Notice F0: Reference implementation of the World Health Organization Antenatal Care Digital Adaption Kit

BornFyne-Prenatal Management System

Two-sentence Overview: 

Achieving universal health coverage requires digital technologies that can transform the way health data is collected and used and contribute to more equitable, rights-based health policies and primary health care services for pregnant women. This project will help expand the functionalities of the BornFyne-prenatal mangement system's antenatal care feature which is a two-way interactive platform. The BornFyne-antenatal care feature was designed adapting components of the WHO focused antenatal care package. The platform currently uses a strafication system to flags high risk pregnancy during antnatal care visits. This project will enable an expansion of these features and the functionality by incoporating components of the WHO digital adaptation kit for antenatal care.BornFyne project is being implemented by Denis and Lenora Foretia Foundation Cameroon in collaboration with University of Ottawa in Cameroon and Zambia and has the epertise and capacity to deliver.

Executive Summary: 

BornFyne is a Grand Challenges Canada funded innovation tested in Bali health district in Cameroon in 2018-2019. BornFyne is an interactive mobile application connected to a real time web portal called the prenatal management system (PNMS). The BornFyne user interface (used at household and for women) is made up of 6 features that is connected to the PNMS(at health facility level). Four online features and two offline features (family planning and medical advisory features for COVID19 messages). The offline features are designed purposely for health promotion. The four online features namely, antenatal care, pain, emergency and postnatal are interactive online features connected from the user interface to the health facility (providers) which is the PNMS. The BornFyne-PNMS supports the delivery of clinical care at primary care level, district hospitals and facilitates referrals to regional hospitals. It supports the health system and ability to respond, track and monitor health facilities, providers, districts, and regional activities. It collects timely data during antenatal care. PNMS uses a decision tree system that automatically flags and allow early detection of high-risk pregnancies and facilitates referrals for early pregnancy and inform the district where clusters of health issues may be located for district follow up. This process enables health care providers to take timely actions in saving lives.

The antenatal care package within the PNMS was initially designed adapting from the WHO focused antenatal care package. Each woman has a unique identifier number on the platform, and socio-demographic data is collected for each women using an equity lens which enable highly disaggregated electronic medical data to be collected for each pregnant woman from antenatal care visits to post natal. The system is set up to collect such wide range of data during antenatal care visit to enable the decision free system stratification to activate high risk pregnancy for immediate and continuous follow up. Currently, the BornFyne-PNMS platform has up to 40% of the features and elements that are listed in the WHO DAK tool across the 8 components. However, some of the existing elements are not currently coded using the same code name as used in the WHO DAK. Forexample, currently the BornFyne-PNMS collects detailed data only during ANC 1, meanwhile the WHO DAK tool requires continuous detail data collection for each ANC visit. This funding will enable us to adapt the codes to align with the WHO DAK code names and also facilitate expansion of this workflow and stratification system to incorporate the additional and detailed components of the WHO DAK and testing of these additional components in four districts in Cameroon and one district in Zambia.

Based on the current stratification system in the BornFyne-PNMS platform, Of the 140 pregnant women that were enrolled for antenatal care visits in the proof-of concept phase, up to 80% were identified as high-risk pregnancy and required follow up to ensure successful birth delivery. BornFyne is an open-source technology, and the team is made up of multi-disciplinary team of experts such as epidemiologist, biostatisticians, and public health expert, global health expert in maternal and newborn child health, software developer, health information systems, medical doctors and midwives. 

Consortium team: 

Denis and Lenora Foretia Foundation established since 2012 in Cameroon is a non-for-profit organization that seeks to catalyse Africa’s economic transformation by focusing on social entrepreneurship, science and technology, innovation, public health and progressive policies that create economic opportunities for all. The Nkafu Policy Institute of the Denis and Lenora Foretia Foundation is an independent Think Tank made up of experts from various background with experience in implementing projects to empower women and innovative entrepreneur projects to support small businesses and empower women. The BornFyne team is composed of medical anthropologist, epidemiologist, health economist, medical doctors, district medical officers and Master students. The Denis and Lenora Foretia Foundation is collaborating with University of Ottawa to implement the BornFyne project. University of Ottawa is the founding organization of the BornFyne project and the team at the University of Ottawa Canada continue to support capacity building in research and innovation for maternal and child health as the project transition towards country ownership. From the onset of the project, the team at University of Ottawa alongside the D &L Foretia foundation collaborated with the Ministry of Public Health Cameroon. The district health team is a relevant stakeholder in the configuration and testing process, thus all the district medical officers for the four districts that we planned to test in Cameroon and one district in Zambia are members of the team. The University of Zambia School of Epidemiology and Public Health supports research activities in Zambia in collaboration with D & L Foretia Foundation and, Women in Global Health Zambian Chapter supports advocacy and knowledge translation. The team at D&L Foretia Foundation presented the BornFyne project to Ministry of Health Zambia in 20020 and currently the team is collaborating with the district medical officer for Mumbwa district through the support from Ministry of Health Zambia. SPRL Donwel Systems is the software developer organization from the onset of the project and also a founding organization of the innovation and has a team that is engaged on continuous development of BornFyne based on user feedback and context. The Centre International de Recherches, d'Enseignements et de Soins (CIRES) Cameroon supports in contextualizing the innovation the two French districts in Cameroon.

Project Description: 

Project Description

  • Cameroon and Zambia are lower-middle income countries with a relatively high maternal mortality rate (MMR) and low uptake of up to 4 ANC visits. Quality of reproductive maternal and childcare is relatively poor. The existing district health information system (DHIS2) system in both countries is not reliable and collects limited data for antenatal care. This data is collected in aggregated form which is more useful for public health decision making and less useful for clinical decision making during antenatal care visits. In addition, the quality of the data is questionable. The COVID-19 pandemic is a perfect storm that has highlighted the dire need for transforming paper collected data into digital platform across sub–Saharan Africa. BornFyne PNMS compliments the DHIS2 in generating highly disaggregated data for clinical and public health decision making. Generating quality, highly disaggregated, and comprehensive data is relevant in understanding the health needs of poor and vulnerable populations, program design, and policies. It helps to inform investment and public health decisions and in measuring progress towards the SDGs and universal health coverage.

    BornFyne is an ongoing project, currently the team is working on other offline features that uniquely addresses inequities of literacy in using digital technology by using graphics to connect and communicate with providers. This BornFyne feature supports health promotion activities in the community by empowering households and rural women with continuous educational health promotion messages on COVID19 and family planning awareness in making informed choices. These health promotional offline features is currently being tested in Bangem(Cameroon) and Mumbwa(Zambia)districts. The innovation uses prompts and cues to trigger behavior change and persuade change using both the user interface and the web-based interface. Audio messages for family planning are uploaded in various local dialects. These audio messages are developed using gender-based analysis approach and behavioral change model and revised as needed according to each community's need.

    In both countries, RMNCH records are still collected on paper and the district health information system (DHIS2) that collects routine surveillance data also has limitations –it only generates aggregated data for public health decision making. PNMS collects individual data for the same RMNCH variables including additional data like socio demographic to support both public and clinical care decision making. DHIS2 only provides the health areas, health facilities and various indicators in aggregate form.

Key objectives of the study

  • Expansion of the current PNMS antenatal care feature workflow to incoporate components of the WHO DAK that are not yet embeded within the PNMS
  • Configure and align the additional elements within the PNMS work flow 
  • Contextulaized the components of DAK and identify gaps and limitations within the context
  • Assess potential interopability with the DHIS2 system
  • Improved and strengthened the capacity of district health services and health facilities in delivering innovative, accountable, quality, data driven RMNACH for women and adolescent girls, marginalized and most vulnerable population in targeted districts in Cameroon and Zambia using the expanded workflow for antenatal care within the PNMS platform 
  • Improve the quality and speed of the health response to pregnant women requiring urgent care

Monitoring and Evaluaiton: Collect data before-and-after comparison amongst health facilities to assess the expanded components and during trianing of providers.In addition to stakeholder consultations.

Deliverables: This will include;

1. Testing of the expanded version of the PNMS antenatal care feature in line with the DAK components

2.Develop content and training manuals

3.Train providers on the additional components and generate reports on antenatal care

4.Publications, webinars and blogs

Timelines: 

March to May 2022--configure the platform incoporating additional DAK components

April-May 2022 Develop content and training manuals

June-August 2022 training and testing of the expanded DAK antenatal care components within the PNMS

July 2022 to February 2023-Data entry, data collection,analysis and reporting

Risk and Mitigation

Management of change: During our proof-of-concept, we observed challenges amongst some health care providers on using electronic records, especially from the onset of the implementation. However, their feedback revealed that constant follow-up training and supervision support greatly improved on their ability to use the services and get famililarized with the platform.

Data privacy-there is always a risk in electronic medical records on data privacy, however, the PNMS platform is password protected and each patient has a unique identifier. 

 

Application Status: 
Pending Review & Investment

Comments

The full proposal needs to clarify: 
- What will be the license for the tool? 
- What are the prospects for the tool to be deployed in more countries and 
- how you are planning on aligning to shelf readiness principles. Also clearly indicate activities around alignment to Instant OpenHIE platform