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Development and implementation experience of a learning healthcare system for facility based newborn care in low resource settings: The Neotree.

作者信息

Heys Michelle, Kesler Erin, Sassoon Yali, Wilson Emma, Fitzgerald Felicity, Gannon Hannah, Hull-Bailey Tim, Chimhini Gwendoline, Khan Nushrat, Cortina-Borja Mario, Nkhoma Deliwe, Chiyaka Tarisai, Stevenson Alex, Crehan Caroline, Chiume Msandeni Esther, Chimhuya Simbarashe

机构信息

Population, Policy and Practice Research and Teaching Department University College London Great Ormond Street Institute of Child Health London UK.

Children's Hospital of Philadelphia General, Thoracic, and Fetal Surgery Newborn Intensive Care Unit Philadelphia USA.

出版信息

Learn Health Syst. 2022 Apr 6;7(1):e10310. doi: 10.1002/lrh2.10310. eCollection 2023 Jan.


DOI:10.1002/lrh2.10310
PMID:36654803
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9835040/
Abstract

INTRODUCTION: Improving peri- and postnatal facility-based care in low-resource settings (LRS) could save over 6000 babies' lives per day. Most of the annual 2.4 million neonatal deaths and 2 million stillbirths occur in healthcare facilities in LRS and are preventable through the implementation of cost-effective, simple, evidence-based interventions. However, their implementation is challenging in healthcare systems where one in four babies admitted to neonatal units die. In high-resource settings healthcare systems strengthening is increasingly delivered via learning healthcare systems to optimise care quality, but this approach is rare in LRS. METHODS: Since 2014 we have worked in Bangladesh, Malawi, Zimbabwe, and the UK to co-develop and pilot the Neotree system: an android application with accompanying data visualisation, linkage, and export. Its low-cost hardware and state-of-the-art software are used to support healthcare professionals to improve postnatal care at the bedside and to provide insights into population health trends. Here we summarise the formative conceptualisation, development, and preliminary implementation experience of the Neotree. RESULTS: Data thus far from ~18 000 babies, 400 healthcare professionals in four hospitals (two in Zimbabwe, two in Malawi) show high acceptability, feasibility, usability, and improvements in healthcare professionals' ability to deliver newborn care. The data also highlight gaps in knowledge in newborn care and quality improvement. Implementation has been resilient and informative during external crises, for example, coronavirus disease 2019 (COVID-19) pandemic. We have demonstrated evidence of improvements in clinical care and use of data for Quality Improvement (QI) projects. CONCLUSION: Human-centred digital development of a QI system for newborn care has demonstrated the potential of a sustainable learning healthcare system to improve newborn care and outcomes in LRS. Pilot implementation evaluation is ongoing in three of the four aforementioned hospitals (two in Zimbabwe and one in Malawi) and a larger scale clinical cost effectiveness trial is planned.

摘要
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1592/9835040/5db7891a9926/LRH2-7-e10310-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1592/9835040/c7a030829dd5/LRH2-7-e10310-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1592/9835040/f8d8a4b56546/LRH2-7-e10310-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1592/9835040/834c1a796467/LRH2-7-e10310-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1592/9835040/5db7891a9926/LRH2-7-e10310-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1592/9835040/c7a030829dd5/LRH2-7-e10310-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1592/9835040/f8d8a4b56546/LRH2-7-e10310-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1592/9835040/834c1a796467/LRH2-7-e10310-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1592/9835040/5db7891a9926/LRH2-7-e10310-g002.jpg

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[1]
Development and implementation experience of a learning healthcare system for facility based newborn care in low resource settings: The Neotree.

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[2]
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[2]
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[3]
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J Pediatric Infect Dis Soc. 2025-4-8

[4]
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[5]
Progress with the Learning Health System 2.0: a rapid review of Learning Health Systems' responses to pandemics and climate change.

BMC Med. 2024-3-22

[6]
Development and Implementation of Digital Diagnostic Algorithms for Neonatal Units in Zimbabwe and Malawi: Development and Usability Study.

JMIR Form Res. 2024-1-26

[7]
Effects of the COVID-19 pandemic on the outcomes of HIV-exposed neonates: a Zimbabwean tertiary hospital experience.

BMC Pediatr. 2024-1-5

[8]
Development and Pilot Implementation of Neotree, a Digital Quality Improvement Tool Designed to Improve Newborn Care and Survival in 3 Hospitals in Malawi and Zimbabwe: Cost Analysis Study.

JMIR Mhealth Uhealth. 2023-12-22

[9]
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Wellcome Open Res. 2022-12-19

[10]
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本文引用的文献

[1]
Indirect impacts of the COVID-19 pandemic at two tertiary neonatal units in Zimbabwe and Malawi: an interrupted time series analysis.

BMJ Open. 2022-6-21

[2]
Usability-Focused Development and Usage of NeoTree-Beta, an App for Newborn Care in a Low-Resource Neonatal Unit, Malawi.

Front Public Health. 2022

[3]
Admissions to a Low-Resource Neonatal Unit in Malawi Using a Mobile App and Dashboard: A 1-Year Digital Perinatal Outcome Audit.

Front Digit Health. 2021-12-23

[4]
Global, regional, and national progress towards Sustainable Development Goal 3.2 for neonatal and child health: all-cause and cause-specific mortality findings from the Global Burden of Disease Study 2019.

Lancet. 2021-9-4

[5]
Auditing use of antibiotics in Zimbabwean neonates.

Infect Prev Pract. 2020-2-19

[6]
Refining clinical algorithms for a neonatal digital platform for low-income countries: a modified Delphi technique.

BMJ Open. 2021-5-18

[7]
LSE-Lancet Commission on the future of the NHS: re-laying the foundations for an equitable and efficient health and care service after COVID-19.

Lancet. 2021-5-22

[8]
Usability of electronic health record systems in UK EDs.

Emerg Med J. 2021-6

[9]
Implementation of a Newborn Clinical Decision Support Software (NoviGuide) in a Rural District Hospital in Eastern Uganda: Feasibility and Acceptability Study.

JMIR Mhealth Uhealth. 2021-2-19

[10]
The use of data in resource limited settings to improve quality of care.

Semin Fetal Neonatal Med. 2021-2

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