Healthcare administrators
Understand what happens to operational information after it is recorded and why accurate source data matters.
Part of a technology-enabled workforce-readiness model.MedX combines structured learning with a functional healthcare operations simulator already used by learners. Explore the working simulator →
Healthcare informatics pathway
Understand the information behind the work. Then work with the data.
Covered in the 8-week programme
Learn how healthcare information is recorded, standardised, classified, moved, stored, governed and checked, then apply that knowledge through realistic synthetic data, quality and informatics scenarios within the MedX workforce-readiness environment.
From operational work to trusted information
Follow healthcare information from operational activity to usable insight.
Healthcare informatics does not begin in a dashboard. It begins with activity recorded in operational and clinical systems.
This pathway develops that understanding and then connects it to practical activity: tracing synthetic information, checking data quality, interpreting structures and explaining how source records affect downstream reporting and analysis.
Workforce-readiness pathway
Connect operational systems, standards, data quality and reporting
Build on operational pathway knowledge by understanding how healthcare information moves through systems, standards, governance, storage and analytical processes, and practise reasoning about that journey.
The information lifecycle
See how the pieces connect
The pathway follows healthcare information from source systems through standards and data flows into analytical structures, reporting and decision support.
Clinical & operational systems
→
Terminology & classifications
→
Data flows
→
Data storage
→
Analytical models
→
Reports & insight
Data quality, governance, confidentiality, definitions and auditability matter throughout the lifecycle.
13-module curriculum
Build healthcare data and informatics capability
The curriculum develops knowledge across terminology, classifications, systems, datasets, governance and analytical structures, providing the theory needed to reason about healthcare information in practice.
01
SNOMED CT
Structured clinical terminology and consistent recording.
Structured clinical terminology and consistent recording.
02
ICD-10
Diagnosis and health-condition classification.
Diagnosis and health-condition classification.
03
OPCS-4
Classification of interventions and procedures.
Classification of interventions and procedures.
04
Healthcare Data Flows
How information moves between operational, reporting and analytical processes.
How information moves between operational, reporting and analytical processes.
05
NHS Data Model & Dictionary
Definitions, structures and common data concepts.
Definitions, structures and common data concepts.
06
Commissioning Data Sets
Structured secondary-care activity information.
Structured secondary-care activity information.
07
Hospital Episode Statistics
Understanding national hospital-activity data.
Understanding national hospital-activity data.
08
Clinical Coding Fundamentals
Coding workflow, classifications and quality awareness.
Coding workflow, classifications and quality awareness.
09
Data Warehousing
Bringing information together for reporting and analysis.
Bringing information together for reporting and analysis.
10
Power BI for Healthcare Analytics
Data preparation, modelling, measures and reporting concepts.
Data preparation, modelling, measures and reporting concepts.
11
Information Governance
Responsible, confidential and secure use of healthcare information.
Responsible, confidential and secure use of healthcare information.
12
Electronic Patient Record Systems
Understanding where operational and clinical information is created.
Understanding where operational and clinical information is created.
13
RTT & Operational Data
Connecting pathway activity, PTLs, waiting lists, validation and reporting.
Connecting pathway activity, PTLs, waiting lists, validation and reporting.
What you’ll develop
Understand the relationships behind healthcare information
The aim is not simply to recognise terminology. Learners should develop a clearer understanding of how systems, standards, datasets and reporting processes relate to one another.
✓
Terminology and classification
Understand the different roles of terminology and classifications such as SNOMED CT, ICD-10 and OPCS-4.
Understand the different roles of terminology and classifications such as SNOMED CT, ICD-10 and OPCS-4.
✓
Healthcare data flows
Trace the broad journey from source systems through datasets, storage and reporting.
Trace the broad journey from source systems through datasets, storage and reporting.
✓
Data-quality awareness
Recognise how missing, duplicated, inconsistent or incorrectly mapped information can affect downstream use.
Recognise how missing, duplicated, inconsistent or incorrectly mapped information can affect downstream use.
✓
Governance awareness
Understand why confidentiality, security, lawful processing and responsible information use matter.
Understand why confidentiality, security, lawful processing and responsible information use matter.
✓
Reporting context
Understand why dashboards and measures depend on reliable source information, definitions and modelling.
Understand why dashboards and measures depend on reliable source information, definitions and modelling.
Core principle
A dashboard is only as useful as the information underneath it.
Informatics connects operational activity with the standards, structures and governance needed to turn recorded information into something that can be interpreted responsibly.
Practical learning
Move from definitions to practical informatics work
Structured activities move the pathway beyond definitions. Learners can trace fictional information, investigate quality issues, interpret structures and explain how healthcare data changes as it moves through operational, information and analytical stages.
01
Understand
Learn the terminology, standards, classifications, systems and datasets used across healthcare information workflows.
02
Trace
Follow fictional information from source records through structured data flows and analytical processes.
03
Check
Identify potential data-quality, mapping, duplication, consistency and governance issues.
04
Explain
Build the ability to describe how source information, definitions and modelling affect reports and decisions.
SOURCE ACTIVITY
Operational records
Fictional registrations, referrals, appointments, pathways and waiting-list activity.
Definitions
Quality
Standards
INFORMATION LAYER
Structured healthcare data
Trace fields, classifications, mappings, transformations and quality issues.
Storage
Models
Governance
DOWNSTREAM USE
Reporting & analysis
Understand how source quality and definitions affect measures, dashboards and decisions.
Practical informatics work
Work with the information behind healthcare operations
MedX is designed to connect operational activity with the information processes behind it. Learners can use fictional records and synthetic data to understand how healthcare information is created, checked, structured and prepared for downstream use.
✓
Trace information
Follow selected information from operational source activity into structured data and reporting contexts.
Follow selected information from operational source activity into structured data and reporting contexts.
✓
Investigate data quality
Identify missing, inconsistent, duplicated or incorrectly represented synthetic information.
Identify missing, inconsistent, duplicated or incorrectly represented synthetic information.
✓
Interpret standards and structures
Connect terminology, classifications, definitions and data structures to their role in healthcare information.
Connect terminology, classifications, definitions and data structures to their role in healthcare information.
✓
Explain downstream impact
Describe how source information and quality issues can affect reporting, analysis and operational decisions.
Describe how source information and quality issues can affect reporting, analysis and operational decisions.
From informatics to analytics
Why data understanding comes before analytics
Analytics becomes more meaningful when learners understand where the information came from, what the fields represent, how the data was structured and what quality limitations may exist.
This pathway therefore provides the informatics capability needed for the next MedX stage: Healthcare Data Analytics.
Explore the Next Pathway
Analytical progression
Source
→
Quality
→
Structure
→
Model
→
Analyse
→
Communicate
The next stage develops practical analytical thinking and reporting capability using healthcare-focused scenarios.
Demonstrate capability
Show how you reason about healthcare information
MedX is being designed to distinguish between knowledge someone has learned and capability they have demonstrated through practical work. In informatics, that means going beyond recognising terminology to showing how information is traced, checked, interpreted and explained.
The planned Capability Evidence Engine is intended to capture measurable performance from relevant activities and help organise practical development into a clearer capability profile.
Explore capability evidence →
Illustrative evidence journey · Capability Evidence Engine planned
Learn → Practise → Demonstrate → Apply
✓
Learned
Understand systems, terminology, classifications, data flows and governance.
Understand systems, terminology, classifications, data flows and governance.
✓
Practised
Trace synthetic information and investigate realistic data-quality scenarios.
Trace synthetic information and investigate realistic data-quality scenarios.
✓
Demonstrated
Produce practical work that can support evidence of informatics reasoning and applied capability.
Produce practical work that can support evidence of informatics reasoning and applied capability.
✓
Applied
Organise relevant evidence for portfolios, applications, interviews and progression.
Organise relevant evidence for portfolios, applications, interviews and progression.
Capability measurement is developing. Synthetic MedX activity is training and capability-development evidence, not employment experience.
Who this pathway can support
Build healthcare information capability for operational, informatics and analytical work
Aspiring informatics professionals
Build practical understanding of healthcare information, systems, standards, datasets, governance and data-quality reasoning.
Developing analysts
Strengthen understanding of the operational and information context behind healthcare datasets and reports.
Digital-health learners
Develop a broader view of how healthcare systems, structured information and analytical processes interact.
Continue the MedX pathway
Turn healthcare information into analysis
Once you understand where healthcare information comes from and how it is structured, the next stage is learning how to interrogate, analyse and communicate that information effectively.
Continue to Data Analytics
MedX progression
Theory → Information work → Analytics → Capability evidence → Career application
Healthcare Data & Informatics bridges operational healthcare work and analytical capability within the wider MedX workforce-readiness pathway.
CONNECTED LEARNING & PRACTICE
Part of the MedX learning experience.
Build relevant knowledge, explore practical healthcare scenarios and develop examples of work you can explain. The MedX approach connects learning with practice and reflection.
Realistic practice, responsibly designed.
Simulation activities use fictional training records and are not NHS employment or clinical placements. MedX is developing further technology to help structure capability evidence.
Build healthcare data and informatics capability.
Understand the systems, standards and structures behind healthcare information, then apply that knowledge through realistic synthetic data and informatics work.