Version: 1.0.0 | Published: 2 Sep 2026 | Updated: 0 days ago
Summary
Documentation
Associated Media:
Description:
Primary Care Medication Orders represent the structured record of medicines a clinician intends to prescribe - the “order” before it becomes a final prescription (the instruction to prescribe a medicine, recorded before dispensing). They capture rich clinical context around prescribing decisions and are extremely valuable for research into safety, appropriateness, and patient outcomes.
Primary Care Medication Orders provide a uniquely detailed view of prescribing intent - essential for improving safety, effectiveness, and equity in primary care.
The data set includes:
1. Medication details including:
- Drug name (coded, usually via dm+d/SNOMED)
- Formulation, strength, dose
- Quantity requested
- Route of administration
- Frequency and duration
2. Clinical context such as Linked problem/diagnosis (if coded), Reason for prescribing (where recorded), Associated observations (e.g., BP, HbA1c), Linked care plan or template fields.
3. Metadata including
- Ordering clinician
- Practice and organisation identifiers
- Date/time of order creation
- Whether the order was acute, repeat, or repeat dispensing
- Status (issued, cancelled, amended)
4. Repeat medication management such as Repeat authorisation details, Review dates, Flags for monitoring requirements, History of previous orders.
What Medication Orders excludes:
- They do not confirm that a medicine was dispensed (that is captured in NHSBSA dispensing data).
- They may not always include a coded indication.
- They exclude non medication orders (e.g., referrals, tests).
Researchers would find the below most important or relevant when using Medication Orders:
1. Understanding prescribing intent
Medication orders show:
- Why a clinician intended to prescribe a medicine
- Changes in prescribing decisions (e.g., cancelled orders)
- Early signals of treatment escalation or de escalation
This is richer than dispensing data alone.
2. Safety and monitoring
Orders allow researchers to:
- Identify high risk medicines requiring monitoring
- Detect unsafe combinations at the point of prescribing
- Study whether monitoring (e.g., blood tests) occurred before issuing repeats
3. Chronic disease management
Medication orders reveal:
- Treatment initiation
- Step up/step down therapy
- Adherence to clinical guidelines
- Patterns in long term condition management (e.g., diabetes, asthma, hypertension)
4. Inequalities in prescribing
Linked demographics allow:
- Studying variation in prescribing by ethnicity, age, deprivation
- Identifying groups with lower access to appropriate medicines
5. Workforce and prescribing roles
Orders show:
- GP vs pharmacist vs nurse prescribing
- Impact of multidisciplinary teams
- How workforce mix affects prescribing quality
6. Linking across datasets
Medication orders can be linked to Observations, Appointments, Prescriptions, Dispensing data, Hospital datasets (SUS).
This enables full pathway research from intention → issue → dispense → outcome.
Using Medication Orders, researchers can:
- Improve medication safety by analysing risky prescribing patterns
- Strengthen guideline adherence through monitoring of prescribing intent
- Reduce inequalities by identifying variation in treatment initiation
- Support personalised care with detailed longitudinal prescribing histories
- Improve chronic disease outcomes by studying therapy changes over time
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 Orders 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
1904923706
Count
02 September 2026
Persons
Distinct Patient Count
9509504
Count
02 September 2026
Origin
Name:
London SDE