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. 2020 Mar;26(1):474-485.
doi: 10.1177/1460458219832053. Epub 2019 Mar 18.

Patient-specific factors associated with pressure injuries revealed by electronic health record analyses

Affiliations

Patient-specific factors associated with pressure injuries revealed by electronic health record analyses

Megan W Miller et al. Health Informatics J. 2020 Mar.

Abstract

Hospital-acquired pressure injuries (HAPIs) are a major source of unintended patient harm and unnecessary costs. The Braden Scale is widely used for risk assessment, yet it lacks specificity and clinical applications. This study used the electronic health record to examine associations between patient-specific factors and pressure injury. Adult patients (age >18) with 3-day length of stay from April 2011 to December 2016 were included. Pressure injuries were identified by ICD-9/ICD-10 codes. Longitudinal multivariate logistic regression was used to evaluate the association between patient-specific factors and HAPIs. This included 57,227 hospital encounters and 241 HAPIs. We observed 2-3 times increased likelihood of acquiring a pressure injury among patients who were malnourished or who had increased intraoperative time. The Braden subscales of nutrition, mobility, and friction showed significant predictive value. Future work is needed to assess the clinical applicability of this work.

Keywords: clinical decision-making; data mining; electronic health records; evidence-based practice; machine learning.

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Conflict of interest statement

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Figures

Figure 1.
Figure 1.
Braden Scale and subscale values in hospital encounters that results in pressure injuries (hospital-acquired pressure injury (HAPI)) or not (no HAPI). The means and standard deviations (SD) for the mean and minimum values of the Braden Scale and all subscales are listed in the table to the left of the forest plot illustrating the relative risk and 95% confidence intervals of each measure.

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