To replicate previous research that found four independent and significant predictors of heel pressure injuries (HPIs) in hospitalized patients using a larger and more diverse patient population.
Researchers conducted a retrospective, case-control study with a main and a validation analysis (N = 1,937). The main analysis had 1,697 patients: 323 patients who had HPIs and 1,374 who did not. The validation analysis had 240 patients: 80 patients who developed HPIs and 160 who did not. Researchers used a series of diagnosis codes to define variables associated with an HPI. Data were extracted from the New York Statewide Planning and Research Cooperative System for January 2014 to June 2015. Study authors conducted a series of forward stepwise logistic regression analyses for both samples to select the variables that were significantly and independently associated with the development of an HPI in a multivariable setting. Researchers generated a receiver operating characteristic curve using the final model to assess the regression model's ability to predict HPI development.
Seven variables were significant and independent predictors associated with HPIs: diabetes mellitus, vascular disease, perfusion issues, impaired nutrition, age, mechanical ventilation, and surgery. The receiver operating characteristic curve demonstrated predictive accuracy of the model.
Beyond a risk assessment scale, providers should consider other factors, such as comorbidities, which can predispose patients to HPI development.