Figures & Tables
Tables
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Seventeen Recipients of Small Grants Funded by MEASURE Evaluation Phase IV, 2015–2019
Research Organization Research Title Study Objective(s) Geographic Coverage Data Sources Integrated Health Initiative Integrating Family Planning Data from Public and Private Health Facilities in Malawi: How Current Approaches Align with FP2020 Goals12 Find approaches to improve the national Health Information System by integrating family planning data from private-sector service delivery points and government facilities 2 districts in each of the 3 regions in Malawi Desk reviews of all national policy documents guiding family planning data and data collection; field observations; 71 KIIs with staff from national-level institutions of the MOH, zonal offices of the 5 quality control divisions (i.e., zones) in Malawi, and family planning service providers, HMIS officers, health surveillance assistants, family planning coordinators, and data clerks Rivers State of Nigeria Primary Health Care Management Board Use of Technology to Manage Health Data in Rivers State, Nigeria: A Qualitative Study on Family Planning and Routine Health Information Systems13 Explore the experiences and perceptions of family planning providers and health information officers on implementing technology for district health data collection and identify factors that affect the sustainability of using technology for data management in Rivers State, Nigeria Rivers State, Nigeria 21 IDIs with state- and LGA-level HMIS officers, desk officers, monitoring and evaluation officers, and reproductive health coordinators; 2 FGDs with 35 facility health information officers and family planning providers Africa Field Epidemiologic Network Family Planning Indicators Assessment and Data Quality Audit in Selected Health Facilities Across Nigeria14 Estimate family planning indicator performance at the health facility level from the HMIS not reflected in DHIS2 to determine the quality of family planning data at the facility level and identify challenges to family planning program implementation in sampled health facilities in Nigeria 2 LGAs in each of the following 6 states in Nigeria: Bauchi, Delta, Enugu, Kano, Osun, and Nasarawa Administration of a questionnaire via interviews with 114 family planning/reproductive health focal people in selected facilities; 42 KIIs with family planning stakeholders and key decision makers in the family planning/reproductive health units at the LGA and state levels in the selected states; 6 FGDs with health workers/service providers The Rescue Initiative-South Sudan Analyzing, Interpreting, and Communicating Routine Family Planning Data in South Sudan15 Explore how effectively family planning data in the RHIS are analyzed, interpreted, and communicated, and discuss barriers to RHIS data use and ownership in 2 states in South Sudan 17 counties in 2 states in South Sudan: Central Equatoria and Western Equatoria Direct observation at service delivery points, individual questionnaires administered to health facility staff, and KIIs with a total of 180 study participants University of the Punjab, Institute of Social and Cultural Studies The Routine Health Information Systems in Punjab Province, Pakistan: Exploring the Potential for Integrating Health Information Systems for Family Planning Data16 Review the RHIS in Punjab province of Pakistan and explore the potential for integrating community-level data into the national HMIS, particularly family planning data, collected by public or private, for-profit, and not-for-profit organizations Punjab province, Pakistan Document review and 16 KIIs with lady health workers, the Population Welfare Dept., Rahnuma–Family Planning Association of Pakistan, DHIS office, United Nations Population Fund, and United Nations Children’s Fund Department of Population Studies, Makerere University Integrating Family Planning Data in Uganda’s Health Management Information System17 Investigate the facilitators, best practices, and barriers of integrating family planning data into the district and national HMIS in Uganda Kampala, Jinja, and Hoima districts, Uganda 16 KIIs with MOH officers, HMIS focal persons at nongovernmental organizations, HMIS focal persons who were district biostatisticians or medical records officers, and providers who were medical records officers at public and private health facilities; a multi-stakeholder dialogue workshop comprised of 11 participants; and a systematic review of the HMIS in sub-Saharan African countries that are United States Agency for International Development family planning priorities International Centre for Diarrhoeal Disease Research, Bangladesh Using DHIS 2 Software to Collect Health Data in Bangladesh18 Explore the perceptions and experiences with using DHIS2 to collect and analyze reproductive, newborn, maternal, and child health data in Bangladesh and to identify facilitators and barriers to using these data at different levels of the health care system Khulna and Chittagong districts in Bangladesh Document review; 23 IDIs with community health care providers, nurses, health inspectors, and upazila statisticians; 2 FGDs with district statisticians; and 11 KIIs with health managers, HMIS experts, and key decision makers Research and Development Division, Ghana Health Service Experiences and Perceptions of Health Staff on Applying Information Technology for District Health Data Management in Ghana19 Explore and document the experiences and perspectives of health staff and managers in the 4 districts on use of mobile technology to collect and manage health data in district health systems 4 administrative districts in Ghana’s Central Region KIIs with 160 frontline health staff (midwives, community health nurses, health information officers, general nurses, and physician assistants) at both the district and subdistrict levels and 14 district and regional health managers and policy makers Centre of Population, Health and Nutrition Services Improving Family Planning Service Delivery in Ghana20 Map out the distribution of all family planning service providers in the region and document how the community-based family planning information system is linked to the national system to recommend strategies for supporting program planning and implementation and improving family planning services Upper East Region, Ghana Records review and data extraction from DHIS2; survey of all types of service providers in the region’s 13 districts by interviewing the family planning providers present (435) using a structured interview questionnaire; 2 FGDs with the district health management team, staff from different subdistrict health teams, and community health officers Governance Links Tanzania Strengthening Tanzania’s Routine Health Information System: Incorporating Family Planning Quality Assessment Indicators21 Investigating the benefit of incorporating indicators related to family planning quality assessment in a decentralized RHIS in rural farming districts around Lake Victoria Administrative district of Magu, Mwanza Region, in the Lake Victoria zone of Tanzania Literature review; questionnaire-facilitated individual interviews with 50 health service providers and community health workers; 12 KIIs with health service providers, pharmacy staff, civil society organization staff, council health management team members, and district health information officers; 2 FGDs with 40 health service providers and community health workers Matibabu Foundation Integrating Family Planning Data in Kenya’s DHIS 222 Investigate integration of family planning data in DHIS2, the factors related to lack of integration, and ways to remedy the lack of integration Siaya and Nairobi counties, with a pretest conducted in Kisumu county in Kenya Eight KIIs with MOH officers from Siaya and Kisumu counties and a representative from the Division of Health Information Systems, at the national level. Four FGDs were conducted with clinicians, nurses, health records officers, and information officers from both public and private health facilities at all levels, from the primary level to county referral hospitals. Equitable Health Access Initiative The Strongest Motivators for Using Routine Health Information in Family Planning: A Prospective Study in Lagos, Nigeria23 Bridge the knowledge gap concerning the motivators behind using routine health information in family planning to improve the use of family planning services 3 LGAs of Lagos state, Nigeria 12 KIIs and 425 questionnaires with men and women working in the health sector Afya Research Africa Family Planning Services in Kenya During a Transition: Utilization Trends Across Counties24 Estimate the general prevalence of family planning use among women of childbearing age and the prevalence of family planning use by county; analyze the trends in family planning utilization over the period of transition, from 2012 to 2015; and estimate the extent to which counties had integrated reporting of family planning services in Kenya’s DHIS2 Kenya National family planning–related DHIS2 data and Kenya Demographic and Health Survey 2014 data Mzumbe University, School of Public Administration and Management Creating a Culture of Data Use in Tanzania: Assessing Health Providers’ Capacity to Analyze and Use Family Planning Data25 Understand health providers’ capacity to analyze collected family planning data and to document available evidence of health service providers using the collected data in theirplanning processes 2 LGAs within each of the following regions in Tanzania: Lindia, Geita, and Arusha 13 IDIs with facility in-charges, reproductive and child health in-charges, data clerks, and family planning facility-based providers; 2 FGDs with 24 health providers; and non-participant observation in 12 health facilities Health Promotion Tanzania Enhancing Use of Routine Health Information for Family Planning to Influence Decision Making in Tanzania26 Explore the type of family planning information collected, how the data are analyzed, and how the information informs planning and budgeting. It examined ways data are handled across all 5 levels of the health system (i.e., national, regional, district, ward, and village) and when and how the data are utilized. Kilimanjaro and Mara regions of Tanzania 31 KIIs with health officers in charge, points of contact for family planning or reproductive health and child health, district medicalofficers, health governance committee, HMIS focal people, and health secretaries from a regional hospital, district hospital, health center (ward level), and dispensary (village level) Association for Reproductive and Family Health Use of Routine Health Information to Inform Budgetary Allocation for Reproductive Health in Cross River State, Nigeria27 To understand the budget process within the state MOH and in the health department of the Calabar municipal local government council; examine the use of routine health information as evidence for budgetary allocation for reproductive health and family planning; identify barriers and constraints to routine data use; explore possible solutions; and dialogue with the stakeholders on how routine health data can be used in the budget process Calabar Municipal LGA in Cross River state, Nigeria Desk review of existing family planning data in Cross River State and Calabar Municipal LGA, KIIs with staff from relevant ministries, and questionnaires administered to middle- and junior-level officers at the state and LGA levels Access Global Ltd. Uganda’s Resources to Finance Family Planning Commodities: Implications for a Total Market Approach29 Understand the extent to which in-country resources can mitigate financing shortages for family planning commodities in Uganda, and the implications of a total market approach Uganda Literature review; retail audits in 16 pharmacies in Mukono district; and 6 researcher-administered questionnaires with family planning program managers Abbreviations: DHIS, District Health Information Software; FGD, focus group discussion; HMIS, health management information system; IDI, in-depth interview; KII, key informant interview; LGA, local government area; MOH, ministry of health; RHIS, routine health information system.
