1599 Usability-focused development of a neonatal feedback dashboard for a low-resource neonatal unit, Malawi

Crehan, Caroline; Mgusha, Yamikani; Hull-Bailey, Tim; Normand, Charles; Shair, Farah; Lorencatto, Fabiana; Chiume-Kayuni, Msandeni; Sassoon, Yali; Fitzgerald, Felicity; Lakhanpaul, Monica; Heys, Michelle

doi:10.1136/archdischild-2021-rcpch.739

Cited by 2 publications

(12 citation statements)

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“…Extraction of data via the data dashboard was also password protected, only accessible to account holders. The author (CC) developed the dashboard iteratively with the KCH paediatric department during the first 6 months of this study timeline ( 25 ), accessing and providing data for initial M&M meetings, supported by a data analyst (FS) and the NeoTree technical team. The author (YM) also had access to the power BI data dashboard by month 7, where she could drill down through the data and download monthly reports.…”

Section: Methodsmentioning

confidence: 99%

“…Since the ZCH pilot ( 21 ), the NeoTree has been iteratively co-developed, implemented, and evaluated at Sally Mugabe Central Hospital, Zimbabwe (from October 2018) ( 22 , 23 ), KCH (from April 2019) ( 21 , 24 ) and in Chinhoyi Provincial Hospital, Zimbabwe (from November 2020). During the implementation at KCH, a dashboard prototype was developed to visualise data on a screen on the neonatal unit and provide a monthly slide deck of morbidity and mortality (M&M) data ( 25 ). Development and maintenance of the NeoTree android app have been a collaborative, end-user, and data-driven effort, employing open-source code while maintaining patient confidentiality, therefore aligning with the principles of digital development ( 26 ).…”

Section: Introductionmentioning

confidence: 99%

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

Mgusha

Nkhoma

Chiume

et al. 2021

Front. Digit. Health

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Introduction: Understanding the extent and cause of high neonatal deaths rates in Sub-Saharan Africa is a challenge, especially in the presence of poor-quality and inaccurate data. The NeoTree digital data capture and quality improvement system has been live at Kamuzu Central Hospital, Neonatal Unit, Malawi, since April 2019.Objective: To describe patterns of admissions and outcomes in babies admitted to a Malawian neonatal unit over a 1-year period via a prototype data dashboard.Methods: Data were collected prospectively at the point of care, using the NeoTree app, which includes digital admission and outcome forms containing embedded clinical decision and management support and education in newborn care according to evidence-based guidelines. Data were exported and visualised using Microsoft Power BI. Descriptive and inferential analysis statistics were executed using R.Results: Data collected via NeoTree were 100% for all mandatory fields and, on average, 96% complete across all fields. Coverage of admissions, discharges, and deaths was 97, 99, and 91%, respectively, when compared with the ward logbook. A total of 2,732 neonates were admitted and 2,413 (88.3%) had an electronic outcome recorded: 1,899 (78.7%) were discharged alive, 12 (0.5%) were referred to another hospital, 10 (0.4%) absconded, and 492 (20%) babies died. The overall case fatality rate (CFR) was 204/1,000 admissions. Babies who were premature, low birth weight, out born, or hypothermic on admission, and had significantly higher CFR. Lead causes of death were prematurity with respiratory distress (n = 252, 51%), neonatal sepsis (n = 116, 23%), and neonatal encephalopathy (n = 80, 16%). The most common perceived modifiable factors in death were inadequate monitoring of vital signs and suboptimal management of sepsis. Two hundred and two (8.1%) neonates were HIV exposed, of whom a third [59 (29.2%)] did not receive prophylactic nevirapine, hence vulnerable to vertical infection.Conclusion: A digital data capture and quality improvement system was successfully deployed in a low resource neonatal unit with high (1 in 5) mortality rates providing and visualising reliable, timely, and complete data describing patterns, risk factors, and modifiable causes of newborn mortality. Key targets for quality improvement were identified. Future research will explore the impact of the NeoTree on quality of care and newborn survival.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Mgusha

Nkhoma

Chiume

et al. 2021

Front. Digit. Health

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“…41 A third targeted QI screen for improving key clinical indicators (eg, admission hypothermia) has been prototyped and piloted pending implementation in the future. 38 The automated delivery of morbidity mortality data to local multi-disciplinary teams is crucial for clinical F I G U R E 3 Data dashboard development, Kamuzu Central Hospital, Malawi: Moves units from hand-drawn, time consuming, unreliable and unclear data charts to clear, dynamic digital displays of meaningful data insights and driving impactful interventions (eg, hypothermia highlighted in lower right dashboard) 38 decision-making, resource management, and the monitoring of quality care and standards. However, recent data from the WHO quality of care network show only 17 of 47 countries in the Africa Region undertake these audits.…”

Section: How the Neotree System Aims To Improve Clinical Carementioning

confidence: 99%

“…Second, evidence‐based clinical decision and management support is provided at the bedside with embedded educational messaging, including dynamic configurability to reflect the needs and capacity of the particular healthcare setting. Third, data are visualised through dashboards (Figure 3) operationalising audit and feedback 38 . Data dashboards use raspberry pi, a low‐cost computer, linked to screens and an open‐source data visualisation software (Metabase).…”

Section: The Neotree: Descriptionmentioning

confidence: 99%

“…Figure3shows data visualisations from the Malawian data dashboard prototype co-developed with Malawian healthcare professionals, incorporating evidence-based audit and feedback features 38. An open-source development process means the software can be easily adopted by hospitals/governments who can then tailor data input fields locally without needing remote software support or creating commercial dependencies.36 In terms of open data curation and management, for example, we work in partnership with the Zimbabwean Ministry of Health and Child Care Electronic Health Records team to ensure seamless integration of Neotree data into the…”

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confidence: 99%

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

Heys

Kesler

Sassoon³

et al. 2022

Learning Health Systems

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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-ofthe-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.Msandeni Esther Chiume and Simbarashe Chimhuya are joint last authors.

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1599 Usability-focused development of a neonatal feedback dashboard for a low-resource neonatal unit, Malawi

Cited by 2 publications

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

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

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

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