Temporal growth and geographic variation in the use of laboratory tests by NHS general practices: using routine data to identify research priorities.

Background: Laboratory tests are extensively used for diagnosis and monitoring in UK primary care. Test usage by GPs, and associated costs, have grown substantially in recent years.
Aim: This study aimed to quantify temporal growth and geographic variation in utilisation of laboratory tests.
Design and Setting: Retrospective cohort study using data from general practices in the UK.
Method: Data from the General Practice Research Database, including patient demographics, clinical details, and laboratory test results, were used to estimate rates of change in utilisation between 2005 and 2009, and identify tests with greatest inter-regional variation, by fitting random-effects Poisson regression models. The study also investigated indications for test requests, using diagnoses and symptoms recorded in the 2 weeks before each test.
Results: Around 660 000 tests were recorded in 230 000 person-years of follow-up. Test use increased by 24.2%, from 23 872 to 29 644 tests per 10 000 person-years, between 2005 and 2009. Tests with the largest increases were faecal occult blood (121%) and C-reactive protein (86%). There was substantial geographic variation in test utilisation; GPs in some regions requested tests such as plasma viscosity and cardiac enzymes at a rate more than three times the national average.
Conclusion: Increases in the use of laboratory tests have substantial resource implications. Rapid increases in particular tests may be supported by evidence-based guidelines, but these are often vague about who should be tested, how often, and for how long. Substantial regional variation in test use may reflect uncertainty about diagnostic accuracy and appropriate indications for the laboratory test. There is a need for further research on the diagnostic accuracy, therapeutic impact, and effect on patient health outcomes of the most rapidly increasing and geographically variable tests.