The AI revolution is rapidly expanding and sweeping across the globe. Countries are in a subtle, but intense race to lead in the adoption and advancement of AI technology.
Africa, on the other hand, is also undergoing a quiet digital revolution. Across the continent, governments, hospitals and innovators are gradually embracing digital health technologies as part of a broader effort to modernise healthcare systems.
There is an explosion in the adoption and use of electronic medical records. Mobile health tools are supporting frontline healthcare professionals, and telemedicine platforms are increasingly becoming accessible, connecting rural communities to specialists and other healthcare professionals.
These digital health solutions are doing more than simply improving access to care. They are also generating something extremely valuable: data!
Every patient record entered into an electronic medical record, every consultation conducted through telemedicine, and every report submitted through a mobile platform contribute to a growing pool of valuable healthcare data.
And this is where the connection to artificial intelligence becomes critical.
As we all know, data is the raw material and backbone of artificial intelligence (AI) systems.
Without sufficient data to analyse and learn from, AI systems cannot deliver accurate predictions or meaningful insights.
But we have a problem… Our data is trapped…
The major limiting factor for Africa, as a continent, in integrating AI into our systems remains the lack of large volumes of structured data, particularly in healthcare.
Even the limited data currently being collected across rural and urban healthcare facilities is stored in silos — that is, isolated systems that don’t communicate with one another.
In such circumstances, meaningful data integration, analysis and large-scale impact become extremely difficult.
Hospitals, laboratories, pharmacies, insurers and national reporting platforms often operate independently. Data is collected, but it stays trapped within separate systems.
And where data isn’t connected, it cannot be used to power artificial intelligence (AI), generate predictive analysis or execute coordinated care.
This is where FHIR comes in. A truly transformative tool that could solve many of the challenges surrounding interoperability in Africa’s healthcare ecosystem.
You cannot build a smart health ecosystem if your systems cannot communicate with one another. To unlock the real promise of AI in Africa’s healthcare ecosystem, we do not need more algorithms; we need a common language.
That language is FHIR!
What Is FHIR In Layman’s Terms?
FHIR is short for Fast Healthcare Interoperability Resources. It is a global standard developed by HL7 (Health Level 7) International to enable consistent information exchange across digital health systems.
In plain language:
FHIR gives health systems a common language. If different hospitals use different software, FHIR allows them to share information without confusion. It standardises how key information is structured.
Information like:
- Laboratory results
- Medications
- Patient demographics
- Diagnoses
- Vital signs
- Clinical notes
FHIR provides a standardised format and structure that all systems can understand and work with, rather than each system storing and sending information in its own format.
Without a shared standard, digital health systems remain isolated. With FHIR, they become connected!
Understanding How FHIR Works
FHIR is built around small, structured building blocks called “resources.” Each resource represents a specific type of healthcare information. Some examples of resources include:
- Patient: a human or animal in question who is receiving healthcare.
- Practitioner: a healthcare professional, can be a doctor, nurse, pharmacist, consultant, etc.
- Observation: lab results, imaging results, vital signs, etc
- Diagnosis: a condition.
- Encounter: used to represent any interaction between a patient and healthcare provider(s) for the purpose of providing healthcare services or assessing a patient’s health status.
There are many other resources, such as billing, insurance, organisation, location, etc., which are placed into different categories, but that is beyond the scope of this publication.
FHIR enables information to be standardised and shared across multiple systems by requiring that shared information meet minimum requirements and be in a specific format.
This is the universally agreed format that all systems can understand and interact with in the same way.
For example, the minimum requirement for creating a patient profile using the patient resource involves providing the following information:
| Field | Why it matters |
| identifier | Unique patient identity (can be the social security number, national ID number, etc) |
| name | Human-readable identification |
| gender | Clinical relevance |
| birthDate | Age calculation, clinical safety |
| telecom | Patient contact |
| address | Location & demographics |
These can be represented in a JSON file in the following format:
{
“resourceType”:”Patient”,
“id”: “patient-001”,
“identifier”: [
{
“system”: “https://hospital.example.org/mrn”,
“value”: “MRN123456”
}
],
“name”: [
{
“use”: “official”,
“family”: “Onwughai”,
“given”: [“Onyeka”]
}
],
“gender”: “male”,
“birthDate”: “1955-07-15”,
“telecom”: [
{
“system”: “phone”,
“value”: “+2348012345678”,
“use”: “mobile”
}
],
“address”: [
{
“city”: “Abuja”,
“state”: “FCT”,
“country”: “Nigeria”
}
]
}
This information is the minimum requirement to avoid confusion, and it has an internationally agreed structure and format so that each system that exchanges it will understand it.
The requirements also specify the data types (e.g., string, boolean, integer, decimal, date, list, etc.) for each parameter (e.g., name, address, gender, identifier, etc.) within each resource.
These resources can then be linked together to form a complete patient story.
A patient resource connects to their observations, medications, allergies and diagnoses. Because each resource follows an internationally agreed structure, different hospital systems can exchange them without confusion.
Importantly, systems can share only what is needed, not entire databases, which improves efficiency and protects privacy.
FHIR also allows organisations or countries to create “profiles.”
A profile is a customised version of a resource that adapts it to local needs.
For example, the United States requires additional data for Race, Ethnicity, and Birth Sex. Instead of redesigning the system from scratch, they refined the existing structure using profiles and created Race, Ethnicity, and Birth Sex as “extensions”. Where unique local requirements exist, FHIR supports “extensions,” which allow additional data fields while still maintaining international compatibility.
FHIR adoption is increasing exponentially worldwide. According to data from the Office of the National Coordinator (ONC), USA, about 85% of digital health companies (including startups) support FHIR APIs in some capacity, and about 73% of startups that integrate with more than one Electronic Health Record (EHR) system report extensive FHIR use, compared to only 27% of those using just one EHR.
As healthcare systems worldwide move toward interoperability, FHIR is positioned not just as a technical standard, but as the backbone of next-generation digital health ecosystems, including those being built across Africa.
“FHIR gives health systems a common language. If different hospitals use different software, FHIR allows them to share information without confusion. It standardises how key information is structured.”
Africa’s Digital Health Momentum: Real Progress, Real Gaps
A number of African countries have already made some meaningful investments in digital health.
Kenya: Expanding Digital Infrastructure
Kenya has introduced electronic medical record systems across many public facilities and developed a national eHealth strategy.
The country has also invested in health information exchange frameworks to support interoperability.
Despite all these, as in many countries, different systems still struggle to communicate consistently across counties and private facilities.
Rwanda: Coordinated National Vision
Rwanda has taken a highly coordinated approach to digital transformation. From hospital systems to community health worker platforms and telemedicine services, Rwanda has prioritised national alignment and central oversight.
This strong governance model shows how interoperability can be built into systems from the beginning, rather than added later.
Ghana: Linking Clinical and Insurance Data
Ghana has digitised many public hospitals and strengthened the infrastructure of its National Health Insurance Scheme.
However, better integration between clinical records and insurance systems would significantly improve efficiency and reduce the burden on the administrators.
FHIR-based interoperability could really simplify claims processing and improve continuity of care.
Nigeria: A Growing But Fragmented Ecosystem
Nigeria has one of the continent’s most vibrant digital health ecosystems, with public systems, private hospitals and innovative health tech startups operating simultaneously.
Yet the scale and decentralised nature of the system create fragmentation. Several factors, such as state-level variation, multiple vendors, and inconsistent standards, limit seamless data exchange.
Several efforts have been made towards fostering interoperability by different not-for- profit, health-tech organisations, one of the most recent ones was the DHIN (Digital Health Interoperability Network) connectathon held at Abuja in November 2025, where FHIR implementation guidelines were published for ePharmacy/ePrescription, Insurance Claims, Medical Devices and MNCH (Maternal and Child Health) and live demos of real life application were made for each tracks with the registrar of MDCN (Medical and Dental Council of Nigeria) and PCN (Pharmacy Council of Nigeria) and other prominent healthcare leaders present.
A resolution was passed to fast-track the adoption of FHIR and interoperability nationwide.
A unified interoperability framework would enable Nigeria to scale its digital innovation.
South Africa: Public–Private Integration
South Africa has advanced laboratory systems and provincial electronic health platforms. As the country moves toward National Health Insurance reform, interoperability between public and private providers will become increasingly critical.
FHIR provides a pathway to standardised exchange across sectors.
Across these countries, the story is similar:
Digital tools exist.
Data is being collected.
But systems are not fully connected!
Why AI And Predictive Analytics Depend Largely On Interoperability
Artificial intelligence in healthcare is heavily built on data. In fact, if there’s no data, AI and predictive analytics would be impossible, as data is the raw material.
To identify patterns, predict risks and support clinical decisions, AI systems require:
- Clean data
- Structured data
- Consistent definitions
- Large, diverse datasets
If Hospital A records “Malaria” as ICD-10 code B50 and Hospital B records it as text saying “severe malaria,” an AI model will struggle to learn from both.
If lab results are formatted inconsistently, predictive tools cannot effectively combine them.
FHIR ensures that:
- Blood pressure readings are structured the same way.
- Diagnoses follow consistent definitions.
- Lab results are clearly categorised.
- Patient identifiers follow agreed formats.
When data is standardised across facilities and regions, it becomes possible to build reliable AI systems trained on African populations, thereby reducing bias and improving relevance.
What This Looks Like In Real Life (Practical Application Of FHIR In Everyday Healthcare)
1. One Patient Record Across Facilities
Imagine a patient in Lagos who visits:
- A primary care clinic
- A private diagnostic centre
- A tertiary hospital
Today, those systems may not share information electronically.
But with FHIR:
- Lab results can be securely accessed by authorised providers. That is, when FHIR is fully functional, several lab results from different private labs can easily be shared with a hospital consultant via hospital EMR systems. With FHIR, your specialist can instantly see your lab results and pharmacy history on their screen. No repeat tests. No “I forgot what medicine I’m taking.”
- Medication histories of patients from community pharmacies can be viewed in real time by physicians or hospital pharmacists directly managing a patient.
- Allergies and chronic conditions become visible. Even the allergies and adverse drug reactions reported by community pharmacies for a particular patient will be displayed in real time to healthcare professionals in the hospital where that patient is being managed.
This greatly reduces medical errors and unnecessary repeat testing.
2. Faster Outbreak Detection
During outbreaks, for example, cholera, Ebola or COVID-19, speed saves lives.
Interoperable systems allow:
- Laboratories to report results automatically, and this report is broadcast to all connected systems, such that all hospitals, pharmacies and healthcare facilities in general will receive this information in real time.
- Facilities to flag suspected cases digitally.
- Ministries of Health to monitor trends in real time.
Countries that can connect clinical and laboratory data quickly are better positioned to respond to emerging threats.
3. Predicting Risk Before Complications Occur
As we all know, AI performance is strongly dependent on the quality and quantity of the data used. The more quality data provided, the better the data’s ability to perform the set tasks. Predictive analytics becomes powerful when data from many facilities is combined.
For example:
- Identifying pregnant women at risk of complications
- Predicting which tuberculosis patients may default on treatment
- Forecasting medicine shortages
- Detecting rising malaria trends early
FHIR enables the structured data exchange required for these models to operate accurately and also enables access to large volumes of high-quality data from multiple sources.
4. Strengthening Telemedicine
Telemedicine is expanding across rural Africa.
But virtual consultations are limited if clinicians cannot see the patient’s history.
With interoperable systems:
- A remote specialist can access structured medical records.
- Lab results can be reviewed instantly.
- Referrals can be sent electronically.
Telemedicine becomes integrated, not isolated.
5. Supporting Clinical Decision Tools
Standardised data from FHRI-enabled systems also enables decision-support tools that assist clinicians by flagging drug interactions, guiding physicians on the best course of therapy, drawing attention to abnormal results, suggesting preventive screenings, etc.
These tools are particularly valuable in resource-constrained settings with limited specialist availability.
The Elephants In The Room (Major Concerns In African Healthcare)
Infrastructure Challenges
A number of facilities have limited internet connectivity.
Some possible solutions include:
- Offline-first systems
- Local data storage with periodic synchronisation
- Mobile-based applications
FHIR is flexible enough to work in low-resource environments when thoughtfully implemented.
Workforce Capacity
Healthcare professionals are not expected to become software engineers. However, administrators and policymakers must understand why interoperability standards matter. A significant percentage of healthcare professionals in Nigeria and across Africa lack digital health literacy. Training programmes and health informatics education can build sustainable local capacity.
Privacy And Trust
Patient data must be protected, and healthcare professionals should be trained and sensitised to the country’s data privacy laws, particularly those governing health data.
FHIR supports:
- Secure authentication
- Controlled access
- Role-based permissions
- Consent management frameworks
Strong governance ensures public trust.
Why This Moment Matters
Africa is still actively building much of its digital health infrastructure.
This creates a strategic opportunity.
Instead of struggling later to fix disconnected systems, countries can embed interoperability standards from the outset.
For global partners, including UK-based organisations, supporting FHIR-aligned infrastructure means investing in:
- Long-term system resilience
- AI-ready health ecosystems
- Pandemic preparedness
- Efficient health financing systems
- Data-driven national planning
Interoperability is not a luxury. It is foundational.
Final Thoughts
Africa’s digital health expansion is impressive. Innovation is vibrant, and investment is increasing.
The next phase must focus on connection!
FHIR is not simply a technical framework. It is the layer that enables digital tools to work together safely, consistently, and at scale.
With interoperability in place, health systems across Africa can move from collecting data to using it intelligently:
- To predict risk
- To respond faster
- To coordinate care
- To reduce waste
- To improve patient outcomes
For African leaders and global partners alike, the question is no longer whether digital health matters.
The question is whether we will connect it properly.
FHIR provides the pathway.
