Clinical trial NCT05127070: Evaluating the NeoTree in Malawi and Zimbabwe
Official title: Evaluating the NeoTree: An eHealth Solution to Reduce Neonatal Mortality in Two Low Income Countries: Malawi and Zimbabwe
Study type: OBSERVATIONAL
Overall status: UNKNOWN
Conditions: Prematurity
Neonatal Encephalopathy
Neonatal Sepsis
Neonatal Death
Neonatal Seizure
Neonatal Jaundice
Neonatal Hypoglycemia
Neonatal Hypothermia
Neonatal Disorder
Neonatal Respiratory Failure
Lead sponsor: University College, London
Sponsor class: OTHER
Collaborators: name: Biomedical Research and Training Institute, Zimbabwe
name: PACHI Malawi - Parent and Child Health Initiative Trust
name: Ministry of Health and Child Welfare, Zimbabwe
First posted: 2021-11-19
Enrollment: 19000
Sex: ALL
Standard ages: CHILD
ADULT
OLDER_ADULT
Observational model: OTHER
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Group 1: Healthcare professionals and managers working in newborn care units in the 3 hospitals.

Group 2: Parents/ carers of babies admitted to the 3 hospital sites. Group 3: All neonates admitted to the hospital sites

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.

Eligibility criteria: Group 1: Healthcare professionals w

HCP will be recruited to the behaviour change and implementation science evaluation study at SMCH, KCH and CPH. Qualitative and quantitative methods will assess acceptability, feasibility and usability of the NeoTree. We estimate a sample size of 160 across sites addressing each aspect, and will carry out an assessment for data thematic saturation before conducting any further interviews (Sample size \~160). An additional 30 HCPs will be recruited to the health economic cost data.

Inclusion criteria:

* working as a healthcare professional or manager caring for newborns admitted to SMCH, KCH or CPH newborn care units during the study period
* Willing and able to give written or audio informed consent for participation.

Exclusion criteria:

● aged over 65 years (Zimbabwe only); No upper exclusion age in Malawi

Group 2: Parents/ carers

A qualitative study will be conducted with families and carers of newborns admitted to the intervention hospitals to assess acceptability of the NeoTree (Sample size \~30, followed by analysis for thematic saturation prior to carrying out further interviews).

Inclusion criteria:

* Parent/carer of a live newborn requiring admission to SMCH, KCH or CPH newborn care units during the study period
* Willing and able to give written or audio informed consent for participation.

Exclusion criteria:

● Parents aged under 18 years (Malawi) and under 16 years (Zimbabwe)

Group 3: Newborns admitted to newborn care units

Inclusion criteria:

* Anonymous individual data will be collected prospectively for all babies admitted to the newborn care units of SMCH, KCH and CPH until the end of the study (anticipated April 2022)
* anonymous individual data will be collected retrospectively for all babies admitted to newborn care units of Bindura Provincial Hospital and Parirenyatwa Hospital during April and October 2021 or beyond.

Exclusion criteria:

● none

Primary outcomes:
measure: 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.
timeFrame: 2.5 years
measure: 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.
timeFrame: 2.5 years
measure: Quantitative Usability (Systems usability score) and qualitative usability of the Neotree and usage (percentage of admitted babies with Neotree admissions data) of the Neotree
timeFrame: 2.5 years
Secondary outcomes:
measure: Cost of implementation
timeFrame: 2.5 years
measure: Case fatality rates (deaths per 1000 babies admitted to newborn care unit) over time
timeFrame: 2.5 years
measure: Facility based neonatal mortality and stillbirth birth rates overtime
timeFrame: 1.5 years
measure: Measures of quality of newborn care (aligned with WHO standards of quality newborn care)
timeFrame: 2.5 years
measure: 5. number of babies with key diagnoses over time (e.g. prematurity, neonatal sepsis, neonatal encephalopathy)
timeFrame: 2.5 years
Other outcomes:
Locations:
city: Lilongwe
country: Malawi
facility: Kamuzu Central Hospital
city: Bindura
country: Zimbabwe
facility: Bindura Provincial Hospital
city: Chinhoyi
country: Zimbabwe
facility: Chinhoyi Provincial Hospital
city: Harare
country: Zimbabwe
facility: Parirenyatwa Hospital
city: Harare
country: Zimbabwe
facility: Sally Mugabe Central Hospital
Study officials:
References:
citation: Crehan C, Kesler E, Chikomoni IA, Sun K, Dube Q, Lakhanpaul M, Heys M. Admissions to a Low-Resource Neonatal Unit in Malawi Using a Mobile App: Digital Perinatal Outcome Audit. JMIR Mhealth Uhealth. 2020 Oct 21;8(10):e16485. doi: 10.2196/16485.
citation: Crehan C, Kesler E, Nambiar B, Dube Q, Lufesi N, Giaccone M, Normand C, Azad K, Heys M. The NeoTree application: developing an integrated mHealth solution to improve quality of newborn care and survival in a district hospital in Malawi. BMJ Glob Health. 2019 Jan 16;4(1):e000860. doi: 10.1136/bmjgh-2018-000860. eCollection 2019.
citation: 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. BMJ Open. 2021 May 18;11(5):e042124. doi: 10.1136/bmjopen-2020-042124.
citation: Gannon H, Chimhuya S, Chimhini G, Neal SR, Shaw LP, Crehan C, Hull-Bailey T, Ferrand RA, Klein N, Sharland M, Cortina Borja M, Robertson V, Heys M, Fitzgerald FC. Electronic application to improve management of infections in low-income neonatal units: pilot implementation of the NeoTree beta app in a public sector hospital in Zimbabwe. BMJ Open Qual. 2021 Jan;10(1):e001043. doi: 10.1136/bmjoq-2020-001043.