Development of a model to predict closure of chronic wounds in Germany: Claims data analysis.

Patients with chronic leg ulcer, pressure ulcer, or diabetic foot ulcer suffer from significant disease burden. With a view to improving healthcare provision sustainably, a predictive model of time to closure (time-to-event analysis) based on claims data was developed. To identify potential predictors of wound closure, clinical information absent from statutory health insurance (SHI) data was modelled. In patients with leg ulcers, age of the patient (hazard ratios [HR] 0.99), increasing number of comorbidities (HR 0.94), inpatient stays (HR 0.74), and treatment by a specialised wound care professional (HR 1.18) were significant predictors of time to closure (adjusted model). In almost all models, the number of inpatient stays and of comorbidities predicted a lower probability of healing. In addition, the age and the sex of the patient were found to be significant predictors in some models (leg ulcer: HR 0.99; pressure ulcer: HR 0.99). Increasing number of comorbidities and inpatient stays were predictors for closure time in all models. Since these predictors may give an indication of wound severity, further clinical information should be considered in future models, as also indicated by the moderate values of the c-statistics. This requires future data linkage between SHI and primary studies (eg, registers).