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Version: 1.0.0 | Published: 8 Oct 2024 | Updated: 229 days ago

Deriving and validating a clinical prediction rule for the diagnosis of asthma in primary care

Dataset

Summary

DOI Name:
10.17605/OSF.IO/FU4GN19

Documentation

Description:

Asthma is common in the UK, causing considerable illness, healthcare usage, and public expense. Accurate diagnosis is essential for good asthma management. Yet, uncertainty about the best way to diagnose asthma can lead to missed diagnoses and under-treatment, or over-diagnosis leading to unnecessary treatment and healthcare costs. To make it easier for doctors and nurses to identify and interpret important information gathered from patient suspected of having asthma, existing research database "Avon Longitudinal Study of Parents and Children" (ALSPAC) will be used to identify feautres which predict who has asthma. This data contains information on a wide-range of socioeconomic, lifestyle, clinical, anthropometric and biological data on all family members repeatedly. The rule will be tested on anonymous routine data from UK GP"s "Optimum Patient Care Research Database".

ALPSAC: http://www.bristol.ac.uk/alspac OPCRD: https://opcrd.co.uk/

Coverage

Spatial:
United Kingdom
Typical Age Range:
0-24

Provenance

Origin

Purposes:
Study
Collection Situations:
Other

Temporal

Accrual Periodicity:
Other
Distribution Release Date:
30 June 2018
Start Date:
01 April 1991
End Date:
30 June 2018
Time Lag:
Not applicable

Accessibility

Access

Access Rights:
To be determined upon data access request
Access Service:
To be determined upon data access request
Delivery Lead Time:
Not applicable
Jurisdictions:
  • GB-ENG
  • GB-SCT
  • GB-WLS
Data Controller:
BREATHE

Usage

Data Use Limitations:
General research use
Resource Creators:
University of Bristol (ALSPAC) Optinum Patient Care (OPCRD)

Format and Standards

Vocabulary Encoding Schemes:
LOCAL
Languages:
en