Evaluating the NeoTree in Malawi and Zimbabwe
- Conditions
- PrematurityNeonatal SepsisNeonatal SeizureNeonatal HypothermiaNeonatal Respiratory FailureNeonatal EncephalopathyNeonatal HypoglycemiaNeonatal DeathNeonatal JaundiceNeonatal Disorder
- Interventions
- Device: Neotree
- Registration Number
- NCT05127070
- Lead Sponsor
- University College, London
- Brief Summary
Neonatal mortality remains unacceptably high. Globally, the majority of mothers now deliver in health facilities in low resource settings where quality of newborn care is poor. Health systems strengthening through digitial quality improvement systems, such as the Neotree, are a potential solution. The overarching aim of this study is to complete the co-development of NeoTree-gamma with key functionalities configured, operationalised, tested and ready for large scale roll out across low resource settings.
Specific study objectives are as follows:
1. To further develop and test the NeoTree at tertiary facilities in Malawi and Zimbabwe
2. To investigate HCPs and parent/carer view of the NeoTree, including how acceptable and usable HCWs find the app, and potential barriers and enablers to implementing/using it in practice.
3. To collect outcome data for newborns from representative sites where NeoTree is not implemented.
4. To test the clinical validity of key NeoTree diagnostic algorithms, e.g. neonatal sepsis and hypoxic ischaemic encephalopathy (HIE) against gold standard or best available standard diagnoses.
5. To add dashboards and data linkage to the functionality of the NeoTree
6. To develop and test proof of concept for communicating daily electronic medical records (EMR) using NeoTree
7. To initiate a multi-country network of newborn health care workers, policy makers and academics.
8. To estimate cost of implementing NeoTree at all sites and potential costs at scale
- Detailed Description
Every year 2.4 million newborn deaths occur worldwide. Up to 70% of newborn deaths are avoidable with implementation of standard-technology, evidence-based interventions. Health systems strengthening and education and training in newborn care are key to saving newborn lives. Implementation of evidence based interventions and guidelines can be supported through provision of reliable data systems, clinical decision support tools and education. Using open-source code and maintaining local data ownership the investigators have used iterative, human- and user-centered design methods and agile processes in software and data management development and design to develop the Neotree: a digital quality improvement system for postnatal facility-based care in low resource settings.
The Neotree aims to improve quality of care and newborn survival through combining data-capture, clinical decision-support, education in newborn care, and feedback of data to dashboards and national aggregate data systems. The investigators found the concept of device-enabled decision support to improve newborn care to be acceptable during workshops with healthcare professionals in Bangladesh (n\~15; 2014) and developed and delivered a prototype of the app. Following this, the investigators co-developed and piloted an early version of the NeoTree with Malawian Healthcare Professionals (HCPs) (n=46; 2016-2017), who reported it was easy to use and helped them deliver quality care.
The research project described in this protocol will enable the investigators to complete the co-development of the Neotree in Zimbabwe and Malawi and generate evidence for how to test it at scale.
Methods and analysis: Mixed methods (i) intervention co-development and optimisation, (ii) pilot implementation evaluation and (iii) economic evaluation study. The Neotree will be implemented in two hospitals in Zimbabwe, and one in Malawi. Clinical and demographic newborn data will be collected via the Neotree, in addition to behavioural science informed qualitative and quantitative implementation evaluation data, cost data, measures of quality newborn care and usability data over the 2-year study period. Six-months of newborn outcome data and cost data will be collected from 2 hospitals receiving usual care for comparison. Case-fatality rate data will inform sample size calculations and study design for a large scale roll out. Training manuals will be refined. Neotree clinical decision support algorithms will be optimised according to best available evidence and clinical validation studies.
Our overall vision is to use best practice and information technology to improve clinical decisions for newborn care and increase rates of newborn survival in under-resourced health care settings. In this study, the care for an estimated 15,000 babies across the three test sites will be impacted by the Neotree. Through successful rollout across Zimbabwe and Malawi - the care for nearly 300,000 babies could be improved annually.
Recruitment & Eligibility
- Status
- UNKNOWN
- Sex
- All
- Target Recruitment
- 19000
Not provided
Not provided
Study & Design
- Study Type
- OBSERVATIONAL
- Study Design
- Not specified
- Arm && Interventions
Group Intervention Description Neonatal admissions at Hospital sites where Neotree is implemented in Zimbabwe and Malawi Neotree The investigators will record routine clinical admission, discharge and microbiological data for all newborns admitted to the newborn care units using the NeoTree as a replacement to paper-based forms. Individual-level patient data will be collected on all neonates admitted for care at Sally Mugabe Central (Oct 2019 to April 2022) and Chinhoyi Provincial Hospitals (Oct 2020 to April 2022) Zimbabwe, and Kamuzu Central Hospital (Oct 2019 to April 2022), Malawi. Given typical admission rates, this equates to a sample size \~12,000 babies in Zimbabwe and \~ 4000 babies in Malawi. Data will be collected from February 2019 to the end of the study, to explore trends over time and also include measures of quality newborn care. Clinical validation sub-study Neotree The sample size for our diagnostic sub-study has been calculated using sepsis as the index diagnosis. Assuming sensitivity and specificity of 92% (lower 95% CI: 84%) \>222 babies would need to be diagnosed with sepsis over five months, during which \~\>2000 babies will be admitted with sepsis across sites (Sally Mugabe Central Hospital, Zimbabwe and Kamuzu Central Hospital, Malawi). If necessary, the investigators will continue to collect data throughout the duration of the study until our sample size is achieved. These data will be collected as part of the routine Neotree data collection.
- Primary Outcome Measures
Name Time Method Acceptability of the Neotree as a digital tool to improve neonatal care and survival using the Theoretical framework of acceptability (TFA) among newborn health care providers and parents/ families of sick/ vulnerable newborns. 2.5 years Qualitative data collected via semi-structured interviews and focus groups will be collected. Topic guides will be informed by the TFA in order to assess acceptability of the Neotree to be embedded into usual clinical care to improve care and outcomes for sick and vulnerable babies in low resource settings.
Quantitative Usability (Systems usability score) and qualitative usability of the Neotree and usage (percentage of admitted babies with Neotree admissions data) of the Neotree 2.5 years mplementation science evaluation of usability and usage of the Neotree to be for healthcare workers in low resource hospital settings in Malawi and Zimbabwe to optimise quality of care or newborns.
Feasibility of the Neotree as a digital tool to improve neonatal care and survival using the Theoretical domains framework (TDF) of feasibility among newborn health care providers and parents/ families of sick/ vulnerable newborns. 2.5 years mplementation science evaluation of feasibility of the Neotree to be embedded into Qualitative data collected via semi-structured interviews and focus groups will be collected. Topic guides will be informed by the TDF in order to assess feasibility of the Neotree to be embedded into usual clinical care to improve care and outcomes for sick and vulnerable babies in low resource settings.
- Secondary Outcome Measures
Name Time Method Facility based neonatal mortality and stillbirth birth rates overtime 1.5 years Overall deaths per 1000 live births and still birth rates in the 3 hospital units using the Neotree over time.
Cost of implementation 2.5 years Costs of implementation of the Neotree to 3 newborn care units, 2 in Zimbabwe and 1 in Malawi
Case fatality rates (deaths per 1000 babies admitted to newborn care unit) over time 2.5 years Case fatality rates of admitted babies to the 3 hospital units using the Neotree over time
5. number of babies with key diagnoses over time (e.g. prematurity, neonatal sepsis, neonatal encephalopathy) 2.5 years Number and outcome (death/discharge) for key diagnostic groups
Measures of quality of newborn care (aligned with WHO standards of quality newborn care) 2.5 years Quantiative measures of standards of quality newborn care measured using the Neotree data. in the 3 hospital facilities where it is implemented.
Trial Locations
- Locations (5)
Kamuzu Central Hospital
🇲🇼Lilongwe, Malawi
Chinhoyi Provincial Hospital
🇿🇼Chinhoyi, Zimbabwe
Bindura Provincial Hospital
🇿🇼Bindura, Zimbabwe
Sally Mugabe Central Hospital
🇿🇼Harare, Zimbabwe
Parirenyatwa Hospital
🇿🇼Harare, Zimbabwe