HDA

This fellowship will inform the next phase of technological and data analytical innovations/inventions to expand on the MSDAT platform for improved healthcare delivery and health system’s monitoring in Nigeria. The objectives of the HDA fellowship are to:

• Build local capacity for research in health data analytics
• Support the development of health data platforms, specifically the MSDAT
• Improve the utilization of the MSDAT platform
• Use findings to inform Health Information Systems (HIS) policy development
• Facilitate the publication of research reports in recognized journals

Applicants are encouraged to go through the MSDAT platform: msdat.fmohconnect.gov.ng 

We believe that with an improvement on the MSDAT platform, decision-makers and stakeholders alike would have the tools they need for evidence-based decisions, reducing avenues for assumptions resulting from the lack of data in healthcare delivery and service. The ultimate goal is that we achieve universal health coverage and that there is an improvement in the quality of life of Nigerian citizens.

The benefits of this fellowship include: 

• ₦2,000,000.00 (per fellow) for postgraduate research (including research expenses e.g. equipment, data collection etc) 
• Capacity building in research and health data analytics
• Possible job opportunities with eHealth4everyone on completion of the fellowship
• Access to a network of individuals with shared interests
• Mentorship and support from the administering body. This would translate into the provision of reviews and guidance during the course of their research.
• Provision of datasets on request. 

Graduates:
To be eligible for this fellowship, the individual must fulfill the following requirements;

1. Must hold an acceptable form of Identification (i.e. an International passport; Drivers’ license; Voters’ Card, National Identity Number (NIN) card).
2. Must be a postgraduate student of any accredited University with a valid means of identification.
3. Candidates should hold a Bachelor’s degree or its equivalent for Master’s students, and a Master’s degree for PhD students.
4. Research should support the development and expansion of existing health data analytic platforms, such as the Multi-Source Data Analytics and Triangulation (MSDAT) platform.
5. The research will prioritise secondary data and goals should be targeted towards improving Nigerian health data and data systems around the following key areas:

• • Health Inputs
  • Health outcomes
  • Health financing
  • Health Workforce
  • Population and demographics
  • Health facility service availability and readiness
  • Service delivery
  • Health Impact
  • Health surveillance

The research goals can be pursued using any of the following approaches;

• • Data Management
  • Visual Analytics
  • Data Mining
  • Data Integration
  • Advanced Analytics
  • Open Data Advocacy
  • Big Data for health
  • Data Demand and use
  • Statistical Modeling of Health Data
  • Health Information System Interoperability
  • Artificial Intelligence
  • Machine learning

HDAFMDA (Health Data Analytics for Ministries, Departments and Agencies):
Applicants must meet the following criteria to become a fellow:

1. At least a Bachelor’s degree in Medicine, Public Health, Data Science, Statistics, Computer science or any related discipline. Five (5) years of experience working with health data will be considered an equivalent.
2. Document(s) confirming their appointment as a staff of the FMoH or partner agency.
3. A letter of attestation from the director of the applicant’s department.
4. Evidence of prior experience in conducting research is an added advantage.
5. Research should support the development and expansion of existing health data analytic platforms, such as the Multi-Source Data Analytics and Triangulation (MSDAT) platform.
6. The research will prioritise secondary data and goals should be targeted towards improving Nigerian health data and data systems around the following key areas:

• • Health Inputs
  • Health outcomes
  • Health Financing
  • Health Workforce
  • Population and Demographics
  • Health facility service availability and readiness
  • Service delivery
  • Health Impact
  • Health surveillance

The research goals can be pursued using any of the following approaches;

• • Data Management
  • Visual Analytics
  • Data Mining
  • Data Integration
  • Advanced analytics
  • Open data advocacy
  • Big Data for health
  • Data demand and use
  • Statistical modeling of health data
  • Health Information System Interoperability
  • Artificial Intelligence
  • Machine learning

How to apply for the fellowship:

Please read the eligibility section above carefully before applying

1. Carefully complete each section of the HDA fellowship form(s) and attach the required documents. These include:
   • • Official transcripts from Academic Institution,
     • Curriculum Vitae (CVs)
     • Admission letters, 
     • Statement of purpose (maximum of 500 words), 
     • Research proposal/summary including timelines for execution, 
     • Letter of recommendation from Supervisor, Head of Department or Dean;
     • A previously published paper, if available. This would be an added advantage.
2. A 2-minute video of the applicant explaining their research proposal and motivation, is required.
3. The HDA fellowship committee will carefully review each proposal and make a final decision. If successful, applicants would be notified (within 8 weeks after the application deadline) that they have been selected to receive the research grant. 
4. Successful applicants must officially “accept” the offer via an email within a week.

Please note: Funds are to be used for the research work ONLY. Funds would possibly cover textbooks, equipment, publications, and travels (for data collection activities etc). Costs that are indirectly related to the research would need to be approved by the HDA fellowship committee. 

In addition, results from all HDA funded research will be completely open for use by the eHealth for Everyone Foundation and others. There will be no copyrighting of research.