mHealth-community health worker telemedicine intervention for surgical site infection diagnosis: a prospective study among women delivering via caesarean section in rural Rwanda.
mHealth-community health worker telemedicine intervention for surgical site infection diagnosis: a prospective study among women delivering via caesarean section in rural Rwanda.
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DOI：
10.1136/bmjgh-2022-009365
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发表时间：
2022-07
影响因子：
8.1
通讯作者：
Hedt-Gauthier, Bethany L.
中科院分区：
文献类型：
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作者：
Nkurunziza, Theoneste;Williams, Wendy;Kateera, Fredrick;Riviello, Robert;Niyigena, Anne;Miranda, Elizabeth;Bikorimana, Laban;Nkurunziza, Jonathan;Velin, Lotta;Goodman, Andrea S.;Matousek, Alex;Klug, Stefanie J.;Gaju, Erick;Hedt-Gauthier, Bethany L.
手术部位感染（ssi）在低收入和中等收入国家造成重大的全球公共卫生负担。大多数ssi在患者出院后发展，可能未被发现。我们评估了移动医疗-社区卫生工作者（CHW）家庭远程医疗干预在卢旺达农村剖宫产妇女中诊断ssi的可行性和诊断准确性。这项前瞻性队列研究包括2019年9月至2020年3月期间在Kirehe地区医院接受剖腹产手术的妇女。术后第10天（±3天），一名训练有素的CHW到家中探访该妇女，提供伤口护理，并通过WhatsApp将伤口照片传送给远程全科医生（GP）。全科医生看了照片，诊断为SSI。第二天，该妇女回到医院接受独立全科医生的体格检查，其SSI诊断被认为是我们分析的金标准。我们描述了干预过程指标，并报告了基于远程医疗的诊断的敏感性和特异性。在纳入研究的787名妇女中，91.4% （n=719）的妇女被CHW安置在家中，所有妇女（n=719, 100%）接受了干预。完成全部干预，包括在1小时内接受GP远程医疗诊断，占79.0% （n=623）。全科医生通过远程医疗诊断ssi 30例（4.2%），通过体格检查诊断ssi 38例（5.4%）。远程医疗的敏感性为36.8%，特异性为97.6%。阴性预测值为96.4%。在卢旺达农村和类似环境中实施移动卫生保健家庭干预是可行的。患者对干预的接受程度是其成功的关键。基于远程医疗的SSI诊断具有较高的阴性预测值，但敏感性较低。进一步的研究必须探索提高准确性的策略，例如将伤口图像与临床数据相结合或使用机器学习开发算法。
Surgical 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. This 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. Of 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%. Implementation 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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