Andersen, Christen Bertel L7; Siersma, V.7; Karlslund, W.7; Hasselbalch, Hans Carl5; Felding, P.6; Bjerrum, O.W.8; Olivarius, Niels de Fine7
1 Forskningsenheden for Almen Praksis, Eksterne centre, Københavns Universitet2 Section of General Practice, Department of Public Health, Faculty of Health and Medical Sciences, Københavns Universitet3 Department of Public Health, Faculty of Health and Medical Sciences, Københavns Universitet4 Department of Clinical Medicine, Department of Clinical Medicine, Faculty of Health and Medical Sciences, Københavns Universitet5 Klinisk Institut6 unknown7 Forskningsenheden for Almen Praksis, Eksterne centre, Københavns Universitet8 Department of Clinical Medicine, Department of Clinical Medicine, Faculty of Health and Medical Sciences, Københavns Universitet
BACKGROUND: The differential blood cell count provides valuable information about a person's state of health. Together with a variety of biochemical variables, these analyses describe important physiological and pathophysiological relations. There is a need for research databases to explore associations between these parameters, concurrent comorbidities, and future disease outcomes. METHODS AND RESULTS: The Copenhagen General Practitioners' Laboratory is the only laboratory serving general practitioners in the Copenhagen area, covering approximately 1.2 million inhabitants. The Copenhagen General Practitioners' Laboratory has registered all analytical results since July 1, 2000. The Copenhagen Primary Care Differential Count database contains all differential blood cell count results (n=1,308,022) from July 1, 2000 to January 25, 2010 requested by general practitioners, along with results from analysis of various other blood components. This data set is merged with detailed data at a person level from The Danish Cancer Registry, The Danish National Patient Register, The Danish Civil Registration System, and The Danish Register of Causes of Death. CONCLUSION: This paper reviews methodological issues behind the construction of the Copenhagen Primary Care Differential Count database as well as the distribution of characteristics of the population it covers and the variables that are recorded. Finally, it gives examples of its use as an inspiration to peers for collaboration.