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 24 months, 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.
Programme Structure & Delivery
Coursework
Interactive modules, weekly readings, recorded and live seminars, and collaborative discussions with peers worldwide.
Assessment
Module assignments, proctored examinations, and capstone projects designed to demonstrate mastery of the field.
Learning Outcomes
- ✦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
Career Pathways
- ✦Clinical Informatics Specialist
- ✦Health IT Project Manager
- ✦Public Health Data Analyst
- ✦EHR Implementation Consultant
- ✦Digital Health Product Owner
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.
Curriculum
Year 1 — Foundations
HI501Introduction to Health Informatics- 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 creditsHI502Clinical Workflow & Process Analysis- 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 creditsHI503Health Data Standards (HL7, FHIR, SNOMED)- 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 creditsHI504Biostatistics & Epidemiology- 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 creditsYear 1 — Systems
HI505Electronic Health Records & Implementation- 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 creditsHI506Health Information Exchange & Interoperability- 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 creditsHI507Clinical Decision Support Systems- 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 creditsHI508Health Data Privacy & Governance- 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 creditsYear 2 — Applied
HI601Population Health Analytics- 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 creditsHI602Digital Health Innovation- 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 creditsHI603MSc Health Informatics Capstone- 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 creditsAdmission 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 24 months. Teaching language: English. Actual time-to-complete depends on mode and any recognised prior learning.
Can I study this from my country?+
This is a fully online award. You study from your country. No student visa and no campus relocation are required.
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. Durham University 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@durhm.co.uk.
