Healthcare supply chains are complex, interconnected systems crucial for delivering timely and effective health services. For USAID implementing partners, optimizing health supply chains in low- and middle-income countries (LMICs) means ensuring critical medicines and supplies reach even the most remote communities.
This requires efficient systems that utilize real-time data to inform critical decision-making at all levels of the supply chain. Data-driven approaches are essential for understanding demand, managing inventory, and forecasting needs accurately.
Uganda’s experience under the Strengthening Supply Chain Systems (SSCS) program, led by the Ministry of Health and USAID-supported organizations like Management Sciences for Health (MSH), offers valuable insights into how a country can optimize its health supply chain through data-driven decision-making.
Importance of Data Use in Health Supply Chains
Data is at the core of any efficient supply chain. By collecting and analyzing data, supply chains can forecast demand, manage stock levels, and improve overall health service delivery. As Dr. Victoria Nganda, a USAID Program Management Specialist for Health Commodities, stated, “without data, we will be operating in the dark.”
In Uganda, data is used at every level, from the central government to district health facilities, to make strategic supply chain decisions that can directly impact the availability of life-saving medicines and equipment.
Uganda’s Quantification and Procurement Planning Unit (QPU) uses data on consumption trends, morbidity, and other key factors to create detailed forecasts and inform procurement planning. The importance of this data cannot be overstated.
For example, QPU’s data-driven forecasting led to an additional budget allocation of $139 million for health commodities in 2023-2024, a significant increase that underscores the impact of data in securing funding for critical health supplies. Accurate data allows supply chain managers to make informed decisions, avoiding costly overstocking or the equally problematic stockouts that jeopardize patient care.
Three Achievements Using Data-Driven Approaches
Uganda’s SSCS program demonstrates how a data-driven approach can transform a health supply chain. According to Dr. Nganda, Uganda receives an annual funding budget of over $450 million from the government and development partners, yet only 60% of essential medicines are available across the country’s health facilities. Addressing this gap requires not only additional funding but also enhanced data visibility to make informed distribution decisions.
1. Improved Stock Visibility and Order Fulfillment
Data from Uganda’s DHIS2 system has helped track stock levels and availability of key medicines. For example, as of July 2024, the national stockout rate for treatment-resistant (TR) medicines stood at 40%, highlighting areas that need urgent attention. DHIS2 data is complemented by additional data sources, including Uganda’s electronic Logistics Management Information System (eLMIS), which captures real-time inventory data from the 1,400 health facilities already equipped with digital systems.
The integration of eLMIS with ordering systems has improved Uganda’s order fulfillment process, making it easier for facilities to request medicines and supplies in a timely manner. In fact, over 1,900 health facilities now place electronic orders through the National Medical Store (NMS), accounting for about 30% of public health facilities across Uganda. This digitization effort has contributed to achieving a 90% order fulfillment rate in Uganda’s private-not-for-profit (PNFP) facilities, according to Dr. Janita Laaga, Project Director for the USAID-funded Local Activity for Warehousing and Distribution at Joint Medical Stores (JMS).
2. Streamlined Resource Allocation
A major advantage of data-driven decision-making is the ability to allocate resources more effectively. The integrated quantification process led by the QPU in 2023 enabled Uganda to identify gaps in funding across different health programs.
For example, data analysis revealed that non-communicable diseases were underfunded. By advocating for increased allocations based on this evidence, the QPU succeeded in securing additional resources for non-communicable disease medications. This ability to advocate for funding based on real data is a powerful tool for development partners and government agencies alike, ensuring that funds are directed where they are most needed.
3. Reduced Waste and Improved Redistribution
One of the key challenges in any health supply chain is managing stock to reduce wastage. Overstocking can lead to expired medicines, while stockouts can prevent patients from accessing necessary treatment. To address this, JMS employs a data-driven redistribution strategy. By regularly analyzing consumption data, JMS redistributes surplus stock from overstocked facilities to those facing shortages, preventing wastage and ensuring a more balanced distribution of supplies.
This approach was particularly successful in managing oxygen supplies during respiratory outbreaks. JMS monitors oxygen consumption and stock levels across facilities, enabling it to respond quickly to spikes in demand. This process is supported by Uganda’s DHIS2, which captures routine reports from health facilities, allowing supply chain managers to track inventory and adjust supply accordingly. By utilizing data to coordinate redistributions, JMS and other stakeholders have improved overall efficiency in Uganda’s supply chain.
3 Challenges to Data-Driven Supply Chain Management
Despite these achievements, Uganda faces challenges in expanding its data-driven approach. Although digital platforms like eLMIS and DHIS2 have been instrumental in improving data visibility, they currently cover only 25% of Uganda’s 6,200 public health facilities. Expanding digital coverage to all health facilities will be critical to achieving a fully data-driven supply chain.
1. Limited Infrastructure and Connectivity
A significant barrier to comprehensive data collection is the lack of digital infrastructure in many regions. NITA-U, Uganda’s National Information Technology Authority, has connected over 1,500 facilities to the national internet backbone, providing essential connectivity for digital reporting. However, many facilities, particularly in remote areas, still lack reliable internet or the hardware needed to capture and transmit data in real-time.
To address this, NITA-U plans to expand digital infrastructure to an additional 1,200 sites over the coming years. This expansion will enable more health facilities to report data in real time, increasing the accuracy of Uganda’s national supply chain data and enhancing decision-making at all levels. Additionally, some digital platforms used in Uganda, such as the UgHub data exchange platform, support offline data entry, allowing facilities to record data even without internet connectivity and transmit it once connectivity is restored.
2. Data Quality and Workforce Training
Data quality is another critical challenge. Even when facilities are equipped with digital tools, data must be accurate and timely to be useful. According to Dr. Mare, ensuring the quality of consumption data from health facilities remains a challenge due to limited staff training and frequent staff turnover. For example, JMS has identified that some facilities report inaccurate consumption patterns, likely due to a lack of understanding of data entry protocols. To address this, JMS and other partners have implemented ongoing training programs for health workers, focusing on data entry and analysis skills.
Capacity-building efforts, particularly at the district level, are essential for improving data quality. Dr. Siraji Masai, District Health Officer (DHO) in the Kapchorwa District, emphasized that regular data quality audits have helped his team identify and correct errors in facility reporting. To further improve data accuracy, Uganda has begun deploying dedicated supply chain professionals at the district level. This approach provides a dedicated workforce focused on monitoring data and supporting health facilities in maintaining accurate records.
3. System Integration for Interoperability
Another ongoing challenge is system integration. Currently, many of Uganda’s digital health platforms are not fully interoperable, limiting the flow of data between systems. For example, electronic medical records (EMRs) and the eLMIS are not yet integrated, complicating data-sharing efforts.
The Ministry of Health is working to achieve interoperability across these systems through the National Health Data Warehouse, which aims to integrate multiple data sources to provide a comprehensive view of the health supply chain. Once these systems are fully integrated, Uganda’s health sector will have a more cohesive, real-time view of its inventory, enabling better forecasting and planning.
5 Recommendations for Data-Driven Supply Chains
Based on Uganda’s experience, USAID implementing partners and other stakeholders can adopt several strategies to strengthen data-driven supply chain performance:
- Invest in Digital Infrastructure and Connectivity: Expanding internet access and providing digital hardware to all health facilities are essential for comprehensive data collection. Offline data entry options can also enable facilities without reliable internet to contribute to national data systems.
- Improve Data Quality Through Training and Capacity-Building: Frequent training sessions and data quality audits help ensure accurate data entry. In Uganda, these efforts have led to significant improvements in reporting accuracy, which in turn enhances the effectiveness of data-driven decision-making.
- Develop an Interoperable Data Ecosystem: Integrating EMRs, eLMIS, and other health data systems is crucial for creating a seamless flow of information. Interoperability reduces redundancies and enables health officials to access all necessary data from a single platform.
- Implement Predictive Analytics for Proactive Planning: With more comprehensive data, supply chains can leverage predictive analytics to anticipate demand shifts and prepare for potential disruptions, such as disease outbreaks or seasonal fluctuations in certain medicines.
- Strengthen Collaboration Between Stakeholders: Effective supply chains require cooperation between ministries, development partners, and local governments. By working together, stakeholders can align resources and strategies to address common challenges and share best practices.
Data-driven decision-making is fundamental to creating resilient, responsive health supply chains. Uganda’s experience underlines the critical role of accurate, timely data in optimizing supply chain performance. By prioritizing digital transformation, enhancing data quality, and fostering system interoperability, USAID implementing partners can ensure that health supply chains in LMICs are equipped to meet the demands of their communities.
A well-functioning, data-driven supply chain not only improves health outcomes but also maximizes the impact of limited resources, ultimately saving lives across Uganda and other regions facing similar challenges.
