Bringing the power of data warehouses and business intelligence tools to DHIS2

This abstract has been accepted at the 2024 DHIS2 Annual Conference

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session link: Novel And Cutting Edge Analytics Use Cases

Bringing the power of data warehouses and business intelligence tools to DHIS2

Domains: Vital health information – population trends, patient details, resource allocation – are trapped in isolated islands, unable to communicate. That’s the reality of many healthcare systems today, where fragmented data hinders progress towards the UNiversal Health Coverage (UHC). While there is more and more data, its true potential remains locked away, by the lack of seamless integration between subsystems. Custom connectors, while initially implemented to bridge these gaps, have proven to be both cumbersome and financially unsustainable. The challenge isn’t a lack of information, but harnessing its collective power. Integrating these disparate sources is crucial to gain a holistic view of system performance, improve data accessibility, and derive meaningful insights and metrics. Innovative solutions are emerging to break down these data silos, fostering seamless communication and unlocking the vast potential within. By investing in data integration tools and standardized formats, we can bridge the gaps and empower informed decision-making. Analytics & Data Quality: The wealth of available data holds immense potential to drive informed decision-making and refine interventions for better patient outcomes. The challenge extends beyond data integration and analysis, encompassing the dissemination of insights to the appropriate audience. This requires a nuanced understanding of stakeholders’ data needs, working environments, and levels of data literacy. BI solutions must prioritize user-centric design, offering intuitive interfaces and customizable dashboards tailored to diverse stakeholders’ needs. Additionally, investing in data literacy initiatives can empower decision-makers to interpret and act upon BI insights, fostering a culture of evidence-based decision-making throughout the healthcare hierarchy.decision-making and refine interventions for better patient outcomes. Interoperability & Integration: In the context of fragmented health information systems, the integration of multiple data sources through a data warehousing approach serves as a pivotal solution to unify disparate information. BAO Systems has designed an integration platform to ease the consolidation of diverse datasets, such as those from Integrated Human Resources Information Systems (IHRIS), Logistics Management Information Systems (LMIS),DHIS2, surveys, and World Population data, into a centralized repository. Our tool, the BAO Analytics Platform (AP), breaks down data silos by providing a single, comprehensive source of truth for healthcare data. By harmonizing data from various sources within a structured framework, stakeholders gain access to a holistic view of health system performance. Moreover, integrated data facilitates sophisticated analyses, enabling informed decision-making and targeted interventions to improve healthcare delivery and patient outcomes. Health Information Systems (HIS) play a crucial role in driving evidence-based decision-making towards Universal Health Coverage. Drawing on the experiences of DRC, Senegal, and Rwanda, common requirements and specificities in HIS integration are identified. BAO Systems proposes a platform approach to support country data integration needs in order to support the UHC strategies, promoting data use by designing customizable dashboards tailored to diverse stakeholders needs. Central to this approach is the integration into DHIS 2 of the data integration and analytics platform called the BAO Analytics Platform (AP) together with the SuperSet business intelligence tool. The AP offers the possibility to ingest and integrate data in real time from multiple and varied data sources together into a scalable data warehouse. The AP provides turn-key and easy-to-use connectors for information systems, platforms and tools commonly used by LMIC governments and health and development organizations supporting them, including DHIS2, CommCare, ODK, Kobo, iHRIS, BHIMA and others. Data in the AP are available for advanced analytics, machine learning and predictive analytics, as well as widespread sharing using popular third party business intelligence (“BI”) tools. The Analytics Platform offers a user-friendly interface and seamless flow from data ingestion to visualization, so that organizations can reduce staff time spent on curating, managing, and manipulating data, and instead focus on generating actionable insights from their data to inform programmatic decision making. We have developed a custom DHIS2 app called the Super BI app that seamlessly integrates Superset dashboards, empowering users to access and explore data insights directly within the familiar DHIS2 interface. The Super BI app simplifies navigation, allows for applying filters, and facilitates deeper data exploration from integrated data sources. This enables the creation of standardized analytics and visuals on integrated data sources, supporting decision-making at the district level. Examples of integrated analytics within DHIS2 demonstrate the value provided to end users and system owners, emphasizing the importance of tailored solutions that meet local needs. By reducing reliance on custom solutions and connectors, this standardized approach not only eases the burden on integration management but also offers a more cost-effective means of integrating multiple data sources, including DHIS2, iHRIS, LMIS, surveys, and population data. Furthermore, the creation, dissemination, and maintenance of standards, such as the Master Facility List, contribute to data quality and interoperability across the HIS. BAO Systems aims to take a platform approach to data integration and advanced analytics inspired by the approach of DHIS2 through building an open source, generic and configurable platform, designed in close collaboration with users, that can be shared and reused across many countries.

Primary Author: Lars Helge Øverland

Data integration, data warehouse, BI tools, Superset