Data-rich, decision-poor: The gap in Kenya’s health information system

In this data-driven age, the Kenyan healthcare sector should invest heavily in big data analytics. Big data analytics involves the use of various techniques, such as machine learning and AI, to unearth hidden data patterns and trends by cross-examining and processing various contexts, thus producing appropriate results.

While fields such as insurance, telecommunications and marketing have invested heavily in big data analytics to refine and produce the latest market trends and personalised product developments, the Kenyan healthcare landscape lags slightly behind.

Kenya is a low-income country with a growing population that is largely living in poverty and suffering from a high disease burden, which puts an economic strain on its health systems.

The unveiling of the Social Health Authority (SHA) in 2024 marked a key step towards achieving universal health coverage in Kenya. The SHA facilitates healthcare services from registered providers by pooling contributions and equitably distributing services to all Kenyans.

This authority holds a wealth of data, including claims data, utilisation records, enrolment records, health costs incurred, and insurance performance metrics. However, data alone does not indicate improvements in service delivery performance.

Despite compulsory health insurance for all citizens, coverage of this insurance scheme is low. Challenges noted include cumbersome claim settlements, inadequate consumer knowledge, negative perceptions, operational inefficiencies and long wait times for service delivery and claim reimbursements, among others. Fraud in this health financing sector remains a challenge.

Through big data analytics, trends can be established based on historical transactions and in particular heavy loss-making contracts to assess indicators of fraud. Trends and analytics will enable interrogation of the quality and cost of business from specific indicators.

Targeted interventions, through data analytics, can improve this national health financing model.

The appropriate data analytics technique will enhance customer experience, real time fraud detection techniques, enhanced claims processing and improve operational tasks execution.

Besides, the process will contribute to improved data-driven policy decision-making and financial sustainability. The analysis of SHA data will allow for a strategic and informed re-think of product packaging to more relevant, affordable, and need-centric insurance coverage even depending on contribution.

Another compelling case for big data analytics in Kenya's health sector lies in the fight against antimicrobial resistance.

Antimicrobial resistance is a silent pandemic ravaging Kenya's public health system. Drug-resistant infections are a leading cause for prolonged hospital stays, increased healthcare expenditure, and increased mortality which can be prevented if adequate measures are put in place.

Through concerted efforts by the government to ensure genomic sequencing, real-time laboratory data reporting and unified electronic health records, Kenya can generate critical data sets necessary to track patterns.

The application of big data analytics in the generated data can unravel resistance hotspots, transmission techniques, and identify the culprit genes driving the resistance. This critical information can shape the nation’s policies and strategies on pharmaceutical drug use and revamp antimicrobial stewardship programmes.

Undoubtedly, data analytics reveal unseen patterns and recommend appropriate corrective measures.

However, data analytics does not solely rely on robust software to effect change. The government must effectively deploy trained healthcare professionals, adopt targeted policy intervention, establish robust data governance infrastructure, and sustain a strong political commitment.

The private sector, a key industry player, equally has to foster innovation and strengthen health data systems. Kenya’s healthcare future heavily relies on action, insight, and foresight grounded in reliable data.

Dr Jesee Gichure Munga is a pharmacist with expertise in regulatory affairs, quality assurance, and data science, affiliated with AfiaData and a member of the Pharmaceutical Society of Kenya