Implementation of Clinical Algorithms in Complex Wound Care: A Pilot Study on Feasibility and Professional Acceptance

PurposeMobile applications that integrate clinical algorithms have the potential to standardize wound assessment and to support clinical decision-making across assessment, diagnostic support, and therapeutic planning in complex wound care. This pilot study explored the feasibility of implementing such algorithms in a mobile application and examined concordance with nurse assessments and professional acceptance.MethodsA prospective multicenter pilot cohort study was conducted between June and October 2023 in rehabilitation units, outpatient clinics, primary healthcare, homecare, and hospitals. Adults aged ≥ 18 years with pressure injuries/pressure ulcers, venous leg ulcers, arterial ulcers, or diabetic foot ulcers were eligible. Nurses recorded data using the CWS_Validation application at three time points over 4 weeks. Agreement between algorithm-generated classifications and nurse assessments was analyzed using Cohen’s kappa, Fleiss’ kappa, and Krippendorff’s alpha. Nurse adherence to therapeutic recommendations and perceptions of the alert system were also evaluated.ResultsA total of 49 patients with 56 wounds (mean age = 79 years) were included. Pressure injuries/pressure ulcers were most prevalent (71.4%), particularly categories 3 (25%) and 4 (23.2%). The algorithm provided diagnoses for 46 wounds, with fair overall concordance with nurse assessments (κ = 0.41; 95% CI: 0.24–0.57). Adherence to therapeutic recommendations was high: 85.3% in complete monitoring and 90.3% in partial monitoring. Nurses rated the alert system positively (mean = 4.34, SD = 0.82) in complete monitoring sessions (n = 109).ConclusionsClinical algorithms can be feasibly integrated into mobile applications and are well accepted by nurses across diverse care contexts. These preliminary findings highlight the potential of algorithm-driven tools to support wound assessment and decision-making, while underscoring the need for larger studies with more robust designs to confirm clinical impact.