Towards a scientific workflow methodology for primary care database studies.
We describe the challenges of conducting studies based on mining large-scale primary care databases, namely data integration, data set definition, result reproducibility and reusability. These correspond to higher-level informatics challenges of automation, provenance capture and component integration. We provide a high-level view of the informatics infrastructure that addresses these challenges through a generic workflow-based e-Science middleware, and describe our experiences using the system to investigate differences in the health status of patients with diabetes before and after the national introduction of the UK GP contract in 2004.
Curcin
Vasa
V
Department of Computing, Imperial College London, London SW7 2AZ, UK. vasa.curcin@imperial.ac.uk
Bottle
Alex
A
Molokhia
Mariam
M
Millett
Christopher
C
Majeed
Azeem
A
D057225:Data Mining / Q000592:standards / Q000706:statistics & numerical data; D016208:Databases, Factual / Q000592:standards / Q000706:statistics & numerical data*; D003922:Diabetes Mellitus, Type 1 / Q000188:drug therapy*; D003924:Diabetes Mellitus, Type 2 / Q000188:drug therapy*; D005260:Female; D006801:Humans; D008297:Male; D008490:Medical Informatics / Q000379:methods / Q000592:standards / Q000706:statistics & numerical data; D011320:Primary Health Care / Q000592:standards / Q000706:statistics & numerical data*; D006113:United Kingdom; D057188:Workflow