impact
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article

The Impact of Nursing Diagnoses on the Length of Stay for Trauma Patients by Hospitalization Type in South Korea

Kyoung Hoon Lim, Hye Jin Park, Eunjoo Lee, Hyun Kyung Woo
International Journal of Nursing Knowledge
Nursing Diagnosis and Documentation
article

The Impact of Nursing Diagnoses on the Length of Stay for Trauma Patients by Hospitalization Type in South Korea

Kyoung Hoon Lim, Hye Jin Park, Eunjoo Lee, Hyun Kyung Woo
article en

Abstract

Purpose As trauma-related hospitalizations increase, the resulting financial burden on patients and national health insurance systems has grown significant. This study aimed to identify the factors most effective at predicting the duration of hospital stay according to hospitalization types (Intensive Care Unit [ICU] vs. General Units) in a trauma center of South Korea. Methods This retrospective study analyzed electronic medical records from 7,455 trauma patients admitted to a tertiary hospital trauma center between 2016 and 2020. Data were analyzed using t-tests, ANOVA, and multiple linear regression analysis. Results The most frequent NANDA-I diagnoses were "risk for falls" in the ICU and "acute/chronic pain" in general units. The average length of stay (LOS) was 26.95 days for ICU patients and 12.89 days for those in general units. For ICU patients, the number of nursing diagnoses (β= .577, p < .001), number of complications (β =.274, p < .001), age (β = −.038, p = .002), and nursing severity (β = .028, p = .037) were significant predictors of LOS. Notably, traditional trauma severity indices (KTAS and ISS) did not significantly predict LOS in the ICU. For general units, predictors included the number of nursing diagnoses (β = .512), complications (β= .227), age (β = −.093), KTAS (β = .061), pressure ulcer risk (β = .055), and nursing severity (β = .044), all at p <.001. Conclusion The number of nursing diagnoses is a more sensitive predictor of LOS in trauma centers than standard severity indices such as KTAS and ISS. It is crucial to emphasize nursing education that enables practitioners to accurately identify health problems and formulate precise nursing diagnoses to improve care quality and effectively manage hospital stays.

International Journal of Nursing Knowledge
Kyungpook National University Hospital (KR), Kyungpook National University (KR), Kyungpook National University Medical Center (KR)
Openalex Percentile: Top 5%
Nursing Diagnosis and Documentation
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