Version: 1.0.0 | Published: 2 Sep 2026 | Updated: 0 days ago
Summary
Documentation
Associated Media:
Description:
Primary Care Medication Statements describe a patient’s current medication status -what medicines they are taking, not taking, stopped, paused, or historically used. They provide a longitudinal, structured view of a patient’s medication history and are essential for safety, continuity, and research into prescribing quality.
The data set includes:
1. Active and historical medications:
- Medicines currently being taken
- Past medications (acute or repeat)
- Repeat medications with review dates
- Stopped or paused medicines
2. Structured medication details including:
- Drug name (SNOMED/dm+d)
- Strength, dose, route, frequency
- Quantity and duration
- Whether the medication is acute, repeat, or repeat dispensing
4. Metadata
- Start and stop dates
- Authorising clinician
- Practice identifiers
- Status flags (active, discontinued, suspended)
What Medication Statements Exclude:
- They do not confirm dispensing (that is NHSBSA data).
- They may not always include a coded indication.
Researchers would find the below most important or relevant when using Medication Statements:
1. Medication safety
Medication statements allow researchers to identify:
- High risk medicines (e.g., DOACs, opioids)
- Missing monitoring (e.g., blood tests for ACE inhibitors)
- Unsafe combinations
- Long term use of medicines requiring review
This aligns with medicines management guidance emphasising safe prescribing and monitoring.
2. Treatment pathways and disease management
Medication statements show:
- Treatment initiation
- Step up/step down therapy
- Long term condition management (diabetes, asthma, hypertension)
- Medication adherence patterns (inferred from repeat issues)
3. Inequalities in prescribing
Linked demographics allow analysis of Variation in treatment initiation, Differences in long term condition management, Disparities in access to medicines.
4. Workforce and prescribing roles
Medication statements help researchers understand:
- GP vs pharmacist vs nurse prescribing
- Impact of multidisciplinary teams
- Variation in prescribing quality across roles
5. Linking across datasets
Medication statements can be linked to Observations (clinical measurements), Appointments, Prescriptions, Dispensing data, Hospital datasets (SUS)
This enables full pathway research from intention → issue → active medication → outcome.
Using Medication Statements, researchers can:
- Improve medication safety by identifying risky or unmonitored medicines
- Enhance chronic disease management through longitudinal medication histories
- Reduce inequalities by analysing variation in prescribing and monitoring
- Support personalised care with detailed medication profiles
- Strengthen continuity of care across GP, pharmacy, and hospital settings
In Pipeline:
Available
Coverage
Spatial:
- United Kingdom
- England
- London
Typical Age Range Min:
0
Typical Age Range Max:
150
Material Type:
None/not available
Follow Up:
> 10 Years
Pathway:
This dataset contains all Primary Care Prescription Statements for London
patients. Each patient will be identified using an unique patient key, this can
be used to link to other London SDE datasets that will help track the patient
pathway.
Provenance
Origin
Purpose:
- Administrative
- Care
- Other
Dataset Type:
- Health and disease
- Treatments/Interventions
Dataset Sub-Type:
- Others
- Others
Source:
EPR
Collection Source:
Primary care - Clinic
Image Contrast:
No
Temporal
Publishing Frequency:
Monthly
Distribution Release Date:
01 September 2026
Start Date:
01 April 2000
Time Lag:
1-2 weeks
Accessibility
Access
Access Rights:
London Secure Data Environment Enquiry Form
Access Service Category:
TRE/SDE
Access Service:
Researchers will have access to a secure workspace via an airlocked Azure
Virtual Desktop with a specific username and password, MFA (multi-factor
authentication) and OAUTH (open authentication). Researchers will get specific
access to a relevant subset of the datasets that are present in the SDE
catalogue for their project and will be able to carry out their research within
the safe haven. There are restrictions applied which prevent the researchers
from taking data out of the safe haven. Once the research is completed the
London SDE admin team will need to be contacted for any requests to egress
summary analysis out of the safe haven which will not breach secure data
environment disclosure control standards.
Access Request Cost:
Access costs will be determined on a project-by-project basis and will depend on
the specific data requirements, platform setup, and any additional services
needed to deliver the project successfully.
Delivery Lead Time:
1-2 months
Data Controller:
Participating London health care organisations act as Joint Data Controllers
within the London SDE. These organisations include for example GP Practices and
Acute Providers from across London.
Data Processor:
The data processor for the London Secure Data Environment (SDE) is primarily
managed by OneLondon, a partnership of London's five integrated care systems
(ICSs) and three health innovation networks. NHS North East London ICB hosts
OneLondon and operates the London Data Service (LDS) as a data processor on
behalf of those organisations, whilst Imperial College Healthcare NHS Trust
hosts the London Analytics Platform (LAP), with Imperial NHS Trust acting as the
data processor for data processing activities undertaken within the platform.
Jurisdiction:
United Kingdom of Great Britain and Northern Ireland
Usage
Data Use Limitation:
No restriction
Data Use Requirements:
- Collaboration required
- Institution-specific restrictions
- Project-specific restrictions
- Time limit on use
- User-specific restriction
Resource Creator:
London SDE
Format and Standards
Vocabulary Encoding Scheme:
- NHS NATIONAL CODES
- LOCAL
- SNOMED CT
Conforms To:
- NHS DATA DICTIONARY
- LOCAL
Language:
English
Format:
Text
Enrichment and Linkage
Investigations:
Linkable Datasets
PID
Title
URL
Each patient will be identified by an unique patient key that can be used to link to all other datasets available within London SDE Platform
Observations
Statistical Population
Population Description
Population Size
Measured Property
Observation Date
Events
505973200
Count
02 September 2026
Persons
Distinct Patient Count
9535090
Count
02 September 2026
Origin
Name:
London SDE