Background: In rural Africa where access to medical personnel is limited, telemedicine can be leveraged to empower community health workers (CHWs) to support effective postpartum home-based care after cesarean section (c-section). As a first step toward telemedicine, we assessed the sensitivity, specificity, and interrater reliability of image-based diagnosis of surgical site infections (SSIs) among women delivering via c-section at a rural Rwandan Hospital.
Methods: Women ≥18 years who underwent c-section from March to October 2017 at Kirehe District Hospital (KDH) were enrolled. On postoperative day 10 at KDH, participants underwent a physical examination by a general practitioner, who provided a diagnosis of SSI or no SSI. Trained CHWs photographed patients' incisions and the collected images were shown to six physicians, who upon review, assigned one of the following diagnoses to each image: definite SSI, suspected SSI, suspected no SSI, and definite no SSI, which were compared with the diagnoses based on physical exam. We report the sensitivity and specificity and assessed reviewer agreement using Gwet's AC1.
Results: 569 images were included, with 61 women (10.7%) diagnosed with an SSI. Of the 3414 image-reviews, 49 (1.4%) could not be assigned diagnoses due to image quality. The median sensitivity and specificity were 0.83 and 0.69, respectively. The Gwet's AC1 estimate for binary classification was 0.46.
Conclusions: We demonstrate decent accuracy but only moderate consistency for photograph-based SSI diagnosis. Strategies to improve overall agreement include providing clinical information to accompany photographs, providing a baseline photograph for comparison, and implementing photograph-taking processes aimed at improving image quality.
© 2022. The Author(s) under exclusive licence to Société Internationale de Chirurgie.