Qualitative Data Collection Consultant, Malawi
Data.FI COVID-19 Learning Agenda, Malawi
Data for Implementation (Data.FI) is a five-year global project funded by the U.S. President’s Emergency Plan for AIDS Relief (PEPFAR) and the U.S. Agency for International Development (USAID), whose goal is to accelerate and sustain access to high-quality data to expedite HIV epidemic control and maintenance. Data.FI is led by Palladium, in partnership with JSI Research & Training Institute; Johns Hopkins University, Department of Epidemiology; Right to Care; Cooper/Smith; IMC Worldwide; Jembi Health Systems; and macro-Eyes.
Data.FI, in collaboration with the Digital Health Division of the Malawi Ministry of Health, developed a capacity building plan using a change management approach based on findings from the Malawi COVID-19 eVaccine Registry Desk Review Report. This capacity building plan is being implemented to support the transition from paper to digital data collection systems (through the DHIS2 eVaccine Registry module) by developing a set of contextualized capacity strengthening tools for COVID-19 vaccine reporting processes.
To draw lessons learned from this activity, USAID/Washington has asked Data.FI to conduct an assessment that will document Data.FI and the Ministry of Health’s COVID-19 digital data capture interventions in Malawi and to better understand how these activities contributed towards strengthening the digital health enabling environment, as it pertains to the workforce and leadership and governance eHealth building blocks; and to what extent and how USAID investments leveraged existing global goods.
To this end, Data.FI is hiring a qualitative data collection consultant to conduct up to 20 semi-structured interviews with key stakeholders in Malawi at the facility, district, and national level.
The national- and district-level interviews will examine respondent impressions of COVID-19 vaccine digital data entry and data capture; to what extent they may have seen changes in the completeness and timeliness of COVID-19 vaccination data as a result of Data.FI activities; and what they see as the future of digital data capture for COVID-19 vaccination data in Malawi.
District-level interviews will also seek to understand respondents’ impressions of the acceptability (willingness of people and the organization to use the immunization data collection system) of COVID-19 data capture.
The district- and facility-level interviews will aim to understand how vaccine data capture happens in practice following the introduction of the eVaccine Registry; the ways in which the system has been strengthened or modified for COVID-19 vaccine data management; and the challenges and barriers to optimal collection, analysis, sharing, and use of high-quality vaccine data.
Data.FI would like to engage a data collection consultant who resides in Malawi, and ideally in Lilongwe. The responsibilities of the Consultant include the following:
- Review the research protocol, refine or revise it as needed, based on ethics committee reviews or changes in research logistics or sampling
- Liaise with Malawi National Health Sciences Research Committee formally identify any changes to research protocol and its timeline
- Organize research logistics including travel and scheduling interviews with up to 4 national level MOH officials, up to 4 district level health officials and up to 12 facility level staff members in at two districts over a two week period
- Secure authorization and introductory letters to appropriate authorities to proceed with data collection
Keep in-country co-investigators informed on study progress
- Lead up to 20 interviews and take detailed notes to share preliminary findings
- Work closely with supervisor to jointly identify key themes from interviews and analyze interview transcripts
- Write summaries of themes based on jointly developed codebook
- Be in regular contact with Palladium staff and hold debriefing sessions with Palladium staff
- Chichewa and English language skills
- Experience working with clinical and community health information systems and an understanding of Malawi’s ministry of health data reporting processes from facility to national level
- Experience successfully communicating with the Malawi National Health Sciences Research Committee revising research protocols
- Familiarity with the Malawian health context
- Extensive experience and demonstrated skills in conducting semi-structured interviews with respondents at multiple levels – both health facility level staff and high level government officials, including ability to ask detailed follow up questions (“probing”)
- Demonstrated qualitative analysis experience
- Strong interpersonal skills
- Ability to travel throughout Malawi
- Demonstrated ability to work with a remote supervisor and colleagues
Period of Performance
The period of performance is March 1, 2023, to June 30, 2023 with a two week data collection period anticipated in early April.
The estimated number of days of LOE for this scope is between 25- 30 days (including 10 days of data collection). The deliverables are as follows:
- Orientation on final protocol and KII guides
- Secure authorization and introductory letters from appropriate authorities and organize data collection logistics
- Keep in-country co-investigators informed of study progress and solicit input from them, as needed
- Conduct KIIs with national, district, and facility level stakeholders, capture high level notes and summarize preliminary findings
- Share completed audio recordings and notes of all interviews. Includes summary of interviewees names, titles, organizations, length of interview, as well as high level findings and any memorable quotes (from interview notes), and some initial suggested codes.
- Translation of memorable quotes from Chichewa to English as necessary.
- Jointly develop codebook with Data.FI staff members based on summary of key themes (English)
- Code sub-set of transcripts, using jointly developed codebook
- Support development of presentation with key findings from KIIs
- Review manuscript summarizing key findings