Unlocking Better Patient Care in Nigeria: Why You Need an EMR with Interoperability

The Institute of Electrical and Electronics Engineers defines interoperability as the ability of a software (or hardware) to work with other products or systems and allow for information exchange. In healthcare, this is more than just a technical feature. Instead, it is a vital tool for effective treatment, disease tracking, and public health research.

Healthcare is inherently collaborative. A patient’s care rarely involves a single clinician. Instead, hospitals, labs, pharmacies, and insurers all use the same medical data. When these systems cannot talk to each other, care becomes fragmented. Consequently, this leads to administrative waste and dangerous medical errors.

Why we need interoperable designs in EMRs

A clinical progress note is essentially a story. It documents the journey of a patient from the onset of symptoms to diagnosis, treatment, recovery, or long-term disease management. These notes capture the reasoning behind a clinician’s decisions and form a core component of the patient’s medical record.
In theory, such documentation should be enough to guide patient care. In practice, however, healthcare delivery extends far beyond the physician’s note.
A patient’s treatment pathway may involve:

• Drug dispensing at pharmacies
• Diagnostic tests in laboratories
• Imaging procedures in radiology departments
• Billing and insurance claim processing
• Regulatory audits by medical boards
• Continuity of care across multiple healthcare institutions

Each of these steps requires data that machines and humans can both read. When systems use incompatible formats, every process slows down. As a result, care becomes more expensive and prone to mistakes.

The Hidden Cost of Non-Standardized Medical Data

Here, we study some of the ripple effects caused by the ambiguity of a “HTN” diagnosis:

A patient’s diagnosis was documented as “Essential HTN”; this is clinically accurate and thoroughly precise. A management regime for the patient is already in view.

Essential hypertension is also known as primary hypertension. It can be shortened into various formats readable to clinicians and experts. However, it is messy with data aggregation and epidemiology, and becomes expensive when mapping “Essential HTN”, “Primary HTN”, “Primary Hypertension” and “Essential Hypertension” to a single diagnosis. It doesn’t look like much, but once we add more diagnoses it becomes a headache to track. The resulting bottleneck would reflect in:

1. Epidemiology and disease tracking
2. Insurance claim management
3. Data fragmentation and eventually, blind policy making.

Global Medical Standards for Interoperability

Global medical standards were created to solve these problems by ensuring that health systems share a common clinical language. Below are the most commonly used medical vocabularies.

1. The International Classification of Diseases (ICD) is one the most widely used diagnostic classification systems, developed by the World Health Organization (WHO), providing a structured system of codes for diseases, symptoms, and medical conditions. Essential Hypertension is coded “I10” in the 10th revision of ICD (ICD-10), meaning everywhere essential hypertension is mentioned, the code I10 is used. This makes searches across all compliant systems simple, fast, and research ready.
2. Logical Observation Identifiers Names and Codes (LOINC) is the golden the standard vocabulary for laboratory tests and clinical measurements. It exists to bridge the gap between each vendor machine analysers, ensuring that different labs with various vendors can understand and refer to the same investigation measurement. For cross-sectional studies, where specific investigation parameters are needed in the study, for example identifying the Mean Corpuscular Hemoglobin Concentration (MCHC) in Sickle-cell patients across hospitals in Nigeria, Ghana and Kenya among other parameters, LOINC gives the ability to find that parameter, separated by the method used. MCHC is coded “786-4” by Automated count and “47279-5” from Cord blood. These nuances might be missing if this ontology isn’t used.
3. Digital Imaging and Communications in Medicine (DICOM) is the technical standard for interoperability of medical images, facilitating storage and transfer of the diagnostic information. Unlike regular imaging compression formats such as JPEG, PNG, and GIFs, DICOM files carries smart data; it stores within an image the patient’s ID, the study date, and the machine settings. This allows a scan taken on one manufacturer’s machine to be read perfectly by any other software. This is interoperability in action. Making query and sorting by modality or diagnosis quick and easy. Most DICOM readers have an anonymization feature, which blinds the patient identifiable information (PII), making this excellent for medical research with high quality images.
4. RxNorm is one of the most advanced medical vocabularies out there for medical drug, and might be one of the most essential for patient-care. It classifies drugs with codes, showing the drug relationships, attributes and the various forms of the medication and how they’re found. This is also vital in patient care where a patient might have documented adverse drug reactions (ADRs) to a specific component in the medication. Those relationships are quickly identified to prevent accidents. It provides a normalized naming system for drugs and allows different software programs to share drug information efficiently. In policy making, RxNorm makes it easy to map drugs administered to clinical outcomes

These standards work together, ensuring that medical systems can communicate effectively by sharing a common clinical language.

Why Interoperability Matters for Research and Public Health

Beyond immediate patient care, interoperability has profound implications for medical research and public health.
When health records are structured and stored using common standards such as ICD-10, LOINC, DICOM, and RxNorm, researchers can aggregate and analyze data across multiple institutions. This enables large-scale studies on disease prevalence, treatment outcomes, and healthcare trends.
Without interoperable data, valuable clinical information becomes trapped in isolated systems, making it difficult to identify patterns that could improve medical practice or inform health policy.

Systems like Tembo EMR are being designed with interoperability in mind, ensuring that digitized clinical data remains structured, shareable, and research-ready; because adopting and implementing standards is not just about improving software; it is about improving the quality of care itself, and finally utilizing the medical data available in Nigeria