MSc

MSc Health Informatics

Where clinical care meets digital innovation

Online & New Capital Campus

4 Semesters (2 Years)36 creditsEnglish

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Overview

Healthcare generates more data than any other sector, yet many institutions struggle to use it effectively. This programme trains informaticians who understand both clinical workflows and modern data architecture. You will study electronic health records, FHIR interoperability standards, clinical decision support, and health data governance including GDPR and HIPAA principles. Case studies span NHS trusts, African community health networks, and private hospital groups. MSc Health Informatics is taught as one award, not a list of unrelated modules. The published length is 4 Semesters (2 Years), and the credit total is 36. Students move from Introduction to Health Informatics through Introduction to Health Informatics; Clinical Workflow & Process Analysis; Health Data Standards (HL7, FHIR, SNOMED); Biostatistics & Epidemiology; Electronic Health Records & Implementation; Health Information Exchange & Interoperability, and finish on MSc Health Informatics Capstone. Each course has a question, a method, and a submission. In this field, students describe how people, records, and decisions move through one service, and separate cause from harm. Reading is a pathway description, an incident summary, and an information standard. The artefact a marker expects is a brief a service manager could use, with the evidence attached. The award is built so that a graduate can do the following in practice: Map clinical workflows and identify informatics improvement opportunities Design EHR configurations and interoperability solutions using HL7 FHIR Apply epidemiological methods to population health analytics Teaching assumes the student can read a source, attempt a problem before the seminar, and revise after feedback. Attendance at live seminars is part of the design. The capstone or final course must use the methods of the earlier courses; a project that ignores them does not pass. This course does not confer a licence to practise nursing, medicine, or any other clinical profession. The pages for each course name the topics that are examined. Those topics are the syllabus. A brochure line is not a substitute for them.

Clinical and IT backgrounds are both welcome — bridge modules level-up whichever side you arrive from. You will configure FHIR APIs in sandbox environments and critique real EHR rollout case studies from the NHS and East Africa.

Who This Programme Is For

Nurses, doctors, and allied health professionals moving into informatics
IT analysts entering healthcare technology roles
Public-health officials managing digital health programmes

Faculty spotlight

Dr. Aisha Okonkwo, former NHS clinical informatics lead, teaches EHR implementation; Professor Emma Laurent researches low-bandwidth telemedicine architectures.

How you can study

Digital only

Study online

100% tuition-free online

Online tuition is completely free. Study from anywhere in Egypt, the Arab region, and worldwide with full digital flexibility.

✦ Tuition: £0 / $0
✦ Examinations are free. There is no exam fee.
✦ Learn from anywhere · Live online seminars

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What You Will Learn

Map clinical workflows and identify informatics improvement opportunities
Design EHR configurations and interoperability solutions using HL7 FHIR
Apply epidemiological methods to population health analytics
Evaluate health IT implementations using safety and usability frameworks
Lead cross-functional teams of clinicians, IT staff, and administrators
Conduct usability and safety assessments of clinical software
Draft data-sharing agreements compliant with UK GDPR

Curriculum

Year 1 — Foundations

Code	Course	Credits · hours
HI501	Introduction to Health Informatics Introduction to Health Informatics (HI501) is a 3-credit course on MSc Health Informatics, with 30 notional learning hours. By the end, students can describe how people, records, and decisions move through one service, and separate cause from harm, using Introduction to Health Informatics as the working context rather than a generic management example. The course is taught in three movements. First, students establish the terms and the decision the course is about. Second, they apply the method to a case, dataset, text, or design and compare it with a weaker alternative. Third, they revise the work after feedback and state what the conclusion cannot support. Preparation uses a pathway description, an incident summary, and an information standard. Seminar time is for the decision, not for reading the materials aloud. Assessment is a brief a service manager could use, with the evidence attached. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone. This course does not confer a licence to practise nursing, medicine, or any other clinical profession. HI501-M1 · Pathway, payment, records, and the bottleneck — Introduction to Health Informatics HI501-M2 · Incident, harm, cause, and the change that prevents a repeat — Introduction to Health Informatics HI501-M3 · Indicators, privacy, and misuse of a report — Introduction to Health Informatics HI501-M4 · Quality, safety, and the limit of the data — Introduction to Health Informatics HI501-M5 · Service design for a named population — Introduction to Health Informatics HI501-M6 · A service or informatics brief with evidence and a recommendation — Introduction to Health Informatics	3 · 30 h
HI502	Clinical Workflow & Process Analysis Clinical Workflow & Process Analysis (HI502) is a 3-credit course on MSc Health Informatics, with 30 notional learning hours. By the end, students can describe how people, records, and decisions move through one service, and separate cause from harm, using Clinical Workflow & Process Analysis as the working context rather than a generic management example. The course is taught in three movements. First, students establish the terms and the decision the course is about. Second, they apply the method to a case, dataset, text, or design and compare it with a weaker alternative. Third, they revise the work after feedback and state what the conclusion cannot support. Preparation uses a pathway description, an incident summary, and an information standard. Seminar time is for the decision, not for reading the materials aloud. Assessment is a brief a service manager could use, with the evidence attached. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone. This course does not confer a licence to practise nursing, medicine, or any other clinical profession. HI502-M1 · Pathway, payment, records, and the bottleneck — Clinical Workflow & Process Analysis HI502-M2 · Incident, harm, cause, and the change that prevents a repeat — Clinical Workflow & Process Analysis HI502-M3 · Indicators, privacy, and misuse of a report — Clinical Workflow & Process Analysis HI502-M4 · Quality, safety, and the limit of the data — Clinical Workflow & Process Analysis HI502-M5 · Service design for a named population — Clinical Workflow & Process Analysis HI502-M6 · A service or informatics brief with evidence and a recommendation — Clinical Workflow & Process Analysis	3 · 30 h
HI503	Health Data Standards (HL7, FHIR, SNOMED) Health Data Standards (HL7, FHIR, SNOMED) (HI503) is a 3-credit course on MSc Health Informatics, with 30 notional learning hours. By the end, students can define a measurable question, fit a method that can be checked, and report where it fails, using Health Data Standards (HL7, FHIR, SNOMED) as the working context rather than a generic management example. The course is taught in three movements. First, students establish the terms and the decision the course is about. Second, they apply the method to a case, dataset, text, or design and compare it with a weaker alternative. Third, they revise the work after feedback and state what the conclusion cannot support. Preparation uses a dataset description, a methods note, and one published evaluation. Seminar time is for the decision, not for reading the materials aloud. Assessment is a project note with the question, the method, the result, and the limitation. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone. HI503-M1 · The question, the unit of analysis, and data quality — Health Data Standards (HL7, FHIR, SNOMED) HI503-M2 · Features, baselines, and error — Health Data Standards (HL7, FHIR, SNOMED) HI503-M3 · Validation, leakage, and what the model must not decide — Health Data Standards (HL7, FHIR, SNOMED) HI503-M4 · Monitoring, drift, and human review — Health Data Standards (HL7, FHIR, SNOMED) HI503-M5 · Interpretation for a non-technical decision maker — Health Data Standards (HL7, FHIR, SNOMED) HI503-M6 · A supervised project with method, result, and limitation — Health Data Standards (HL7, FHIR, SNOMED)	3 · 30 h
HI504	Biostatistics & Epidemiology Biostatistics & Epidemiology (HI504) is a 3-credit course on MSc Health Informatics, with 30 notional learning hours. By the end, students can define a measurable question, fit a method that can be checked, and report where it fails, using Biostatistics & Epidemiology as the working context rather than a generic management example. The course is taught in three movements. First, students establish the terms and the decision the course is about. Second, they apply the method to a case, dataset, text, or design and compare it with a weaker alternative. Third, they revise the work after feedback and state what the conclusion cannot support. Preparation uses a dataset description, a methods note, and one published evaluation. Seminar time is for the decision, not for reading the materials aloud. Assessment is a project note with the question, the method, the result, and the limitation. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone. HI504-M1 · The question, the unit of analysis, and data quality — Biostatistics & Epidemiology HI504-M2 · Features, baselines, and error — Biostatistics & Epidemiology HI504-M3 · Validation, leakage, and what the model must not decide — Biostatistics & Epidemiology HI504-M4 · Monitoring, drift, and human review — Biostatistics & Epidemiology HI504-M5 · Interpretation for a non-technical decision maker — Biostatistics & Epidemiology HI504-M6 · A supervised project with method, result, and limitation — Biostatistics & Epidemiology	3 · 30 h

Year 1 — Systems

Code	Course	Credits · hours
HI505	Electronic Health Records & Implementation Electronic Health Records & Implementation (HI505) is a 3-credit course on MSc Health Informatics, with 30 notional learning hours. By the end, students can describe how people, records, and decisions move through one service, and separate cause from harm, using Electronic Health Records & Implementation as the working context rather than a generic management example. The course is taught in three movements. First, students establish the terms and the decision the course is about. Second, they apply the method to a case, dataset, text, or design and compare it with a weaker alternative. Third, they revise the work after feedback and state what the conclusion cannot support. Preparation uses a pathway description, an incident summary, and an information standard. Seminar time is for the decision, not for reading the materials aloud. Assessment is a brief a service manager could use, with the evidence attached. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone. This course does not confer a licence to practise nursing, medicine, or any other clinical profession. HI505-M1 · Pathway, payment, records, and the bottleneck — Electronic Health Records & Implementation HI505-M2 · Incident, harm, cause, and the change that prevents a repeat — Electronic Health Records & Implementation HI505-M3 · Indicators, privacy, and misuse of a report — Electronic Health Records & Implementation HI505-M4 · Quality, safety, and the limit of the data — Electronic Health Records & Implementation HI505-M5 · Service design for a named population — Electronic Health Records & Implementation HI505-M6 · A service or informatics brief with evidence and a recommendation — Electronic Health Records & Implementation	3 · 30 h
HI506	Health Information Exchange & Interoperability Health Information Exchange & Interoperability (HI506) is a 3-credit course on MSc Health Informatics, with 30 notional learning hours. By the end, students can describe how people, records, and decisions move through one service, and separate cause from harm, using Health Information Exchange & Interoperability as the working context rather than a generic management example. The course is taught in three movements. First, students establish the terms and the decision the course is about. Second, they apply the method to a case, dataset, text, or design and compare it with a weaker alternative. Third, they revise the work after feedback and state what the conclusion cannot support. Preparation uses a pathway description, an incident summary, and an information standard. Seminar time is for the decision, not for reading the materials aloud. Assessment is a brief a service manager could use, with the evidence attached. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone. This course does not confer a licence to practise nursing, medicine, or any other clinical profession. HI506-M1 · Pathway, payment, records, and the bottleneck — Health Information Exchange & Interoperability HI506-M2 · Incident, harm, cause, and the change that prevents a repeat — Health Information Exchange & Interoperability HI506-M3 · Indicators, privacy, and misuse of a report — Health Information Exchange & Interoperability HI506-M4 · Quality, safety, and the limit of the data — Health Information Exchange & Interoperability HI506-M5 · Service design for a named population — Health Information Exchange & Interoperability HI506-M6 · A service or informatics brief with evidence and a recommendation — Health Information Exchange & Interoperability	3 · 30 h
HI507	Clinical Decision Support Systems Clinical Decision Support Systems (HI507) is a 3-credit course on MSc Health Informatics, with 30 notional learning hours. By the end, students can describe how people, records, and decisions move through one service, and separate cause from harm, using Clinical Decision Support Systems as the working context rather than a generic management example. The course is taught in three movements. First, students establish the terms and the decision the course is about. Second, they apply the method to a case, dataset, text, or design and compare it with a weaker alternative. Third, they revise the work after feedback and state what the conclusion cannot support. Preparation uses a pathway description, an incident summary, and an information standard. Seminar time is for the decision, not for reading the materials aloud. Assessment is a brief a service manager could use, with the evidence attached. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone. This course does not confer a licence to practise nursing, medicine, or any other clinical profession. HI507-M1 · Pathway, payment, records, and the bottleneck — Clinical Decision Support Systems HI507-M2 · Incident, harm, cause, and the change that prevents a repeat — Clinical Decision Support Systems HI507-M3 · Indicators, privacy, and misuse of a report — Clinical Decision Support Systems HI507-M4 · Quality, safety, and the limit of the data — Clinical Decision Support Systems HI507-M5 · Service design for a named population — Clinical Decision Support Systems HI507-M6 · A service or informatics brief with evidence and a recommendation — Clinical Decision Support Systems	3 · 30 h
HI508	Health Data Privacy & Governance Health Data Privacy & Governance (HI508) is a 3-credit course on MSc Health Informatics, with 30 notional learning hours. By the end, students can map one named system, write a threat model, and specify the controls that would stop the most likely path, using Health Data Privacy & Governance as the working context rather than a generic management example. The course is taught in three movements. First, students establish the terms and the decision the course is about. Second, they apply the method to a case, dataset, text, or design and compare it with a weaker alternative. Third, they revise the work after feedback and state what the conclusion cannot support. Preparation uses control catalogues, incident write-ups, and a short technical standard. Seminar time is for the decision, not for reading the materials aloud. Assessment is a defensive design with a test plan and a statement of residual risk. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone. HI508-M1 · Assets, trust boundaries, and the adversary model — Health Data Privacy & Governance HI508-M2 · Threat modelling and attack paths — Health Data Privacy & Governance HI508-M3 · Identity, logging, and segmentation — Health Data Privacy & Governance HI508-M4 · Detection, containment, and evidence — Health Data Privacy & Governance HI508-M5 · Residual risk and what a control does not stop — Health Data Privacy & Governance HI508-M6 · Defensive design, test plan, and after-action review — Health Data Privacy & Governance	3 · 30 h

Year 2 — Applied

Code	Course	Credits · hours
HI601	Population Health Analytics Population Health Analytics (HI601) is a 3-credit course on MSc Health Informatics, with 30 notional learning hours. By the end, students can define a measurable question, fit a method that can be checked, and report where it fails, using Population Health Analytics as the working context rather than a generic management example. The course is taught in three movements. First, students establish the terms and the decision the course is about. Second, they apply the method to a case, dataset, text, or design and compare it with a weaker alternative. Third, they revise the work after feedback and state what the conclusion cannot support. Preparation uses a dataset description, a methods note, and one published evaluation. Seminar time is for the decision, not for reading the materials aloud. Assessment is a project note with the question, the method, the result, and the limitation. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone. HI601-M1 · The question, the unit of analysis, and data quality — Population Health Analytics HI601-M2 · Features, baselines, and error — Population Health Analytics HI601-M3 · Validation, leakage, and what the model must not decide — Population Health Analytics HI601-M4 · Monitoring, drift, and human review — Population Health Analytics HI601-M5 · Interpretation for a non-technical decision maker — Population Health Analytics HI601-M6 · A supervised project with method, result, and limitation — Population Health Analytics	3 · 30 h
HI602	Digital Health Innovation Digital Health Innovation (HI602) is a 3-credit course on MSc Health Informatics, with 30 notional learning hours. By the end, students can describe how people, records, and decisions move through one service, and separate cause from harm, using Digital Health Innovation as the working context rather than a generic management example. The course is taught in three movements. First, students establish the terms and the decision the course is about. Second, they apply the method to a case, dataset, text, or design and compare it with a weaker alternative. Third, they revise the work after feedback and state what the conclusion cannot support. Preparation uses a pathway description, an incident summary, and an information standard. Seminar time is for the decision, not for reading the materials aloud. Assessment is a brief a service manager could use, with the evidence attached. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone. This course does not confer a licence to practise nursing, medicine, or any other clinical profession. HI602-M1 · Pathway, payment, records, and the bottleneck — Digital Health Innovation HI602-M2 · Incident, harm, cause, and the change that prevents a repeat — Digital Health Innovation HI602-M3 · Indicators, privacy, and misuse of a report — Digital Health Innovation HI602-M4 · Quality, safety, and the limit of the data — Digital Health Innovation HI602-M5 · Service design for a named population — Digital Health Innovation HI602-M6 · A service or informatics brief with evidence and a recommendation — Digital Health Innovation	3 · 30 h
HI603	MSc Health Informatics Capstone MSc Health Informatics Capstone (HI603) is a 6-credit course on MSc Health Informatics, with 60 notional learning hours. By the end, students can describe how people, records, and decisions move through one service, and separate cause from harm, using MSc Health Informatics Capstone as the working context rather than a generic management example. The course is taught in three movements. First, students establish the terms and the decision the course is about. Second, they apply the method to a case, dataset, text, or design and compare it with a weaker alternative. Third, they revise the work after feedback and state what the conclusion cannot support. Preparation uses a pathway description, an incident summary, and an information standard. Seminar time is for the decision, not for reading the materials aloud. Assessment is a brief a service manager could use, with the evidence attached. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone. This course does not confer a licence to practise nursing, medicine, or any other clinical profession. HI603-M1 · Pathway, payment, records, and the bottleneck — MSc Health Informatics Capstone HI603-M2 · Incident, harm, cause, and the change that prevents a repeat — MSc Health Informatics Capstone HI603-M3 · Indicators, privacy, and misuse of a report — MSc Health Informatics Capstone HI603-M4 · Quality, safety, and the limit of the data — MSc Health Informatics Capstone HI603-M5 · Service design for a named population — MSc Health Informatics Capstone HI603-M6 · A service or informatics brief with evidence and a recommendation — MSc Health Informatics Capstone	6 · 60 h

Code

Course

Credits · hours

HI601

Population Health Analytics

Population Health Analytics (HI601) is a 3-credit course on MSc Health Informatics, with 30 notional learning hours. By the end, students can define a measurable question, fit a method that can be checked, and report where it fails, using Population Health Analytics as the working context rather than a generic management example. The course is taught in three movements. First, students establish the terms and the decision the course is about. Second, they apply the method to a case, dataset, text, or design and compare it with a weaker alternative. Third, they revise the work after feedback and state what the conclusion cannot support. Preparation uses a dataset description, a methods note, and one published evaluation. Seminar time is for the decision, not for reading the materials aloud. Assessment is a project note with the question, the method, the result, and the limitation. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone.

HI601-M1 · The question, the unit of analysis, and data quality — Population Health Analytics
HI601-M2 · Features, baselines, and error — Population Health Analytics
HI601-M3 · Validation, leakage, and what the model must not decide — Population Health Analytics
HI601-M4 · Monitoring, drift, and human review — Population Health Analytics
HI601-M5 · Interpretation for a non-technical decision maker — Population Health Analytics
HI601-M6 · A supervised project with method, result, and limitation — Population Health Analytics

3 · 30 h

HI602

Digital Health Innovation

Digital Health Innovation (HI602) is a 3-credit course on MSc Health Informatics, with 30 notional learning hours. By the end, students can describe how people, records, and decisions move through one service, and separate cause from harm, using Digital Health Innovation as the working context rather than a generic management example. The course is taught in three movements. First, students establish the terms and the decision the course is about. Second, they apply the method to a case, dataset, text, or design and compare it with a weaker alternative. Third, they revise the work after feedback and state what the conclusion cannot support. Preparation uses a pathway description, an incident summary, and an information standard. Seminar time is for the decision, not for reading the materials aloud. Assessment is a brief a service manager could use, with the evidence attached. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone. This course does not confer a licence to practise nursing, medicine, or any other clinical profession.

HI602-M1 · Pathway, payment, records, and the bottleneck — Digital Health Innovation
HI602-M2 · Incident, harm, cause, and the change that prevents a repeat — Digital Health Innovation
HI602-M3 · Indicators, privacy, and misuse of a report — Digital Health Innovation
HI602-M4 · Quality, safety, and the limit of the data — Digital Health Innovation
HI602-M5 · Service design for a named population — Digital Health Innovation
HI602-M6 · A service or informatics brief with evidence and a recommendation — Digital Health Innovation

3 · 30 h

HI603

MSc Health Informatics Capstone

MSc Health Informatics Capstone (HI603) is a 6-credit course on MSc Health Informatics, with 60 notional learning hours. By the end, students can describe how people, records, and decisions move through one service, and separate cause from harm, using MSc Health Informatics Capstone as the working context rather than a generic management example. The course is taught in three movements. First, students establish the terms and the decision the course is about. Second, they apply the method to a case, dataset, text, or design and compare it with a weaker alternative. Third, they revise the work after feedback and state what the conclusion cannot support. Preparation uses a pathway description, an incident summary, and an information standard. Seminar time is for the decision, not for reading the materials aloud. Assessment is a brief a service manager could use, with the evidence attached. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone. This course does not confer a licence to practise nursing, medicine, or any other clinical profession.

HI603-M1 · Pathway, payment, records, and the bottleneck — MSc Health Informatics Capstone
HI603-M2 · Incident, harm, cause, and the change that prevents a repeat — MSc Health Informatics Capstone
HI603-M3 · Indicators, privacy, and misuse of a report — MSc Health Informatics Capstone
HI603-M4 · Quality, safety, and the limit of the data — MSc Health Informatics Capstone
HI603-M5 · Service design for a named population — MSc Health Informatics Capstone
HI603-M6 · A service or informatics brief with evidence and a recommendation — MSc Health Informatics Capstone

6 · 60 h

Career Paths

Clinical Informatics Specialist
Health IT Project Manager
Public Health Data Analyst
EHR Implementation Consultant
Digital Health Product Owner

Programme Highlights

Modules co-designed with practising clinicians
FHIR and openEHR standards in practical labs
Focus on low-resource and global health settings
Partnership case studies from three continents
Ideal for nurses, doctors, and IT professionals transitioning into informatics
Case studies from three continents and varied resource settings
Ideal foundation for health-tech product management roles

Assessment

Modules are assessed through a published mix of coursework, applied projects, and examinations. Exam windows are announced in advance so students in other time zones are not forced into overnight sittings. Alternative arrangements are available where documented.

Admission requirements

Academic entry

Bachelor's degree from an accredited institution (minimum 2:2 or GPA 2.5/4.0)
Healthcare or IT background preferred but not required

English language

English proficiency: IELTS 5.5, TOEFL 46, or equivalent (waived for prior English-medium study)

Documents

Statement of Purpose (500 words minimum) outlining your goals and fit for the programme
Two academic or professional references with contact details
CV or résumé documenting relevant education and professional experience

Programme questions

How long is the MSc Health Informatics?

The published duration is 4 Semesters (2 Years). Teaching language: English. Actual time-to-complete depends on mode and any recognised prior learning.

Can I study this from my country?

You may study this award fully online from your country, or — where published — on campus at IUC. Online study does not require a student visa. Campus study may.

What does it cost?

Degree tuition for this award is published as £0 / tuition-free on the online pathway. Examination or administrative fees may apply at checkout — never an annual tuition invoice. Check the Fees page for any extras.

What are the entry requirements?

Requirements are grouped on this page (academic, English, documents). Equivalent qualifications are considered. English may be waived after prior English-medium study.

How is the programme assessed?

Assessment is typically a mix of coursework, projects, and examinations. Doctoral awards include a thesis or dissertation and an oral examination. Details sit in the programme specification and module outlines.

Will this award be recognised where I live?

Recognition of the award for local employment, professional licence, or ministry attestation is decided by your employer or regulator. Imperial University in Cairo publishes verification pages for certificates. We do not claim automatic equivalence in every country.

How do I apply?

Start an application on this website. Progress is saved from the first step. Admissions: admissions@iucairo.co.uk.

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