PrematurityNCT05127070
Evaluating the NeoTree in Malawi and Zimbabwe
An observational study of Prematurity and Neonatal Encephalopathy, run by University College, London at 5 sites in 2 countries.
Trial 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. Read more about this study
- Who is it for?
- Any age
- Conditions the study is for
- Prematurity, Neonatal Encephalopathy, Neonatal Sepsis
- What is being tested?
- Neotree
- Type of treatment
- Medical device
- How many people
- 19,000 participants
- Where
- 5 sitesin 2 countries
- Study dates
- 1 Oct 2019to 1 Sep 2022
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages Any age
- All sexes
- Child, Adult, Older adult
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
Who may be able to join
- 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.
- 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.
- 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.
Who cannot join
- ● 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).
- ● Parents aged under 18 years (Malawi) and under 16 years (Zimbabwe)
- Group 3: Newborns admitted to newborn care units
- ● none
Trial locations and contacts
5 sites in 2 countries.
5 sites in 2 countries
Zimbabwe4 sites, 4 recruiting
- Recruiting
Bindura Provincial Hospital
Bindura
Simbarashe Chimhuya
- Recruiting
Chinhoyi Provincial Hospital
Chinhoyi
Simbarashe Chimhuya
- Recruiting
Parirenyatwa Hospital
Harare
- Recruiting
Sally Mugabe Central Hospital
Harare
Simbarashe Chimhuya
Malawi1 site, 1 recruiting
- Recruiting
Kamuzu Central Hospital
Lilongwe
Msandeni Chiume
About this study
Official title: Evaluating the NeoTree: An eHealth Solution to Reduce Neonatal Mortality in Two Low Income Countries: Malawi and Zimbabwe
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:
- To further develop and test the NeoTree at tertiary facilities in Malawi and Zimbabwe
- 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.
- To collect outcome data for newborns from representative sites where NeoTree is not implemented.
- 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.
- To add dashboards and data linkage to the functionality of the NeoTree
- To develop and test proof of concept for communicating daily electronic medical records (EMR) using NeoTree
- To initiate a multi-country network of newborn health care workers, policy makers and academics.
- To estimate cost of implementing NeoTree at all sites and potential costs at scale
Read the 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.
- Conditions
- Prematurity, Neonatal Encephalopathy, Neonatal Sepsis, Neonatal Death, Neonatal Seizure, Neonatal Jaundice
- Being tested
- Neotree
- Medical subject headings
- Premature Birth, Neonatal Sepsis, Perinatal Death, Jaundice, Neonatal, Infant, Newborn, Diseases
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
NeotreeDevice
The Neotree is a digital app, data collection and quality improvement system. collecting and collating routine health data at the bedside for babies on admission and discharge and for laboratory results. it provides point of care education and clinical decision support to optimise the clinical care of sick and vulnerable newborns according to approved and best available clinical guidelines.
| Study group | Role | What they receive |
|---|---|---|
| Behavioural science and implementation research | The investigators will recruit adult health care professionals, senior hospital managers and parents/carers of neonates. Approximate sample sizes in each country are as follows: Zimbabwe: ~80 Healthcare Professionals ; ~20 Carers/ parents of newborn babies and ~10 Hospital administrators/ managers. Malawi: ~40 Healthcare Professionals (~10 HCPs per focus group discussion); ~10 Carers/ parents of newborn babies and ~10 Hospital administrators/ managers. Total participants for new data collection: 180 (this number is likely to be much lower if there is limited staff turnover at neonatal units and if HCPs agree to participate in multiple research activities). | |
| Cost data | A time-use survey will be conducted with a small sample of Healthcare professionals at all 3 hospitals where the Neotree is implemented (sample size ~30) to measure time spent for different activities/procedures carried out on or for a patient. | |
| Neonatal admissions at Hospital sites where Neotree is implemented in Zimbabwe and Malawi | 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. Receives: Device: Neotree | |
| Comparative case-fatality rates in units using NeoTree and representative control sites | The investigators will collect outcome data from neonatal clinical records at two additional representative hospital sites in Zimbabwe over a 6 month period (sample size ~1200), to inform our sample size calculation for a full evaluation at scale in the future. Individual level data will be collected retrospectively from Bindura Provincial Hospital and Parirenyatwa Hospital (1/4/2021 to 01/10/2021 or beyond depending on sample size). | |
| Clinical validation sub-study | 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. Receives: Device: Neotree |
What is being measured
The primary outcome is the main question the study is designed to answer.
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.
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.
Measured: 2.5 years
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.
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.
Measured: 2.5 years
Quantitative Usability (Systems usability score) and qualitative usability of the Neotree and usage (percentage of admitted babies with Neotree admissions data) of the Neotree
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.
Measured: 2.5 years
Secondary outcomes (5)
Cost of implementation
Costs of implementation of the Neotree to 3 newborn care units, 2 in Zimbabwe and 1 in Malawi
Measured: 2.5 years
Case fatality rates (deaths per 1000 babies admitted to newborn care unit) over time
Case fatality rates of admitted babies to the 3 hospital units using the Neotree over time
Measured: 2.5 years
Facility based neonatal mortality and stillbirth birth rates overtime
Overall deaths per 1000 live births and still birth rates in the 3 hospital units using the Neotree over time.
Measured: 1.5 years
Measures of quality of newborn care (aligned with WHO standards of quality newborn care)
Quantiative measures of standards of quality newborn care measured using the Neotree data. in the 3 hospital facilities where it is implemented.
Measured: 2.5 years
5. number of babies with key diagnoses over time (e.g. prematurity, neonatal sepsis, neonatal encephalopathy)
Number and outcome (death/discharge) for key diagnostic groups
Measured: 2.5 years
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted19 Nov 2021
- Study start1 Oct 2019
- Primary completion1 Sep 2022 (estimated)
- Study completion1 Sep 2022 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (4)Papers the sponsor has linked to this study.
- Other trials for PrematurityStudies of the same condition, open and under way.
- More trials run by University College, LondonThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Other
- Time perspective
- Prospective
- Enrolment
- 19,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- University College, London
- Sponsor type
- University, hospital or other
- Collaborators
- Biomedical Research and Training Institute, Zimbabwe, PACHI Malawi - Parent and Child Health Initiative Trust, Ministry of Health and Child Welfare, Zimbabwe
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05127070
- Sponsor's protocol ID
- 17123/001
- Status last verified
- Oct 2021
- First submitted
- 21 Oct 2021
- Last updated
- 18 May 2022
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: We are planning to create and host an open data set from the clinical Neotree data. All Neotree code is open source on github.
Publications
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.
PubMed 33084581Crehan 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.
PubMed 30713745Evans 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.
PubMed 34006538Gannon 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.
PubMed 33472853
Study at a glance
From the registry record, last updated by the sponsor on 18 May 2022. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Evaluating the NeoTree: An eHealth Solution to Reduce Neonatal Mortality in Two Low Income Countries: Malawi and Zimbabwe
- ClinicalTrials.gov ID
- NCT05127070
- Acronym / sponsor ID
- 17123/001
- Conditions
- Prematurity, Neonatal Encephalopathy, Neonatal Sepsis, Neonatal Death, Neonatal Seizure, Neonatal Jaundice
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 19,000 participants (estimated)
- Lead sponsor
- University College, LondonUniversity, hospital or other
- Collaborators
- Biomedical Research and Training Institute, Zimbabwe, PACHI Malawi - Parent and Child Health Initiative Trust, Ministry of Health and Child Welfare, Zimbabwe
- Study start
- 1 Oct 2019 (actual)
- Primary completion
- 1 Sep 2022 (estimated)
- Study completion
- 1 Sep 2022 (estimated)
- First posted
- 19 Nov 2021 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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:
- To further develop and test the NeoTree at tertiary facilities in Malawi and Zimbabwe
- 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.
- To collect outcome data for newborns from representative sites where NeoTree is not implemented.
- 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.
- To add dashboards and data linkage to the functionality of the NeoTree
- To develop and test proof of concept for communicating daily electronic medical records (EMR) using NeoTree
- To initiate a multi-country network of newborn health care workers, policy makers and academics.
- 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.
Study design
- Observational model
- Other
- Time perspective
- Prospective
- Number of arms
- 5
| Arm | Type | Receives |
|---|---|---|
| Behavioural science and implementation research | – | –The investigators will recruit adult health care professionals, senior hospital managers and parents/carers of neonates. Approximate sample sizes in each country are as follows: Zimbabwe: ~80 Healthcare Professionals ; ~20 Carers/ parents of newborn babies and ~10 Hospital administrators/ managers. Malawi: ~40 Healthcare Professionals (~10 HCPs per focus group discussion); ~10 Carers/ parents of newborn babies and ~10 Hospital administrators/ managers. Total participants for new data collection: 180 (this number is likely to be much lower if there is limited staff turnover at neonatal units and if HCPs agree to participate in multiple research activities). |
| Cost data | – | –A time-use survey will be conducted with a small sample of Healthcare professionals at all 3 hospitals where the Neotree is implemented (sample size ~30) to measure time spent for different activities/procedures carried out on or for a patient. |
| Neonatal admissions at Hospital sites where Neotree is implemented in Zimbabwe and Malawi | – | Device: NeotreeThe 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. |
| Comparative case-fatality rates in units using NeoTree and representative control sites | – | –The investigators will collect outcome data from neonatal clinical records at two additional representative hospital sites in Zimbabwe over a 6 month period (sample size ~1200), to inform our sample size calculation for a full evaluation at scale in the future. Individual level data will be collected retrospectively from Bindura Provincial Hospital and Parirenyatwa Hospital (1/4/2021 to 01/10/2021 or beyond depending on sample size). |
| Clinical validation sub-study | – | Device: NeotreeThe 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. |
Who may qualify
- Sex
- All
- Age groups
- Child, Adult, Older adult
- 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
Key inclusion criteria (6 listed)
- 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.
- 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.
- 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)
Key exclusion criteria (6 listed)
- ● 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).
- ● Parents aged under 18 years (Malawi) and under 16 years (Zimbabwe)
- Group 3: Newborns admitted to newborn care units
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| NeotreeThe Neotree is a digital app, data collection and quality improvement system. collecting and collating routine health data at the bedside for babies on admission and discharge and for laboratory results. it provides point of care education and clinical decision support to optimise the clinical care of sick and vulnerable newborns according to approved and best available clinical guidelines. | Device | Clinical validation sub-study, Neonatal admissions at Hospital sites where Neotree is implemented in Zimbabwe and Malawi |
Primary outcome
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.
Time frame: 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.
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.
Time frame: 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.
Quantitative Usability (Systems usability score) and qualitative usability of the Neotree and usage (percentage of admitted babies with Neotree admissions data) of the Neotree
Time frame: 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.
5 secondary outcomes
Cost of implementation
Time frame: 2.5 years
Case fatality rates (deaths per 1000 babies admitted to newborn care unit) over time
Time frame: 2.5 years
Facility based neonatal mortality and stillbirth birth rates overtime
Time frame: 1.5 years
Measures of quality of newborn care (aligned with WHO standards of quality newborn care)
Time frame: 2.5 years
5. number of babies with key diagnoses over time (e.g. prematurity, neonatal sepsis, neonatal encephalopathy)
Time frame: 2.5 years
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 18 May 2022.
- Background: PubMed 33084581Crehan 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.
- Background: PubMed 30713745Crehan 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.
- Background: PubMed 34006538Evans 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.
- Results publication: PubMed 33472853Gannon 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.
- Neotree charity websiteLink provided by the sponsor.
- open source codeLink provided by the sponsor.
- Individual participant dataSharing planned: Yes. We are planning to create and host an open data set from the clinical Neotree data. All Neotree code is open source on github.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
5 sites in 2 countries: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Prematurity and Neonatal Encephalopathy, run by University College, London at 5 sites in 2 countries.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 6 inclusion and 6 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 18 May 2022. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 5 sites in Zimbabwe, Malawi. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Michelle Heys, MD(Res) (07541381106, m.heys@ucl.ac.uk), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome 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. (time frame: 2.5 years). The study lists 3 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT05127070, which also lists 4 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 18 May 2022.