Design of a Rule-based Decision Model for Assessment of Chronic Wounds
Creators: name: Haadi Mombini
name: Tulu, Bengisu
name: Strong, Diane
name: Agu, Emmanuel
name: Nguyen, Holly
name: Pedersen, Peder
name: Lindsay, Clifford
name: Dunn, Raymond
name: Loretz, Lorraine
Publisher: name: figshare
Year: 2020
Subjects: subject: 80609 Information Systems Management
subject: FOS: Computer and information sciences
subject: FOS: Computer and information sciences

description: Chronic wounds are expensive to treat and have a significant impact on patients’ quality of life [1]. Due to lack of access to wound experts, patients usually receive care from non-expert clinicians who have limited chronic wound assessment skills. Clinical decision support systems (CDSS) can assist these non-expert clinicians. This research in progress is part of an ongoing project working on developing a smartphone based wound CDSS to support non-expert clinicians during wound assessments in remote settings. Since each chronic wound type has a different assessment and management procedure, this paper focused on building a decision model that supports users in determining the type of chronic wounds so that we can later guide them on the proper evidence based decision path.We used design science research methodology (DSRM) model by Peffers et al. [2] to design rule-based decision models that can assess chronic wound type efficiently using wound photos and simple clinical values as input. We chose the rule-based decision models because they are intuitive, explainable and likely more trusted among clinicians.The meta-requirement gathering phase involved collection of chronic wound descriptors extracted from clinical guidelines and expert knowledge using 4 semi- structured interviews with two experts (a dually credentialed podiatric surgeon/vascular nurse practitioner and a plastic surgeon from UMass Memorial Medical Center). We received IRB approval for using wound photo repository maintained by the UMass Medical School. During the interviews, each expert 1) looked at 15 wound photos, 2) assessed wound type and conditions, and 3) explained how certain wound descriptors affected their decision. Using clinical wound management guidelines and analysis of our interview data, we identified design requirements and finally define our design principles (DPs) as: (1) design for simple explanation and (2) design for decision making under uncertainty. Following the design of the high level decision framework (see Fig.1), we developed our decision rules.Our rules in the model consist of conditional if-statements and actions that are executed after each condition or a set of conditions is met. The 35 rules embedded within the assessment module allow non-expert clinicians to input wound descriptors (e.g. location, tissues types, medical history, and other descriptors) into the systems to determine the type of wound. Below is an example of a complete decision rule from assessment module:If wound location is Bottom of the Toes AND patient has Diabetes History AND wound has Periwound Callus AND Round Shape AND Moist AND Full Thickness Depth Then show wound is diabetic foot ulcer with medium-high confidence level.Decision rules were tested using decision tables, and were evaluated using 17 new wound photos from the UMass collection. We found that imprecise location and incomplete patient medical history features (prior vascular issues) negatively affected the accuracy of the model. Rules were modified and validated further using wound photos and electronic health records (EHR) data containing clinicians’ notes collected from 4 new patients at a wound clinic. The model was successful in providing simple explanation for the given wound types within doctors notes. We also identified the venous ulcer assessment rules did not capture all the wound descriptors that were present in the photo; however, this did not affect the accuracy of the assessment module. Results showed that our model has the potential in assisting with the wound assessment and providing simple explanations for each assessment. Our data collection protocol is in place at a medical center and we will update our decision model to include infection assessment and actionable wound decisions.<br>References1. Jarbrink, K., et al., Prevalence and incidence of chronic wounds and related complications: a protocol for a systematic review. Syst Rev, 2016. 5(1): p. 152.2. Peffers, K., et al., A Design Science Research Methodology for Information Systems Research. Journal of Management Information Systems, 2007. 24(3): p. 45-77.