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Gannon H, Larsson L, Chimhuya S, Mangiza M, Wilson E, Kesler E, Chimhini G, Fitzgerald F, Zailani G, Crehan C, Khan N, Hull-Bailey T, Sassoon Y, Baradza M, Heys M, Chiume M. Development and Implementation of Digital Diagnostic Algorithms for Neonatal Units in Zimbabwe and Malawi: Development and Usability Study. JMIR Form Res 2024; 8:e54274. [PMID: 38277198 PMCID: PMC10858425 DOI: 10.2196/54274] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Revised: 12/19/2023] [Accepted: 12/20/2023] [Indexed: 01/27/2024] Open
Abstract
BACKGROUND Despite an increase in hospital-based deliveries, neonatal mortality remains high in low-resource settings. Due to limited laboratory diagnostics, there is significant reliance on clinical findings to inform diagnoses. Accurate, evidence-based identification and management of neonatal conditions could improve outcomes by standardizing care. This could be achieved through digital clinical decision support (CDS) tools. Neotree is a digital, quality improvement platform that incorporates CDS, aiming to improve neonatal care in low-resource health care facilities. Before this study, first-phase CDS development included developing and implementing neonatal resuscitation algorithms, creating initial versions of CDS to address a range of neonatal conditions, and a Delphi study to review key algorithms. OBJECTIVE This second-phase study aims to codevelop and implement neonatal digital CDS algorithms in Malawi and Zimbabwe. METHODS Overall, 11 diagnosis-specific web-based workshops with Zimbabwean, Malawian, and UK neonatal experts were conducted (August 2021 to April 2022) encompassing the following: (1) review of available evidence, (2) review of country-specific guidelines (Essential Medicines List and Standard Treatment Guidelinesfor Zimbabwe and Care of the Infant and Newborn, Malawi), and (3) identification of uncertainties within the literature for future studies. After agreement of clinical content, the algorithms were programmed into a test script, tested with the respective hospital's health care professionals (HCPs), and refined according to their feedback. Once finalized, the algorithms were programmed into the Neotree software and implemented at the tertiary-level implementation sites: Sally Mugabe Central Hospital in Zimbabwe and Kamuzu Central Hospital in Malawi, in December 2021 and May 2022, respectively. In Zimbabwe, usability was evaluated through 2 usability workshops and usability questionnaires: Post-Study System Usability Questionnaire (PSSUQ) and System Usability Scale (SUS). RESULTS Overall, 11 evidence-based diagnostic and management algorithms were tailored to local resource availability. These refined algorithms were then integrated into Neotree. Where national management guidelines differed, country-specific guidelines were created. In total, 9 HCPs attended the usability workshops and completed the SUS, among whom 8 (89%) completed the PSSUQ. Both usability scores (SUS mean score 75.8 out of 100 [higher score is better]; PSSUQ overall score 2.28 out of 7 [lower score is better]) demonstrated high usability of the CDS function but highlighted issues around technical complexity, which continue to be addressed iteratively. CONCLUSIONS This study describes the successful development and implementation of the only known neonatal CDS system, incorporated within a bedside data capture system with the ability to deliver up-to-date management guidelines, tailored to local resource availability. This study highlighted the importance of collaborative participatory design. Further implementation evaluation is planned to guide and inform the development of health system and program strategies to support newborn HCPs, with the ultimate goal of reducing preventable neonatal morbidity and mortality in low-resource settings.
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Affiliation(s)
- Hannah Gannon
- Population, Policy and Practice, Institute of Child Health, University College London, London, United Kingdom
- Biomedical Research and Training Institute, Harare, Zimbabwe
| | - Leyla Larsson
- Institute of Computational Biology, Computational Health Centre, Helmholtz, Munich, Germany
| | - Simbarashe Chimhuya
- Department of Child, Adolescent and Women's Health, Faculty of Medicine and Health Science, University of Zimbabwe, Harare, Zimbabwe
| | | | - Emma Wilson
- Population, Policy and Practice, Institute of Child Health, University College London, London, United Kingdom
| | - Erin Kesler
- Children's Hospital of Philadelphia, Philidephia, PA, United States
| | - Gwendoline Chimhini
- Department of Child, Adolescent and Women's Health, Faculty of Medicine and Health Science, University of Zimbabwe, Harare, Zimbabwe
| | - Felicity Fitzgerald
- Biomedical Research and Training Institute, Harare, Zimbabwe
- Department of Infectious Disease, Imperial College London, London, United Kingdom
| | | | - Caroline Crehan
- Population, Policy and Practice, Institute of Child Health, University College London, London, United Kingdom
| | - Nushrat Khan
- Population, Policy and Practice, Institute of Child Health, University College London, London, United Kingdom
| | - Tim Hull-Bailey
- Population, Policy and Practice, Institute of Child Health, University College London, London, United Kingdom
| | | | | | - Michelle Heys
- Population, Policy and Practice, Institute of Child Health, University College London, London, United Kingdom
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Jacobsson B, Simpson JL. FIGO good practice recommendations for reducing preterm birth and improving child outcomes. Int J Gynaecol Obstet 2021; 155:1-4. [PMID: 34520060 DOI: 10.1002/ijgo.13863] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Bo Jacobsson
- Department of Obstetrics and Gynecology, Institute of Clinical Science, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.,Department of Obstetrics and Gynecology, Sahlgrenska University Hospital, Region Västra Götaland, Gothenburg, Sweden.,Department of Genetics and Bioinformatics, Domain of Health Data and Digitalization, Institute of Public Health, Oslo, Norway
| | - Joe Leigh Simpson
- Department of Human and Molecular Genetics, Department of Obstetrics and Gynecology, Herbert Wertheim College of Medicine, Florida International University, Miami, Florida, USA
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