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• W4384073276 abstract "<h3>Objectives</h3> Neonatal mortality remains high in low-resource settings. Accurate, evidence-based identification and management of neonatal conditions could improve outcomes through standardising 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 healthcare facilities. First phase CDS development included developing and implementing neonatal resuscitation algorithms, developing initial versions of CDS to address a range of neonatal conditions and a Delphi study to review key algorithms[1–3]. Here we describe the next stage of co-development, implementation and usability evaluation of digital CDS algorithms in Malawi and Zimbabwe. <h3>Methods</h3> 11 diagnosis-specific online workshops with Zimbabwean and Malawian neonatal experts were conducted (August 2021 to April 2022) encompassing: Review of available evidence Country specific guideline review (Essential Medicines List and Standard Treatment Guidelines for Zimbabwe (EDLIZ); Care of the infant and newborn (COIN), Malawi) Identification of uncertainties within the literature for future research After agreement of clinical content, the algorithms were programmed into a test script, tested with the respective hospital’s healthcare professionals (HCPs), and refined according to their feedback. Once finalised, the algorithms were programmed into the Neotree software and implemented at the tertiary-level study sites (Sally Mugabe Central hospital (SMCH), Zimbabwe and Kamuzu Central hospital (KCH), Malawi) in December 2021 and May 2022. Usability was evaluated at SMCH through two usability workshops and usability questionnaires: Post-Study System Usability Questionnaire (PSSUQ) and Systems Usability Scale (SUS). <h3>Results</h3> Eleven algorithms were refined and integrated into Neotree. The resulting output was evidence-based diagnostic and management algorithms tailored to local resource availability (Table 1). Where national management guidelines differed, e.g. birthweight thresholds for admissions to the neonatal unit, country-specific guidelines were created. Nine HCPs attended usability workshops and completed the SUS questionnaire (n=8 completed the PSSUQ). Both usability scores (SUS mean 75.8/100 (higher score better); PSSUQ overall 2.28/7 (lower score better)) demonstrated high usability of the CDS function (comparable to previous SUS scores assessing usability of Neotree data capture and dashboard functionalities) but highlighted issues around technical complexity which have been subsequently addressed. <h3>Conclusion</h3> This study highlighted the importance of collaborative participatory design. Real-world usability testing could further enhance implementation methodology. Effective local and international partnerships were key. Approvals by the Paediatric Associations of Zimbabwe and Malawi are pending. Mixed methods, larger scale evaluation of impact on neonatal quality of care and survival is planned. <h3>References</h3> Evans M, Corden MH, Crehan C, Fitzgerald F, Heys M. Refining clinical algorithms for a neonatal digital platform for low-income countries: a modified Delphi technique. <i>BMJ Open</i> 2021;<b>11</b>(5):e042124. Epub 2021/05/20. doi: 10.1136/bmjopen-2020-042124. Heys M, Kesler E, Sassoon Y, Wilson E, Fitzgerald F, Gannon H, et al. Development and implementation experience of a learning healthcare system for facility based newborn care in low resource settings: The Neotree. <i>Learning Health Systems</i> 2022;<b>n/a</b>(n/a):e10310. doi: https://doi.org/10.1002/lrh2.10310. Crehan C, Kesler E, Nambiar B, Dube Q, Lufesi N, Giaccone M, <i>et al</i>. The NeoTree application: developing an integrated mHealth solution to improve quality of newborn care and survival in a district hospital in Malawi. <i>BMJ Glob Health</i> 2019;<b>4</b>(1):e000860. Epub 2019/02/05. doi: 10.1136/bmjgh-2018-000860." @default.
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• W4384073276 date "2023-06-19" @default.
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• W4384073276 title "572 Development and implementation of digital diagnostic algorithms for neonatal units in Zimbabwe and Malawi: Neotree" @default.
• W4384073276 doi "https://doi.org/10.1136/archdischild-2023-rcpch.492" @default.
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