Data analytics for better health system governance

Data analytics is essential to improving decision-making, optimizing resource use, and strengthening health systems. At Bluesquare, we help governments, donors, non-governmental organizations and health programmes — particularly in low- and middle-income countries — transform complex and scattered source of health systems data into actionable insights. Through our powerful digital platforms and expertise in data integration, we enable smarter planning and more effective public health interventions.

The challenge of health data quality

In public health, data comes from a wide array of sources: health information management systems (HMIS), surveys, health facility reporting disease surveillance platforms, and more. Each source has its own structure and format, creating challenges in terms of data quality, interoperability, and usability.

A significant challenge remains the integration of unstructured data—like PDFs, paper-based reports, or handwritten notes, to these central data repositories so they can be exploited and bring value. At Bluesquare, we facilitate digitization and harmonization through tools and standards that ensure interoperability with existing systems, such as DHIS2, the widely deployed HMIS in low- and middle-income countries.

Why data integration is key to health system strengthening

Health data integration means consolidating multiple sources into a unified data infrastructure —whether a data warehouse, platform — so that stakeholders can gain a comprehensive view of the health system thanks to key visualizations.

Read more about what we do with National Malaria Data Repositories.

With tools like IASO, OpenHexa and DHIS2 we support countries in (among others):

• Tracking disease outbreaks and vaccination coverage in near real-time.
• Monitoring financial flows and service delivery performance at health facility level.
• Identifying underserved areas through geospatial data analysis.
• Aligning donor reporting with national strategies.

Centralized and integrated data systems help reduce fragmentation, increase transparency, and accelerate evidence-based decision-making.

Three levels of healthcare data analytics

To improve health system performance, analytics must go beyond simple data collection. At Bluesquare, we help governments and organizations build capacity in three levels of analytics.

1. Descriptive analytics – Understanding the present

Descriptive analytics provides an overview of current and past trends. It enables stakeholders to assess service delivery, coverage gaps, disease incidence, and more.

We develop interactive dashboards, maps, and custom indicators to visualize key performance metrics. This helps ministries of health and donors to make informed decisions during planning and evaluation phases.

2. Predictive analytics – Anticipating future needs

Using historical data and statistical modeling, predictive analytics can identify patterns and forecast events — such as disease outbreaks or stock shortages.

Bluesquare helps integrate predictive models into national systems to support:

• Early warning systems for epidemic response.
• Forecasting resource needs based on service utilization trends.
• Planning future campaigns (e.g., seasonal malaria prevention).

However, predictive modeling depends heavily on the availability of high-quality, timely data — a gap we actively help our partners address. This is what has been done in the framework of MACEPA, a Bluesquare project in the Democratic Republic of Congo.

3. Prescriptive analytics – Guiding policy and action

Prescriptive analytics recommends specific interventions to improve outcomes. For example, it can suggest how to optimize resource allocation across regions based on disease burden and health facility capacity.

At Bluesquare, we work with governments to model different policy scenarios, helping them evaluate the impact and trade-offs of each decision. Our tools support results-based financing (RBF), enabling funders to link disbursements to performance metrics.

Learn more with this example of RBF project led by Bluesquare back in 2017.

From data to decision: building resilient health systems

Healthcare data analytics is not just a technical discipline — it is a strategic lever for health system governance. Whether improving financial accountability, strengthening health information systems, or supporting routine decision-making, Bluesquare empowers public health stakeholders to turn data into action.

Realizing the full potential of health data analytics requires:

• Investments in digital infrastructure.
• Commitment to data governance and ethics.
• Capacity building across ministries and local institutions.
• Collaborative ecosystems between data scientists, public health experts, and funders.

With the right tools and partnerships, healthcare analytics can lead to more resilient, equitable, and effective health systems.

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