ArticleBMJ global health2022
mHealth-community health worker telemedicine intervention for surgical site infection diagnosis: a prospective study among women delivering via caesarean section in rural Rwanda.
Article in BMJ global health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 3 of them syntheses that pooled it.
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Who cites it
12 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Epidemiology of surgical site infections post-cesarean section in Africa: a comprehensive systematic review and meta-analysis.BMC pregnancy and childbirth · 2025Pooled it
- Surgical site infections after caesarean section across sub-Sahara Africa: a scoping review of prevalence and associated factors.Frontiers in global women's health · 2025Pooled it
- Prevalence of post-caesarean section surgical site infections in Rwanda: A systematic review and meta-analysis.International wound journal · 2024Pooled it
- SAGES white paper: strategic principles, operational considerations, and practical recommendations for building sustainable laparoscopic surgical training in low-resource settings: a 10-step guide.Surgical endoscopy · 2026Article
- Artificial intelligence and precision nursing in the operating room: transforming perioperative safety and surgical outcomes.Frontiers in bioengineering and biotechnology · 2026Review
- The feasibility of M-health for people with chronic low back pain in Shanghai, China: A qualitative study.Hong Kong physiotherapy journal : official publication of the Hong Kong Physiotherapy Association Limited = Wu li chih liao · 2025Article
- Acceptability of telemedicine for early surgical site infection diagnosis after cesarean delivery in rural Rwanda: a qualitative study.Maternal health, neonatology and perinatology · 2025Article
- Enhancing Surgical Wound Monitoring: A Paired Cohort Study Evaluating a New AI-Based Application for Automatic Detection of Potential Infections.Journal of clinical medicine · 2024Article
- WhatsApp Versus SMS for 2-Way, Text-Based Follow-Up After Voluntary Medical Male Circumcision in South Africa: Exploration of Messaging Platform Choice.JMIR formative research · 2024Article
- Machine Learning Approaches for the Image-Based Identification of Surgical Wound Infections: Scoping Review.Journal of medical Internet research · 2024Article
- Late and Persistent Symptoms Suggestive of Surgical Site Infections After Cesarean Section: Results from a Prospective Cohort Study in Rural Rwanda.Surgical infections · 2023Article
- Image-based surgical site infection algorithms to support home-based post-cesarean monitoring: Lessons from Rwanda.PLOS global public health · 2023Article
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14 authors.
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Abstract
backgroundSurgical site infections (SSIs) cause a significant global public health burden in low and middle-income countries. Most SSIs develop after patient discharge and may go undetected. We assessed the feasibility and diagnostic accuracy of an mHealth-community health worker (CHW) home-based telemedicine intervention to diagnose SSIs in women who delivered via caesarean section in rural Rwanda.
methodsThis prospective cohort study included women who underwent a caesarean section at Kirehe District Hospital between September 2019 and March 2020. At postoperative day 10 (±3 days), a trained CHW visited the woman at home, provided wound care and transmitted a photo of the wound to a remote general practitioner (GP) via WhatsApp. The GP reviewed the photo and made an SSI diagnosis. The next day, the woman returned to the hospital for physical examination by an independent GP, whose SSI diagnosis was considered the gold standard for our analysis. We describe the intervention process indicators and report the sensitivity and specificity of the telemedicine-based diagnosis.
resultsOf 787 women included in the study, 91.4% (n=719) were located at their home by the CHW and all of them (n=719, 100%) accepted the intervention. The full intervention was completed, including receipt of GP telemedicine diagnosis within 1 hour, for 79.0% (n=623). The GPs diagnosed 30 SSIs (4.2%) through telemedicine and 38 SSIs (5.4%) through physical examination. The telemedicine sensitivity was 36.8% and specificity was 97.6%. The negative predictive value was 96.4%.
conclusionsImplementation of an mHealth-CHW home-based intervention in rural Rwanda and similar settings is feasible. Patients' acceptance of the intervention was key to its success. The telemedicine-based SSI diagnosis had a high negative predictive value but a low sensitivity. Further studies must explore strategies to improve accuracy, such as accompanying wound images with clinical data or developing algorithms using machine learning.
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