Vera von Kalckreuth, Victor P Rwandarwacu, Ludovico Cobuccio, Théophile Dusengumuremyi, Gillian A Levine, Martin Norris, Alix Miauton, Rainer Tan, Emmanuel Rusingiza, Christian Umuhoza, Florent H Rutagarama, Hippolyte B Muhire, John Baptist Nkuranga, Nina Vaezipour, Kristina Keitel, Fenella Beynon, Lisine Tuyisenge, Valérie D'Acremont, Alexandra V Kulinkina
{"title":"eppoct +卢旺达:在初级卫生保健机构管理15岁以下患病儿童的临床决策支持算法。","authors":"Vera von Kalckreuth, Victor P Rwandarwacu, Ludovico Cobuccio, Théophile Dusengumuremyi, Gillian A Levine, Martin Norris, Alix Miauton, Rainer Tan, Emmanuel Rusingiza, Christian Umuhoza, Florent H Rutagarama, Hippolyte B Muhire, John Baptist Nkuranga, Nina Vaezipour, Kristina Keitel, Fenella Beynon, Lisine Tuyisenge, Valérie D'Acremont, Alexandra V Kulinkina","doi":"10.4314/rjmhs.v8i1.13","DOIUrl":null,"url":null,"abstract":"<p><p>Primary health systems in resource-constrained settings suffer from human resource shortages, low quality care, and diagnostic uncertainty, resulting in over-reliance on antibiotics, increasing risks of antimicrobial resistance. Digital clinical decision support algorithms (CDSAs) help healthcare workers adhere to clinical guidelines and improve prescribing practices. In this manuscript, we present the scope and content of 'ePOCT+ Rwanda' (electronic Point-Of-Care Tests +), a CDSA trialed in primary health centers of Rusizi and Nyamasheke districts during the DYNAMIC project. The algorithm is based on the WHO IMCI guidelines, expanded to include a broader range of ages (between 1 day and 14 years, inclusive) and acute medical conditions encountered in primary care (57 diagnoses for young infants < 2 months and 144 diagnoses for children 2 months to 14 years). The digital application used to deploy ePOCT+ prompts users to enter the results of medical history, physical examinations and laboratory tests to propose diagnoses, treatments and managements. In addition to routine point-of-care tests, ePOCT+ utilizes haemoglobin and C-reactive protein tests, as well as pulse oximetry, targeted to specific clinical conditions. We discuss the rationale behind the content of the algorithm and the process of aligning it with the Rwandan paediatric guidelines and tailoring it to the primary care setting.</p>","PeriodicalId":520910,"journal":{"name":"Rwanda journal of medicine and health sciences","volume":"8 1","pages":"148-162"},"PeriodicalIF":0.0000,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12188259/pdf/","citationCount":"0","resultStr":"{\"title\":\"ePOCT+ Rwanda: A Clinical Decision Support Algorithm For Managing Sick Children Below 15 Years of Age in Primary Healthcare Settings.\",\"authors\":\"Vera von Kalckreuth, Victor P Rwandarwacu, Ludovico Cobuccio, Théophile Dusengumuremyi, Gillian A Levine, Martin Norris, Alix Miauton, Rainer Tan, Emmanuel Rusingiza, Christian Umuhoza, Florent H Rutagarama, Hippolyte B Muhire, John Baptist Nkuranga, Nina Vaezipour, Kristina Keitel, Fenella Beynon, Lisine Tuyisenge, Valérie D'Acremont, Alexandra V Kulinkina\",\"doi\":\"10.4314/rjmhs.v8i1.13\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Primary health systems in resource-constrained settings suffer from human resource shortages, low quality care, and diagnostic uncertainty, resulting in over-reliance on antibiotics, increasing risks of antimicrobial resistance. Digital clinical decision support algorithms (CDSAs) help healthcare workers adhere to clinical guidelines and improve prescribing practices. In this manuscript, we present the scope and content of 'ePOCT+ Rwanda' (electronic Point-Of-Care Tests +), a CDSA trialed in primary health centers of Rusizi and Nyamasheke districts during the DYNAMIC project. The algorithm is based on the WHO IMCI guidelines, expanded to include a broader range of ages (between 1 day and 14 years, inclusive) and acute medical conditions encountered in primary care (57 diagnoses for young infants < 2 months and 144 diagnoses for children 2 months to 14 years). The digital application used to deploy ePOCT+ prompts users to enter the results of medical history, physical examinations and laboratory tests to propose diagnoses, treatments and managements. In addition to routine point-of-care tests, ePOCT+ utilizes haemoglobin and C-reactive protein tests, as well as pulse oximetry, targeted to specific clinical conditions. We discuss the rationale behind the content of the algorithm and the process of aligning it with the Rwandan paediatric guidelines and tailoring it to the primary care setting.</p>\",\"PeriodicalId\":520910,\"journal\":{\"name\":\"Rwanda journal of medicine and health sciences\",\"volume\":\"8 1\",\"pages\":\"148-162\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-03-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12188259/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Rwanda journal of medicine and health sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4314/rjmhs.v8i1.13\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/3/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Rwanda journal of medicine and health sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4314/rjmhs.v8i1.13","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/3/1 0:00:00","PubModel":"eCollection","JCR":"","JCRName":"","Score":null,"Total":0}
ePOCT+ Rwanda: A Clinical Decision Support Algorithm For Managing Sick Children Below 15 Years of Age in Primary Healthcare Settings.
Primary health systems in resource-constrained settings suffer from human resource shortages, low quality care, and diagnostic uncertainty, resulting in over-reliance on antibiotics, increasing risks of antimicrobial resistance. Digital clinical decision support algorithms (CDSAs) help healthcare workers adhere to clinical guidelines and improve prescribing practices. In this manuscript, we present the scope and content of 'ePOCT+ Rwanda' (electronic Point-Of-Care Tests +), a CDSA trialed in primary health centers of Rusizi and Nyamasheke districts during the DYNAMIC project. The algorithm is based on the WHO IMCI guidelines, expanded to include a broader range of ages (between 1 day and 14 years, inclusive) and acute medical conditions encountered in primary care (57 diagnoses for young infants < 2 months and 144 diagnoses for children 2 months to 14 years). The digital application used to deploy ePOCT+ prompts users to enter the results of medical history, physical examinations and laboratory tests to propose diagnoses, treatments and managements. In addition to routine point-of-care tests, ePOCT+ utilizes haemoglobin and C-reactive protein tests, as well as pulse oximetry, targeted to specific clinical conditions. We discuss the rationale behind the content of the algorithm and the process of aligning it with the Rwandan paediatric guidelines and tailoring it to the primary care setting.