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Version: 1.0.1

London Ambulance Service Frequent Callers (LAS)

Dataset

Documentation

Description:
A list of the registered population that meet the LAS Frequent Callers criteria. This includes: - seen and conveyed - seen and treated - treated over the phone

Coverage

Spatial:
United Kingdom,England,London,Brent,Ealing,Hammersmith and Fulham,Harrow,Hillingdon,Hounslow,Kensington and Chelsea,Westminster
Typical Age Range:
0-150
Follow Up:
1 - 10 Years
Pathway:
This dataset contains all LAS Frequent Caller data for patients in London. Each patient will be identified using an unique patient key, patient keys can be used to link to other datasets to understand the patient pathway.

Provenance

Origin

Purposes:
  • Administrative
  • Care
  • Other
Sources:
  • EPR
  • Other
Collection Situations:
Secondary care - Ambulance

Temporal

Accrual Periodicity:
Monthly
Start Date:
31 March 2023
Time Lag:
1-2 weeks

Accessibility

Access

Access Service:
Researchers will have access to a VDI environment with a specific username and password. The researchers will get access to the datasets that is present in the hub's catalogue and would be able to carry out their research within the safe haven. There are restrictions applied which prevents the researchers from taking data out of the safe haven, once the research/analysis is completed the admin team will need to be contacted for taking the analysis off the safe haven.
Access Request Cost:
In Progress
Delivery Lead Time:
1-2 months
Data Controller:
Joint data controller model across North West London
Data Processor:
North West London Integrated Care Board (NWL ICB); North East London Integrated Care Board (NEL ICB); North of England Commissioning Support Unit (NECS)

Usage

Data Use Limitations:
No restriction
Data Use Requirements:
  • Collaboration required
  • Institution-specific restrictions
  • Project-specific restrictions
  • Time limit on use
  • User-specific restriction
Resource Creators:
NHS NWL ICS;,;London SDE

Format and Standards

Vocabulary Encoding Schemes:
LOCAL
Conforms To:
OTHER
Languages:
en
Formats:
  • Excel
  • SQL
  • Tableau
  • R

Observations

Statistical Population
Population Description
Population Size
Measured Property
Observation Date
Events
4147
Count
10 December 2025
Persons
695
Count
10 December 2025