Randomized controlled trials in wound care generalize poorly because they exclude patients with significant comorbid conditions. Research using real-world wound care patients is hindered by lack of validated methods to stratify patients according to severity of underlying illnesses. We developed a comprehensive stratification system for patients with wounds that predicts healing likelihood. Complete medical record data on 50,967 wounds from the United States Wound Registry were assigned a clear outcome (healed, amputated, etc.). Factors known to be associated with healing were evaluated using logistic regression models. Significant variables (p < 0.05) were determined and subsequently tested on a holdout sample of data. A different model predicted healing for each wound type. Some variables predicted significantly in nearly all models: wound size, wound age, number of wounds, evidence of bioburden, tissue type exposed (Wagner grade or stage), being nonambulatory, and requiring hospitalization during the course of care. Variables significant in some models included renal failure, renal transplant, malnutrition, autoimmune disease, and cardiovascular disease. All models validated well when applied to the holdout sample. The "Wound Healing Index" can validly predict likelihood of wound healing among real-world patients and can facilitate comparative effectiveness research to identify patients needing advanced therapeutics.
© 2013 by the Wound Healing Society.