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| ID | Type | Description | Link |
|---|---|---|---|
| WoundPilot | Other Identifier | Ghent University Hospital |
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This study evaluates whether a digital decision support tool, called WoundPilot, can help primary care nurses make more accurate and consistent decisions when caring for patients with chronic wounds.
In daily practice, treatment decisions for chronic wounds can vary between clinicians, even when they assess the same patient. This variation may lead to delays in appropriate care, inconsistent treatment choices, or unnecessary referrals. WoundPilot was developed to guide clinicians through a structured wound assessment and link this assessment to clear treatment recommendations.
In this study, primary care nurses will assess a series of clinical cases either with or without the support of WoundPilot. Their decisions will be compared with an expert reference standard to determine whether the use of WoundPilot improves the accuracy of decisions and reduces differences between nurses.
The results of this study will help determine whether WoundPilot can support more consistent and evidence-based wound care in clinical practice.
Background Clinical decision-making in chronic wound care shows considerable variability, even when clinicians are presented with similar patient information. This variability may result in delayed or inappropriate treatment, inconsistent use of therapies, or failure to escalate care when clinically indicated.
Structured clinical decision support systems (CDSS) aim to reduce unwarranted variation by guiding clinicians through predefined assessment steps and linking these to management pathways. WoundPilot is an evidence-informed CDSS developed to support structured wound assessment and treatment decision-making in primary care.
Objective The primary objective is to evaluate the effect of WoundPilot on the accuracy and consistency of clinical decision-making in chronic wound care among primary care nurses.
Secondary objectives are to:
Study Design
This study is a randomized parallel vignette study conducted among primary care nurses. Participants are randomly assigned to:
Methods Participants include primary care nurses involved in wound care decision-making in home care or nursing home settings.
In the intervention group, participants receive a short training on WoundPilot and use the tool to assess clinical cases. In the control group, participants assess the same type of cases using their usual reasoning and verbalize their decision-making process.
For each case, participants make decisions regarding wound assessment and treatment planning, including supportive therapy, antimicrobial use, debridement, dressing selection, and referral.
An expert reference standard is established by a panel of wound care experts. Participant decisions are compared to this reference.
Outcomes
The primary outcome is the correctness of treatment decisions compared with the expert reference standard. Secondary outcomes include:
Significance This study evaluates whether a structured clinical decision support system can improve the accuracy and consistency of clinical decision-making in chronic wound care. Findings may inform the role of digital decision support tools in supporting evidence-based practice in primary care.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Reasoning with decision support | Experimental | Participants in this arm assess standardized clinical cases of patients with chronic wounds using WoundPilot, a digital clinical decision support system (CDSS). WoundPilot guides users through a structured, stepwise wound assessment, including evaluation of wound etiology, infection, wound evolution, wound bed characteristics, exudate, and wound edges. Based on the assessment, the system provides structured guidance to support treatment decision-making, including recommendations on supportive therapy, local wound management, and referral. Participants receive a brief training on the use of WoundPilot prior to the assessment and then independently evaluate a set of clinical cases using the tool. |
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| Usual reasoning | No Intervention | Participants in this arm assess standardized clinical cases of patients with chronic wounds using their usual clinical reasoning, without the support of a clinical decision support system. Participants independently evaluate each case and make decisions regarding wound assessment and treatment planning, including supportive therapy, local wound management, and referral. They are asked to verbalize their reasoning during the assessment process, which is recorded for subsequent analysis. No additional training or decision support tool is provided. |
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| WoundPilot | Device | WoundPilot is a software-based clinical decision support system (CDSS) designed to support structured wound assessment and treatment decision-making in primary care. The system guides users through a stepwise assessment process using predefined decision nodes, including evaluation of wound etiology, infection, wound evolution, wound bed characteristics, exudate, and wound edges. Based on the entered information, WoundPilot provides structured guidance to support treatment planning, including recommendations on supportive therapy, local wound management, and referral. The system incorporates evidence-informed clinical pathways and aims to standardize wound assessment and reduce variability in clinical decision-making. |
| Measure | Description | Time Frame |
|---|---|---|
| Accuracy of Treatment Decisions Compared With an Expert Reference Standard | Accuracy of treatment decisions will be assessed by comparing each participant's treatment decisions for standardized chronic wound cases with an expert reference standard. Treatment decisions include supportive therapy, antimicrobial therapy, wound cleansing, debridement, choice of wound product, management of wound edges or wound environment, protection of exposed bone or tendon when applicable, referral or contact with another healthcare professional or department, wound swab, and additional technical investigations. Accuracy will be analyzed at the level of individual treatment decision components and as a composite correctness score per case. | During a single assessment session (approximately 2 hours) |
| Measure | Description | Time Frame |
|---|---|---|
| Alignment of Wound Assessment Decisions With Expert Reference Standard | Accuracy of wound assessment decisions will be evaluated by comparing participant assessments with an expert reference standard. This includes classification of wound type, assessment of infection (local, spreading, or systemic), evaluation of wound evolution, wound bed characteristics, presence of hypergranulation or exposed structures, amount of exudate, and assessment of wound edges and surrounding skin. |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Steven Smet, Master | Contact | +3293328793 | Steven.Smet@UZGent.be | |
| Hilde Beele, PhD | Contact | +32 9 332 33 81 | Hilde.Beele@uzgent.be |
| Name | Affiliation | Role |
|---|---|---|
| Steven Smet, Master | University Hospital, Ghent | Study Chair |
| Hilde Beele, PhD | University Hospital, Ghent | Principal Investigator |
| Dimitri Beeckman, PhD |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Ghent University Hospital | Ghent | Oost-Vlaanderen | 9000 | Belgium |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 38461069 | Background | Smet S, Verhaeghe S, Beeckman D, Fourie A, Beele H. The process of clinical decision-making in chronic wound care: A scenario-based think-aloud study. J Tissue Viability. 2024 May;33(2):231-238. doi: 10.1016/j.jtv.2024.03.002. Epub 2024 Mar 1. | |
| 34237439 | Background | Smet S, Probst S, Holloway S, Fourie A, Beele H, Beeckman D. The measurement properties of assessment tools for chronic wounds: A systematic review. Int J Nurs Stud. 2021 Sep;121:103998. doi: 10.1016/j.ijnurstu.2021.103998. Epub 2021 Jun 7. |
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Individual participant data (IPD) will not be shared due to the small sample size and the risk of potential re-identification of participants, as well as the inclusion of qualitative data (e.g., verbalized reasoning) that may contain indirectly identifiable information.
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| ID | Term |
|---|---|
| D014947 | Wounds and Injuries |
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One group uses WoundPilot, the other group uses usual clinical reasoning.
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| During a single assessment session (approximately 2 hours) |
| Between-Nurse Variability in Treatment Decisions | Variability in treatment decisions between participants will be assessed within each study group. Agreement between participants will be quantified using statistical measures such as Fleiss' kappa to evaluate consistency of treatment decisions across standardized cases. | During a single assessment session (approximately 2 hours) |
| Between-Nurse Variability in Wound Assessment Decisions | Variability in wound assessment decisions between participants will be evaluated within each study group. Agreement will be quantified using appropriate statistical methods (e.g., Fleiss' kappa) to assess consistency in the evaluation of decision-critical wound parameters. | During a single assessment session (approximately 2 hours) |
| Recognition and Interpretation of Clinical Change | Participants' ability to recognize and correctly interpret clinical changes over time will be assessed by comparing decisions between initial and follow-up case scenarios. Correct identification of wound evolution and appropriate adaptation of treatment decisions will be evaluated against the expert reference standard. | During a single assessment session (approximately 2 hours) |
| Usability of WoundPilot (Dutch System Usability Scale) | Usability of WoundPilot will be assessed using the Dutch System Usability Scale (D-SUS), a validated 10-item questionnaire scored on a 5-point Likert scale. The D-SUS provides a total score ranging from 0 to 100, with higher scores indicating better usability. | During a single assessment session (approximately 2 hours) |
| University Ghent |
| Study Chair |