title: On-admission pressure ulcer prediction using the nursing needs score.
abstract: BACKGROUND
  Pressure ulcers (PUs) are considered a serious problem in nursing care and require preventive measures. Many risk assessment methods are currently being used, but most require the collection of data not available on admission. Although nurses assess the Nursing Needs Score (NNS) on a daily basis in Japanese acute care hospitals, these data are primarily used to standardize the cost of nursing care in the public insurance system for appropriate nurse staffing, and have never been used for PU risk assessment.
  
  
  OBJECTIVE
  The objective of this study was to predict the risk of PU development using only data available on admission, including the on-admission NNS score.
  
  
  METHODS
  Logistic regression was used to generate a prediction model for the risk of developing PUs after admission. A random undersampling procedure was used to overcome the problem of imbalanced data.
  
  
  RESULTS
  A combination of gender, age, surgical duration, and on-admission total NNS score (NNS group B; NNS-B) was the best predictor with an average sensitivity, specificity, and area under receiver operating characteristic curve (AUC) of 69.2% (6920/100), 82.8% (8280/100), and 84.0% (8400/100), respectively. The model with the median AUC achieved 80% (4/5) sensitivity, 81.3% (669/823) specificity, and 84.3% AUC.
  
  
  CONCLUSIONS
  We developed a model for predicting PU development using gender, age, surgical duration, and on-admission total NNS-B score. These results can be used to improve the efficiency of nurses and reduce the number of PU cases by identifying patients who require further examination.
authors: Department of Medical Informatics, Institute of Health Biosciences, The University of Tokushima Graduate School, Tokushima, Japan. yokotamu19@gmail.com.
authors: Yoko
authors: http://orcid.org/0000-0002-9616-7520
authors: Y
authors: Nakamura
authors: A Ammar
authors: http://orcid.org/0000-0003-1747-0431
authors: AA
authors: Ghaibeh
authors: Yoko
authors: http://orcid.org/0000-0002-9985-2953
authors: Y
authors: Setoguchi
authors: Kazue
authors: http://orcid.org/0000-0002-6187-9085
authors: K
authors: Mitani
authors: Yoshiro
authors: http://orcid.org/0000-0002-7445-2857
authors: Y
authors: Abe
authors: Ichiro
authors: http://orcid.org/0000-0002-1553-6305
authors: I
authors: Hashimoto
authors: Hiroki
authors: http://orcid.org/0000-0002-8313-5896
authors: H
authors: Moriguchi
keywords: imbalanced data; logistic regression; nursing needs score; prediction; pressure ulcer