PREDICTIVE MODELING OF PRESSURE INJURY RISK IN PATIENTS ADMITTED TO AN INTENSIVE CARE UNIT
Por:
Ladios-Martin M, Fernández-de-Maya J, Ballesta-López FJ, Belso-Garzas A, Mas-Asencio M and Cabañero-Martínez MJ
Publicada:
1 jul 2020
Resumen:
Background Pressure injuries are an important problem in hospital care. Detecting the population at risk for pressure injuries is the first step in any preventive strategy. Available tools such as the Norton and Braden scales do not take into account all of the relevant risk factors. Data mining and machine learning techniques have the potential to overcome this limitation.
Objectives To build a model to detect pressure injury risk in intensive care unit patients and to put the model into production in a real environment.
Methods The sample comprised adult patients admitted to an intensive care unit (N = 6694) at University Hospital of Torrevieja and University Hospital of Vinalopo. A retrospective design was used to train (n = 2508) and test (n = 1769) the model and then a prospective design was used to test the model in a real environment (n = 2417). Data mining was used to extract variables from electronic medical records and a predictive model was built with machine learning techniques. The sensitivity, specificity, area under the curve, and accuracy of the model were evaluated.
Results The final model used logistic regression and incorporated 23 variables.The model had sensitivity of 0.90, specificity of 0.74, and area under the curve of 0.89 during the initial test, and thus it outperformed the Norton scale.The model performed well 1 year later in a real environment.
Conclusions The model effectively predicts risk of pressure injury. This allows nurses to focus on patients at high risk for pressure injury without increasing workload.
Filiaciones:
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About the Authors: Mireia Ladios-Martin is head of quality, Ribera Salud, Valencia, Spain
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José Fernández-de-Maya is a patient safety officer, University Hospital of Vinalopó, Alicante, Spain, and University Hospital of Torrevieja, Alicante, Spain
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Francisco-Javier Ballesta-López is coordinator of the Population Health Management Unit, University Hospital of Vinalopó and University Hospital of Torrevieja
Belso-Garzas A:
Adrián Belso-Garzas is a data science lead and Manuel Mas-Asencio is a data analytics manager, Futurs, Alicante, Spain
Mas-Asencio M:
Adrián Belso-Garzas is a data science lead and Manuel Mas-Asencio is a data analytics manager, Futurs, Alicante, Spain
Cabañero-Martínez MJ:
María José Cabañero-Martínez is an associate professor, Nursing Department, University of Alicante, Spain
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