Cohort profile: The Dutch wound monitor cohort and the Swedish Region Halland Integrated Platform (RHIP) wound cohort

Hard-to-heal wounds are a growing human and financial concern, constituting approximately 1-3% of the healthcare budget. Wound care is not a medical specialty and is often not prioritized within healthcare. A large portion of the cost and suffering caused by wounds has the potential to be mediated through improved knowledge and effectivised workflows. One potential way to achieve this is through the implementation of AI-tools to support clinicians in planning and executing wound care. Information-driven care is a framework for implementing AI-technology in healthcare. Wound Monitor is a Dutch database containing data collected from home-care visits conducted by wound specialists during 2005 to 2022, mostly in Limburg. It contains data of more than 17000 patients. Region Halland, Sweden, created a platform of integrated clinical, financial and operational data called "The Regional Healthcare Information Platform" (RHIP). The platform contains data on over 500 000 patients during 2008-2021. Within this data, a subset of almost 39000 patients have been diagnosed with wounds or wound related conditions. This subset of patients are defined as the RHIP Wound Cohort. This article characterizes the two wound cohorts in terms of demographics and wound types. Further, it examines the quality, quantity and granularity of the respective databases. The discussion section evaluates the strengths and weaknesses of the datasets in terms of the perspective they provide on the patient and wound journey. Lastly, the discussion section also explores how the cohorts may be utilized for predictive modeling and other machine learning-based applications in order to enable information-driven wound care.

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Publication Details

Journal
PLoS ONE
Published
2026-01-21
DOI
https://doi.org/10.1371/journal.pone.0339260
Primary Topic
Wound Healing and Treatments
Type
article
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article

Cohort profile: The Dutch wound monitor cohort and the Swedish Region Halland Integrated Platform (RHIP) wound cohort

M Ohlsson, Hanna Stenhamre, Ernst Ahlberg, Jens Lundström et al.
PLoS ONE
Wound Healing and Treatments
article

Cohort profile: The Dutch wound monitor cohort and the Swedish Region Halland Integrated Platform (RHIP) wound cohort

M Ohlsson, Hanna Stenhamre, Ernst Ahlberg, Jens Lundström, John Pavia, Oskar Gustafsson, Daniel Tsang
article en

Abstract

Hard-to-heal wounds are a growing human and financial concern, constituting approximately 1-3% of the healthcare budget. Wound care is not a medical specialty and is often not prioritized within healthcare. A large portion of the cost and suffering caused by wounds has the potential to be mediated through improved knowledge and effectivised workflows. One potential way to achieve this is through the implementation of AI-tools to support clinicians in planning and executing wound care. Information-driven care is a framework for implementing AI-technology in healthcare. Wound Monitor is a Dutch database containing data collected from home-care visits conducted by wound specialists during 2005 to 2022, mostly in Limburg. It contains data of more than 17000 patients. Region Halland, Sweden, created a platform of integrated clinical, financial and operational data called "The Regional Healthcare Information Platform" (RHIP). The platform contains data on over 500 000 patients during 2008-2021. Within this data, a subset of almost 39000 patients have been diagnosed with wounds or wound related conditions. This subset of patients are defined as the RHIP Wound Cohort. This article characterizes the two wound cohorts in terms of demographics and wound types. Further, it examines the quality, quantity and granularity of the respective databases. The discussion section evaluates the strengths and weaknesses of the datasets in terms of the perspective they provide on the patient and wound journey. Lastly, the discussion section also explores how the cohorts may be utilized for predictive modeling and other machine learning-based applications in order to enable information-driven wound care.

PLoS ONEVol. 21(1)
Royal Holloway University of London (GB), Lund University (SE), Mölnlycke Health Care (Sweden) (SE), Halmstad University (SE)
Partnerships for the goals
Openalex Percentile: Top 81%
Wound Healing and Treatments
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