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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 predicto...

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Autores principales: Hagenström, Kristina, Protz, Kerstin, Petersen, Jana, Augustin, Matthias
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Blackwell Publishing Ltd 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8684882/
https://www.ncbi.nlm.nih.gov/pubmed/33949101
http://dx.doi.org/10.1111/iwj.13599
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author Hagenström, Kristina
Protz, Kerstin
Petersen, Jana
Augustin, Matthias
author_facet Hagenström, Kristina
Protz, Kerstin
Petersen, Jana
Augustin, Matthias
author_sort Hagenström, Kristina
collection PubMed
description 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).
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spelling pubmed-86848822021-12-30 Development of a model to predict closure of chronic wounds in Germany: Claims data analysis Hagenström, Kristina Protz, Kerstin Petersen, Jana Augustin, Matthias Int Wound J Original Articles 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). Blackwell Publishing Ltd 2021-05-05 /pmc/articles/PMC8684882/ /pubmed/33949101 http://dx.doi.org/10.1111/iwj.13599 Text en © 2021 The Authors. International Wound Journal published by Medicalhelplines.com Inc (3M) and John Wiley & Sons Ltd. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Original Articles
Hagenström, Kristina
Protz, Kerstin
Petersen, Jana
Augustin, Matthias
Development of a model to predict closure of chronic wounds in Germany: Claims data analysis
title Development of a model to predict closure of chronic wounds in Germany: Claims data analysis
title_full Development of a model to predict closure of chronic wounds in Germany: Claims data analysis
title_fullStr Development of a model to predict closure of chronic wounds in Germany: Claims data analysis
title_full_unstemmed Development of a model to predict closure of chronic wounds in Germany: Claims data analysis
title_short Development of a model to predict closure of chronic wounds in Germany: Claims data analysis
title_sort development of a model to predict closure of chronic wounds in germany: claims data analysis
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8684882/
https://www.ncbi.nlm.nih.gov/pubmed/33949101
http://dx.doi.org/10.1111/iwj.13599
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