Every result your laboratory releases passes through software before it reaches a clinician. The people who design, run, and question that software are a profession in their own right, and West Africa and the GCC need far more of them.
Dr. Chukwuka · Physician-haematologist, founder of EEHLSS | ALAFIAAI · ~8 min read
For research and education only. Not medical, legal or regulatory advice.
Ask a laboratory scientist in Lagos, Accra or Riyadh what slows their day down, and it is rarely the analyser. It is the handover: results retyped from an instrument printout, a request form that does not match the sample, a critical value phoned through but never documented, or a quality control run sitting in a notebook nobody audits. These are information problems, and they sit in the gap between the bench and the computer.
Laboratory informatics is the discipline that closes that gap. The CDC and the Association of Public Health Laboratories describe it as the application of information science, computer science, and information technology to laboratory practice. This covers more than just record-keeping; it includes test analysis, instrument messaging, decision support, and knowledge management. Their competency guidelines go further, noting that because every laboratory depends on information systems, every staff member needs some level of informatics competence, even though true specialists remain scarce.
That scarcity represents a real career opportunity. This guide outlines the primary roles, the essential skills, the formal and informal pathways into the field, and a practical 90-day plan for those ready to begin.
The roles: a ladder, not a single job
Job titles differ depending on the employer and the country, but most laboratory informatics work fits into a recognisable set of roles. Most people move through these positions step by step; few start out fully formed.
| Role | What the work looks like | Typical entry background |
|---|---|---|
| LIS super-user / champion | First-line support on the bench, training colleagues, reporting faults, testing changes before go-live | Practising lab scientist |
| LIS analyst / application specialist | Building and maintaining test, result and instrument dictionaries; reference ranges; rules; reports | Lab scientist with system experience |
| Interface / integration analyst | Connecting analysers, middleware, EHRs and national systems using HL7, ASTM and increasingly FHIR; mapping codes such as LOINC | Lab or IT background |
| Implementation & validation specialist | Workflow mapping, test scripts, user acceptance testing, go-live support, documented validation | Either; often vendor-side |
| Laboratory data analyst | Turnaround time, QC and utilisation analytics; dashboards; audit evidence | Lab scientist with SQL or Python |
| LIS manager / informatics lead | Governance, change control, vendor management, security, budgets, strategy | Experienced analyst |
| Physician or pathologist informatician | Clinical ownership of rules, reporting and decision support; validating algorithms; linking the lab to clinical care | Medically qualified, with informatics training |
| Computational / AI specialist | Building and, crucially, evaluating models on laboratory data, including flags, morphology and forecasting | Scientist or clinician with data-science skills |
Vendor job descriptions and industry guidance follow a similar pattern: you start with entry-level support or application roles, move into configuration and implementation, and eventually progress to senior analyst, project management, architecture, or leadership positions. I often see contract work on go-lives and upgrades serving as a common bridge between these levels.
The skills that actually get people hired
1. Laboratory domain knowledge
This is the advantage bench scientists already hold. Knowing why a haemolysed potassium matters, how a full blood count flag is generated, what a delta check is for, and how ISO 15189 expects results to be traceable is hard to teach an IT graduate quickly. Industry guidance consistently lists understanding laboratory workflows as the first skill.
2. Systems and data
You need to master LIS dictionary configuration, reading HL7 messages, basic SQL for data extraction, and terminologies like LOINC. Once you have the data, Python or R allows you to analyse it. You do not need a computer science degree for this, but you do need deliberate practice using real (de-identified) data.
3. Validation, quality and risk
A single configuration change can alter thousands of results. Employers are looking for people who write test plans, run user acceptance testing, maintain audit trails, and prioritise patient-safety risk. For those moving into AI, the discipline is the same: define the intended use, measure performance locally, monitor drift, and ensure human accountability.
4. People and change
Most implementations fail because of social friction, not technical flaws. Training colleagues, acting as a bridge between clinicians and developers, and managing the pressure when a new system goes live are the skills that distinguish a lead from a mere analyst.
A useful yardstick: The CDC/APHL competency guidelines grade informatics skills at four levels: beginner, competent, proficient and expert, adapted from the Dreyfus model of skill acquisition. Rating yourself honestly against those levels is a free, structured way to find your gaps.
Pathways in: three doors
From the bench
This is the most common route. Volunteer as the LIS champion in your section, join the validation work for the next upgrade, and learn how to pull your own turnaround and QC data. Within a year, you will have the evidence of system experience that analyst roles require.
From IT or data science
Developers and data professionals often have the technical skills, but they lack laboratory context. To build tools that actually get used rather than just sitting on a shelf, they need to shadow bench staff. They must understand the pre-analytical, analytical, and post-analytical phases, as well as the specific accreditation requirements we follow.
From medicine and pathology
In the United States, clinical informatics is a board-certified subspecialty managed by the American Board of Pathology and the American Board of Preventive Medicine. ACGME-accredited fellowship has become the primary route; the older practice pathway closed to new applicants in 2026, and the non-accredited fellowship pathway required training to start before the end of 2025. Residents can use the Pathology Informatics Essentials for Residents (PIER) curriculum, developed by the Association of Pathology Chairs, the Association for Pathology Informatics and the College of American Pathologists, which provides a structured syllabus covering databases and security, LIS management, digital pathology and analytics.
If you aren’t a physician, you can still apply for AMIA’s Health Informatics Certification (AHIC). Eligibility depends on having a qualifying degree and several years of informatics experience. Because the exam is based on US practice, it signals general competence rather than specific local regulatory knowledge.
Why now: the West African and GCC picture
In Nigeria, the Federal Government’s Nigeria Digital in Health Initiative, launched in 2024 and restated at a national stakeholder meeting in 2025, aims to build an interoperable national health data network and to bring the private sector, which delivers a large share of services, into national reporting. Interoperability of this kind needs people who understand both lab data and messaging standards. A recent example: a laboratory information management system used by NCDC’s national laboratories and partner labs has been connected to the national surveillance platform, SORMAS, so results entered once now flow automatically to decision-makers.
In Saudi Arabia, digital transformation under Vision 2030 has created demand, but research suggests a mismatch between graduates and employers. A 2023 study in BMC Medical Education found that surveyed experts favoured postgraduate informatics qualifications and often preferred computer-science graduates over bachelor’s health informatics graduates, and recommended more practical, industry-linked training. Laboratory professionals who combine domain knowledge with demonstrable technical work are well placed to fill that gap.
A 90-day starter plan
- Days 1–30: map and measure. Map out your lab’s sample journey, from the initial request to the final report. Rate your current performance against the four competency levels. Finally, learn to read a single HL7 result message from your own system.
- Days 31–60: build one thing. With your lab’s permission and using de-identified data, write some SQL or Python to generate a turnaround-time or QC report that your manager actually needs.
- Days 61–90: make it visible. Offer to join their next validation or upgrade. Write up what you built as a short case study, then present it at a departmental meeting or a professional association session.
A portfolio of small, real, governed projects carries more weight than a certificate alone, especially in markets where formal informatics training pathways are still being established.
The bottom line
Laboratory informatics is the intersection of laboratory medicine, software, standards, and now AI. It rewards those who understand the bench work and are willing to learn the systems behind it. As laboratories across West Africa and the GCC digitise, connect to national platforms, and begin evaluating AI decision-support tools, the professionals who can configure, validate, and govern these systems will shape the quality of every result. At EEHLSS and ALAFIAAI, we build MedLabAI-LIS as decision support, never as a replacement for professional judgement. That approach only works when laboratories have their own informatics talent.
This article is educational and reflects publicly available sources as of October 2026. Certification rules change; confirm current eligibility directly with each awarding body. No patient data were used.
References
- Ned-Sykes R, et al. Competency Guidelines for Public Health Laboratory Professionals: CDC and the Association of Public Health Laboratories. MMWR Suppl 2015;64(1). cdc.gov/mmwr/preview/mmwrhtml/su6401a1.htm
- APHL. Laboratory Competencies resources. aphl.org
- American Board of Pathology. Clinical Informatics subspecialty certification. abpath.org
- AMIA. Clinical Informatics Subspecialty. amia.org
- AMIA. Health Informatics Certification (AHIC): eligibility. amia.org
- CAP Today. From concept to curriculum: PIER going strong five years later. 2019. captodayonline.com
- Soft Computer Consultants. How do I get into laboratory information systems? 2024. softcomputer.com
- Resolve to Save Lives. A new lab system closes a critical gap in Nigeria’s disease surveillance. 2026. resolvetosavelives.org
- Gazette Nigeria. FG launches digital health reform to strengthen service delivery (Nigeria Digital in Health Initiative). gazettengr.com
- Alzghaibi H. The gap between bachelor’s degree graduates in health informatics and employer needs in Saudi Arabia. BMC Med Educ 2023;23:475. pmc.ncbi.nlm.nih.gov/articles/PMC10294393
- Saudi Health Informatics Competency Framework (doctoral work, University of Victoria). dspace.library.uvic.ca
EEHLSS | ALAFIAAI · Computational haematology & laboratory AI education · Educational content, not clinical advice
Leave a Reply