Digitalisation of Health Supply Chains: A Case Study Example

Context

This case study is based on practical implementation guidance shared during Health Procurement Africa’s (HPA) Ask the Expert webinar on digitalisation in public health procurement. The session presented an applied approach from Kenya, delivered by an HPA procurement expert, illustrating how public-sector health procurement teams can apply digital technologies to improve supply chain visibility, forecasting, and decision making.

Watch the full Ask the Expert webinar recording here.

Introduction

Digitalisation is transforming the way public health procurement systems operate. Unlike basic digitisation, which converts information into electronic formats, digitalisation enables organisations to use digital technologies to improve processes, enhance transparency, and generate greater value from data.

In public healthcare supply chains, digitalisation can help procurement teams improve demand forecasting, reduce stockouts, minimise wastage, and strengthen overall supply chain performance. This case study examines how Kenya has implemented digital supply chain tools to support national health commodity management.

Digitalisation Framework for Health Supply Chains

Digital Component	Purpose
Digitisation of Data	Convert procurement and supply chain records into digital formats
Supply Chain Automation	Automate procurement and inventory management processes
AI-driven Forecasting	Use consumption data to predict demand and guide supply decisions
Data Analytics	Identify trends, risks, and opportunities for improving procurement performance
Integrated Information Systems	Connect supply chain stakeholders and processes within a unified platform

Developing Digital Procurement Systems

Implementing digital procurement systems requires structured data, strong governance, and collaboration between technical specialists and procurement professionals. Organisations must also ensure that digital tools align with broader healthcare objectives, particularly improving patient outcomes and supply chain reliability.

Digital platforms can support end-to-end procurement processes, including demand forecasting, inventory management, order management, and delivery monitoring. When combined with analytics tools, these systems enable procurement teams to make data-driven decisions.

Case Application: Kenya’s Integrated Logistics Management Information System (ILMIS)

In Kenya, the government has implemented an Integrated Logistics Management Information System (ILMIS) to support national health commodity security. The system is managed through the Kenya Medical Supplies Authority (KEMSA) and is designed to automate and strengthen supply chain management across the healthcare sector.

The ILMIS platform enables health facilities to submit requests, conduct forecasting, and manage inventory using a single digital system. The platform integrates several components including early warning systems, forecasting tools, and automated ordering processes.

Key System Components

Component	Function
Commodity Early Warning System	Identifies supply chain risks such as potential stockouts or overstocking
Forecasting Module	Uses consumption data to predict commodity demand
Budgeting and Prioritisation Tools	Allow facilities to align procurement with available resources
Automated Ordering Platform	Enables facilities to submit procurement requests electronically
Electronic Proof of Delivery	Confirms delivery of commodities to health facilities through mobile systems

AI-Driven Forecasting and Demand Planning

A key innovation within the ILMIS system is the use of artificial intelligence and predictive analytics to support forecasting. The system analyses consumption patterns from health facilities using time-series models to estimate future demand for health commodities.
This approach allows procurement teams to move from reactive supply chain management towards a more proactive, demand-driven system. Facilities can generate forecasts directly within the system, allowing national procurement teams to plan procurement volumes more accurately.

Implementation Challenges

Before the introduction of digital systems, Kenya’s health supply chain faced several challenges, including limited visibility of facility-level demand, frequent stockouts, and high levels of commodity wastage due to expiry.

Digitisation of supply chain data has helped address these challenges by providing real-time information on inventory levels, consumption trends, and supply chain performance.

Results and Achievements

Outcome	Impact
Improved Demand Forecasting	Facilities can generate demand forecasts using consumption data
Reduced Stockouts	Better visibility enables faster response to supply shortages
Lower Commodity Wastage	Data-driven planning reduces expiry and overstocking
Improved Supply Chain Visibility	National teams can monitor inventory levels across facilities
Operational Efficiency	Automation reduces manual processes and administrative workload

Lessons Learned

The implementation of ILMIS highlighted several lessons for digital transformation in health procurement systems. First, strong government ownership of digital platforms is essential for sustainability. Second, capacity building is critical to ensure health workers can effectively use new digital tools.
Third, collaboration between government agencies, development partners, and technical specialists is necessary to successfully implement large-scale digital procurement systems.

Conclusion

This case study demonstrates how digitalisation can transform public health procurement systems. By integrating forecasting tools, automated ordering systems, and data analytics, Kenya has strengthened its ability to manage health commodity supply chains and improve procurement decision making.

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