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Understanding the UK GP Research Databases: GPRD and THIN Insights into Health Improvement

This introduction to the UK General Practice Research Database (GPRD) and The Health Improvement Network (THIN) explores their value as significant health data sources. Covering over 6.5 million individuals and more than 350 GP practices, these databases provide insights into diagnoses, biochemistry, risk factors, and prescribed drugs. While GPRD and THIN present opportunities for population-based studies and real-life data collection, they also have limitations like incomplete cancer staging and limited lifestyle information. Understanding their strengths and weaknesses is crucial for health research.

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Understanding the UK GP Research Databases: GPRD and THIN Insights into Health Improvement

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  1. Introduction to UK GO dataGPRD: General Practice Research DatabaseTHIN: Health Improvement Network Some new data too

  2. Records from GP routine records • GPRD=THIN (almost) • >6% of the UK population • >350 GP practices • >6½ million individual people Data sources

  3. Largest UK employer―4th largest employer in world • 1.7 million employees • 40,000 GPs • 10,000 GP practices • GPs see 140 patients per week UK NHS―National Health Service

  4. Diagnoses: GP and some hospital • Biochemistry: HbA1c etc • Risk factors: weight, smoking etc • Family history (some) • Drugs (all prescribed drugs) • Outpatient contacts • Free text • GPRD only….linked data: • Cancer registry data • Hospital inpatient data Data content

  5. Quality: representativeness

  6. Quality: completeness

  7. Quality: completeness

  8. Size―over 5% UK population • Nationally representative • Fast―information already collected • Frequent collections • All prescribable drugs • Population based • Study design flexibility • ‘Real Life’ data―collected during normal GP visit • Link to GP and patient for additional information Strengths

  9. £cost! • No direct link to secondary care data (THIN) • No direct link of prescriptions to diagnoses - temporal implied link • Limited information on OTC medications • Limited data on lifestyles, diet etc • Not dispensed prescriptions • Limited information on hospital prescribing • Some medications only administered by specialists Weaknesses

  10. Details of the cancer diagnosis variable • No systematic cancer staging data • Metastatic cancer: have to infer • Hospital cancer treatments not known Weaknesses re Ca.

  11. New data! Survival after incident cancer: diabetes vs. non-diabetes

  12. Incident cancers by cancer site

  13. Incident cancers by DM treatment

  14. Mean survival by Ca. site (years)

  15. Δ mean survival by Ca. site (years)

  16. Cumulative mortality (crude) DM Non-DM

  17. Cumulative mortality (adjusted) DM Non-DM Adjusted: age, sex, smoking, morbidity

  18. HR DM vs-N-DM (Cox)

  19. adjHR: DM vs N-DM (=1) by treatment

  20. Cum-mortality: ± metformin (adjusted) Met- Met- Met+ Met+ Exposed in first 3 months Exposed anytime aft Ca. diag HR=0.72; 0.68-0.76; p<0.00001 HR=0.83; 0.78-0.89; p<0.00001

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