Data Utilization
Utilizing data for evidence-based decision-making
Effective decision-making around maternal, newborn, and child health (MNCH) policies and programs requires collaboration among various institutions and sectors, leveraging their data and expertise. Governments and their partners face numerous decisions on how to allocate limited health resources. While many countries possess valuable data from sources like household and health facility surveys, routine health information systems, and program monitoring and evaluation efforts, these data are often underutilized. This underutilization can be due to data being owned by different groups within and outside Ministries of Health, a lack of capacity among data owners to analyze and interpret the data, and data not being collected or disaggregated at levels useful for decision-making (Keita et. al., 2019).
Depending on the country context, key sources for MNCH data that could be used for programming include:
- Health Management Information System (HMIS).
- Systematic maternal death reviews, where implemented.
- MNCH quality of care checklists, where implemented.
- Lives Saved Tool (LiST).
What Are the Benefits of Stronger Data Utilization?
- Facilitates identification of gaps in MNCH programming.
- Supports a program design/re-design process based on evidence.
- Helps track progress and monitor the impact of interventions being implemented.
- Supports advocacy efforts towards supporting resource allocation and prioritization.
- Enables effective management of the family planning program.
How to Implement
1. Design/Refine the Local MNCH Program Based on Existing Evidence
- Conduct a landscaping and bottleneck analysis of the local MNCH program.
- Design/refine the local MNCH program, guided by the collected information. This should be led by the city MNCH program managers, with support from TCI.
- Determine indicators of interest to the program, data sources, and intended use.
- Devise expected level of achievements (ELAs) for each indicator relevant to the local MNCH program design.
2. Monitor the Implementation of the Local MNCH Program
- Collect relevant data as activities are implemented. The level of data collected depends on the program design and available resources for monitoring.
- If relevant, conduct TCI’s Data Quality Assessment (DQA) interventions to ensure high-quality monitoring data.
3. Conduct Local MNCH Program Meetings Where Data is Used to Guide Decisions
- Convene regular coordination meetings, with support from TCI. Key stakeholders could include city health officers, city MNCH program managers, finance officers, data officers, and facility focal points. In the meetings, they should discuss the activities done in the latest period and progress towards outcomes.
- Identify the gaps and areas for improvement. Create an action plan to address the gaps, with clear assignments and timelines.
- Review the progress towards the data action plan in the next meeting.
What's the Evidence?
Several resources support the positive impact of convening multiple stakeholders to use data for decision-making.Â
- Use of a multi-institutional approach in Mali (Keita, et al, 2019).
- Use of a five-step data-informed platform for health strategy in Ethiopia (Zenebe, et al, 2023).
- Exploring the use of data science (Akuze, et al, 2024).
Key Indicators
- Percentage of cities that used data to inform their local MNCH program design.
- Percentage of cities that track outcomes towards their MNCH indicators and ELAs.
- Percentage of cities conducting MNCH coordination meetings quarterly (or at the expected frequency).
- Percentage of cities that created an action plan based on data reviewed in the meetings.
- Percentage of cities that reviewed the status of the action plan in their following meeting
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Tips
- Data for decision-making should be applied at all levels of engagement – from designing the program, monitoring implementation, and creating action plans based on gaps/challenges identified.
- If there are existing local mechanisms that support data for decision-making, TCI should aim to strengthen those instead of creating new mechanisms.
- Ensure that the appropriate people are included in the feedback meetings so that decisions are made and action plans are followed through.
Challenges
- Lack of high-quality data that can support decision-making.
- Convening stakeholders to review the MNCH program, given competing priorities.
- Inadequate financial or human resources to address the programmatic gaps identified.
Key Resources
- Analysis and use of health facility data: guidance for maternal, newborn, child and adolescent health programme managers. WHO 2023
- Using MNCAH data for decision-making. WHO 2023
- MNCAH RHIS indicators: country mapping template. WHO 2023
- Digital health. WHO
- Digital Health Resources. Global Digital Health
