mHealth-community health worker telemedicine intervention for surgical site infection diagnosis: a prospective study among women delivering via caesarean section in rural Rwanda

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.

Prevalence of post‐caesarean section surgical site infections in Rwanda: A systematic review and meta‐analysis

“…The included studies were published from 2014 to 2023. A total of 10 studies were conducted at Kirehe District Hospital, 1 , 9 , 13 , 15 , 16 , 17 , 18 , 19 , 20 , 21 two studies at University Teaching Hospital of Kigali, 10 , 22 and one study at University Teaching Hospital of Butare, 23 Kibungo District Hospital, 24 Ruhengeri Referral Hospital, 25 Kabgayi Hospital 14 and Bushenge Provincial Hospital each. 26 Nine studies were cohort studies, 1 , 9 , 15 , 16 , 17 , 19 , 20 , 21 , 24 six were randomized controlled trials 10 , 13 , 18 , 22 , 25 , 26 and two were cross‐sectional studies.…”

“…A total of 10 studies were conducted at Kirehe District Hospital, 1 , 9 , 13 , 15 , 16 , 17 , 18 , 19 , 20 , 21 two studies at University Teaching Hospital of Kigali, 10 , 22 and one study at University Teaching Hospital of Butare, 23 Kibungo District Hospital, 24 Ruhengeri Referral Hospital, 25 Kabgayi Hospital 14 and Bushenge Provincial Hospital each. 26 Nine studies were cohort studies, 1 , 9 , 15 , 16 , 17 , 19 , 20 , 21 , 24 six were randomized controlled trials 10 , 13 , 18 , 22 , 25 , 26 and two were cross‐sectional studies. 14 , 23 Five studies had sample sizes above 650 participants 9 , 13 , 16 , 21 , 26 while 12 studies had sample sizes below 650 participants.…”

“…26 Nine studies were cohort studies, 1 , 9 , 15 , 16 , 17 , 19 , 20 , 21 , 24 six were randomized controlled trials 10 , 13 , 18 , 22 , 25 , 26 and two were cross‐sectional studies. 14 , 23 Five studies had sample sizes above 650 participants 9 , 13 , 16 , 21 , 26 while 12 studies had sample sizes below 650 participants. 1 , 10 , 14 , 15 , 17 , 18 , 19 , 20 , 22 , 23 , 24 , 25 Eight studies were published from 2021 to 2023 9 , 13 , 14 , 16 , 17 , 20 , 21 , 24 while nine studies were published before 2021 (from 2020 to 2014).…”

“… 14 , 23 Five studies had sample sizes above 650 participants 9 , 13 , 16 , 21 , 26 while 12 studies had sample sizes below 650 participants. 1 , 10 , 14 , 15 , 17 , 18 , 19 , 20 , 22 , 23 , 24 , 25 Eight studies were published from 2021 to 2023 9 , 13 , 14 , 16 , 17 , 20 , 21 , 24 while nine studies were published before 2021 (from 2020 to 2014). 1 , 10 , 15 , 18 , 19 , 22 , 23 , 25 , 26 The highest post‐caesarean SSI prevalence reported was 15.9% in the study conducted at the University Teaching Hospital of Kigali 10 while the lowest prevalence was 1.8% in the study conducted at Kirehe District Hospital 1 (Table 1 ).…”

Image-based surgical site infection algorithms to support home-based post-cesarean monitoring: Lessons from Rwanda

“…Over the last eight years, our research team has explored several strategies for sustainable, home-based, CHW-supported care for women after cesarean delivery in rural Rwanda. We have demonstrated that home-based follow-up by CHWs is feasible and acceptable [5,6], but our attempts for simple clinical screenings or sending pictures to general practitioners has resulted in low SSI diagnostic accuracy [5][6][7][8]. In contrast, our machine learning image-based diagnostic algorithms are yielding higher accuracy: 81.3% sensitivity and 65.3% specificity for visible image algorithms [9], increasing to 97% sensitivity and 87% specificity when using computer vision techniques and color calibration in the image processing pipeline, and 95% specificity and 84% specificity for thermal image algorithms [10].…”