A predictive model for pressure ulcer outcome: the Wound Healing Index.
2015
The purpose of this learning activity is to provide information regarding the creation of a risk-stratification system to predict the likelihood of the healing of body and heel pressure ulcers (PrUs).This continuing education activity is intended for physicians and nurses with an interest in skin and wound care.After participating in this educational activity, the participant should be better able to:1. Explain the need for a PrU risk stratification tool.2. Describe the purpose and methodology of the study.3. Delineate the results of the study and development of the Wound Healing Index.: To create a validated system to predict the healing likelihood of patients with body and heel pressure ulcers (PrUs), incorporating only patient- and wound-specific variables.The US Wound Registry data were examined retrospectively and assigned a clear outcome (healed, amputated, and so on). Significant variables were identified with bivariate analyses. Multivariable logistic regression models were created based on significant factors (P <.05) and tested on a 10% randomly selected hold-out sample.Fifty-six wound clinics in 24 states: A total of 7973 body PrUs and 2350 heel PrUs were eligible for analysis.Not applicable: Healed PrU MAIN RESULTS:: Because of missing data elements, the logistic regression development model included 6640 body PrUs, of which 4300 healed (64.8%), and the 10% validation sample included 709 PrUs, of which 477 healed (67.3%). For heel PrUs, the logistic regression development model included 1909 heel PrUs, of which 1240 healed (65.0%), and the 10% validation sample included 203 PrUs, of which 133 healed (65.5%). Variables significantly predicting healing were PrU size, PrU age, number of concurrent wounds of any etiology, PrU Stage III or IV, evidence of bioburden/infection, patient age, being nonambulatory, having renal transplant, paralysis, malnutrition, and/or patient hospitalization for any reason.Body and heel PrU Wound Healing Indices are comprehensive, user-friendly, and validated predictive models for likelihood of body and heel PrU healing. They can risk-stratify patients in clinical research trials, stratify patient data for quality reporting and benchmarking activities, and identify patients most likely to require advanced therapeutics to achieve healing.
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