The Intego database: background, methods and basic results of a Flemish general practice-based continuous morbidity registration project

BackgroundIntego is the only operational computerized morbidity registration network in Belgium based on general practice data. Intego collects data from over 90 general practitioners. All the information is routinely collected in the electronic health record during daily practice.MethodsIn this article we describe the design and methods used within the Intego network together with some of its basic results. The collected data, the quality control procedures, the ethical-legal aspects and the statistical procedures are discussed.ResultsIntego contains longitudinal information on 285 357 different patients, corresponding to over 2.3% of the Flemish population representative in terms of age and sex. More than 3 million diagnoses, 12 million drug prescriptions and 29 million laboratory tests have been recorded.ConclusionsIntego enables us to present and compare data on health parameters, incidence and prevalence rates, laboratory results, and prescribed drugs for all relevant subgroups on a routine basis and is unique in Belgium.

[1]  Carla Truyers,et al.  Higher Incidence of Common Diagnoses in Patients with Low Back Pain in Primary Care , 2012, Pain practice : the official journal of World Institute of Pain.

[2]  Geert Goderis,et al.  Quality assessment of automatically extracted data from GPs' EPR. , 2012, Studies in health technology and informatics.

[3]  Bert Aertgeerts,et al.  The use of human tissue in epidemiological research; ethical and legal considerations in two biobanks in Belgium , 2010, Medicine, health care, and philosophy.

[4]  D. Fleming,et al.  European primary care surveillance networks: their structure and operation. , 2006, Family practice.

[5]  D. H. de Bakker,et al.  Tweede Nationale Studie naar ziekten en verrichtingen in de huisartspraktijk: klachten en aandoeningen in de bevolking en in de huisartspraktijk. , 2004 .

[6]  D. M. Fleming,et al.  Electronic medical records: recommendations for routine. Report of the eHID (Electronic Health Indicator Data Project): the eHID project recommendations. , 2007 .

[7]  M Soledad Cepeda,et al.  Optimal matching with a variable number of controls vs. a fixed number of controls for a cohort study. trade-offs. , 2003, Journal of clinical epidemiology.

[8]  H Jick,et al.  Validation of information recorded on general practitioner based computerised data resource in the United Kingdom. , 1991, BMJ.

[9]  Bert Aertgeerts,et al.  Computerized general practice based networks yield comparable performance with sentinel data in monitoring epidemiological time-course of influenza-like illness and acute respiratory illness , 2010, BMC family practice.

[10]  Bert Aertgeerts,et al.  Serious infections in children: an incidence study in family practice , 2006, BMC family practice.

[11]  Bert Aertgeerts,et al.  Malignant melanoma: to screen or not to screen? An evaluation of the Euromelanoma Day in Belgium. , 2010, European journal of dermatology : EJD.

[12]  M Pringle,et al.  Assessment of the completeness and accuracy of computer medical records in four practices committed to recording data on computer. , 1995, The British journal of general practice : the journal of the Royal College of General Practitioners.

[13]  Stefaan Bartholomeeusen,et al.  Quality of antibiotic prescription during office hours and out-of-hours in Flemish primary care, using European quality indicators , 2014, The European journal of general practice.

[14]  Bert Aertgeerts,et al.  Incident somatic comorbidity after psychosis: results from a retrospective cohort study based on Flemish general practice data , 2011, BMC family practice.

[15]  Graham Watt,et al.  William Pickles lecture. General practice and the epidemiology of health and disease in families. , 2004, The British journal of general practice : the journal of the Royal College of General Practitioners.

[16]  N. Breslow,et al.  Statistical methods in cancer research. Volume II--The design and analysis of cohort studies. , 1987, IARC scientific publications.

[17]  M. Graffar [Modern epidemiology]. , 1971, Bruxelles medical.

[18]  Frank Buntinx,et al.  Intego in de praktijk (deel 7): Incidentie van melanomen en niet-melanoomachtige huidkankers , 2005 .

[19]  M. Van Ranst,et al.  Association between recent herpes zoster but not herpes simplex infection and subsequent risk of malignancy in women: a retrospective cohort study , 2013, Epidemiology and Infection.

[20]  Peter Croft,et al.  Quality of morbidity coding in general practice computerized medical records: a systematic review. , 2004, Family practice.

[21]  Timothy L. Lash,et al.  Comprar Modern Epidemiology | Timothy L. Lash | 9781451190052 | Lippincott Williams & Wilkins , 2012 .

[22]  Sander Greenland,et al.  Modern Epidemiology 3rd edition , 1986 .

[23]  Geert Goderis,et al.  Long-term evolution of renal function in patients with type 2 diabetes mellitus: a registry-based retrospective cohort study , 2013, BMJ Open.

[24]  Ralph B D'Agostino,et al.  Estimating treatment effects using observational data. , 2007, JAMA.

[25]  F Buntinx,et al.  Medisch-deontologische en juridische aspecten van algemene en continue morbiditeitsregistratie , 2006 .