Patients, carers and healthcare providers' perspectives on a patient-owned surveillance system for diabetic foot ulcer care: A qualitative study.

Objective: Digital health has recently gained a foothold in monitoring and improving diabetes care. We aim to explore the views of patients, carers and healthcare providers (HCPs) regarding the use of a novel patient-owned wound surveillance application as part of outpatient management of patients with diabetic foot ulcers (DFUs). Methods: Semi-structured online interviews were conducted with patients, carers and HCPs in wound care for DFUs. The participants were recruited from a primary care polyclinic network and two tertiary hospitals in Singapore, within the same healthcare cluster. Purposive maximum variation sampling was used to select participants with differing attributes to ensure heterogeneity. Common themes relating to the wound imaging app were captured. Results: A total of 20 patients, 5 carers and 20 HCPs participated in the qualitative study. None of the participants have used a wound imaging app before. Regarding a patient-owned wound surveillance app, all were open and receptive to the system and workflow for use in DFU care. Four major themes emerged from patients and carers: (1) technology, (2) application features and usability, (3) feasibility of using the wound imaging application and (4) logistics of care. Four major themes were identified from HCPs: (1) attitudes towards wound imaging app, (2) preferences regarding functionality, (3) perceived challenges for patients/carers and (4) perceived barriers for HCPs. Conclusion: Our study highlighted several barriers and facilitators from patients, carers and HCPs regarding the use of a patient-owned wound surveillance app. These findings demonstrate the potential of digital health and areas to improve and tailor a DFU wound app suitable for implementation in the local population.

Clinical validation of an artificial intelligence-enabled wound imaging mobile application in diabetic foot ulcers.

There is a lifetime risk of 15% to 25% of development of diabetic foot ulcers (DFUs) in patients with diabetes mellitus. DFUs need to be followed up on and assessed for development of complications and/or resolution, which was traditionally performed using manual measurement. Our study aims to compare the intra- and inter-rater reliability of an artificial intelligence-enabled wound imaging mobile application (CARES4WOUNDS [C4W] system, Tetsuyu, Singapore) with traditional measurement. This is a prospective cross-sectional study on 28 patients with DFUs from June 2020 to January 2021. The main wound parameters assessed were length and width. For traditional manual measurement, area was calculated by overlaying traced wound on graphical paper. Intra- and inter-rater reliability was analysed using intra-class correlation statistics. A value of <0.5, 0.5-0.75, 0.75-0.9, and >0.9 indicates poor, moderate, good, and excellent reliability, respectively. Seventy-five wound episodes from 28 patients were collected and a total of 547 wound images were analysed in this study. The median wound area during the first clinic consultation and all wound episodes was 3.75 cm2 (interquartile range [IQR] 1.40-16.50) and 3.10 cm2 (IQR 0.60-14.84), respectively. There is excellent intra-rater reliability of C4W on three different image captures of the same wound (intra-rater reliability ranging 0.933-0.994). There is also excellent inter-rater reliability between three C4W devices for length (0.947), width (0.923), and area (0.965). Good inter-rater reliability for length, width, and area (range 0.825-0.934) was obtained between wound nurse measurement and each of the C4W devices. In conclusion, we obtained good inter-rater and intra-rater reliability of C4W measurements against traditional wound measurement. The C4W is a useful adjunct in monitoring DFU wound progress.

Clinical validation of a machine-learning-based handheld 3-dimensional infrared wound imaging device in venous leg ulcers.

Chronic venous insufficiency is a chronic disease of the venous system with a prevalence of 25% to 40% in females and 10% to 20% in males. Venous leg ulcers (VLUs) result from venous insufficiency. VLUs have a prevalence of 0.18% to 1% with a 1-year recurrence of 25% to 50%, bearing significant socioeconomic burden. It is therefore important for regular assessment and monitoring of VLUs to prevent worsening. Our study aims to assess the intra- and inter-rater reliability of a machine learning-based handheld 3-dimensional infrared wound imaging device (WoundAide [WA] imaging system, Konica Minolta Inc, Tokyo, Japan) compared with traditional measurements by trained wound nurse. This is a prospective cross-sectional study on 52 patients with VLUs from September 2019 to January 2021 using three WA imaging systems. Baseline patient profile and clinical demographics were collected. Basic wound parameters (length, width and area) were collected for both traditional measurements and measurements taken by the WA imaging systems. Intra- and inter-rater reliability was analysed using intra-class correlation statistics. A total of 222 wound images from 52 patients were assessed. There is excellent intra-rater reliability of the WA imaging system on three different image captures of the same wound (intra-rater reliability ranging 0.978-0.992). In addition, there is excellent inter-rater reliability between the three WA imaging systems for length (0.987), width (0.990) and area (0.995). Good inter-rater reliability for length and width (range 0.875-0.900) and excellent inter-rater reliability (range 0.932-0.950) were obtained between wound nurse measurement and each of the WA imaging system. In conclusion, high intra- and inter-rater reliability was obtained for the WA imaging systems. We also obtained high inter-rater reliability of WA measurements against traditional wound measurement. The WA imaging system is a useful clinical adjunct in the monitoring of VLU wound documentation.