Table 2 Results of the assessment of the existing health data sources for T2D care
Type | Collected/owned by (part of project) | Period | Population (representativeness) | Content | Strengths | Limitations |
|---|---|---|---|---|---|---|
PATIENT SURVEY DATA | ||||||
Health Interview survey (HIS)a | Sciensano (Belgian Institute for Health) | Repeated cross-sectional: every 4 years since 1997 | Representative sample of the Belgian population (N = +/−10,000 respondents) | medication use, health care use and costs, health behavior (physical activity, diet, smoking, alcohol), BMI, diagnostic information | -Representative for the population -Extensive lifestyle and sociodemographic info | -Small numbers of T2D patients (6,2%) -Self-reported data, recall bias -Selection and sample bias -The most severe and institutionalized patients are excluded -Time lag: data of 2018 was available in 2021 -Cross-sectional data -No clinical data -No information about type of GP-practice |
Belgian Health Examination study (BELHES)b | Cross-sectional: 2018 | Representative subsample of the HIS (N = +/1200 respondents) | blood and urine test, blood pressure measure, BMI | -Clinical data -Can be linked to HIS data | -Small sample (+ same limitations HIS data) | |
HEALTH PROFESSIONAL SURVEY DATA | ||||||
Sentinel Network of General Practitioners (surveillance network)c | A network of Registered GPs, coordinated by Sciensano | Longitudinal: since 1979 Periodic modules to monitor one or more specific illness problems | A network of 125 practices (their patient population covers 1–1,5% of the Belgian population) | sociodemographics, treatment and morbidity data | -Representative for Belgian GP workforce -Able to study the evolution and epidemiology of certain diseases | -Quality of data strongly depends on the reporting quality of GPs -The most recent T2D module was in 2010 |
(REGISTER) DATA | ||||||
Belgian Diabetes Register d | Diabetes Liga | Longitudinal: since 1997 | New patients < 40 years old diagnosed with T1D | sociodemographics, clinical data | -Clinical data -Longitudinal | -Only T1D patients (not the target population of this study) |
IQED: Initiative for Quality Improvement & Epidemiology in Diabetes e | Hospital based data requested by Sciensano for audit (Surveillance of the convention for diabetes self-regulation) | Repeated cross-sectional retrospective study design (every 18 months): since 2001 | Patients in a diabetes care trajectory: +/−  100 diabetic centres treated +/−  120,000 patients -each time 10% of the population is sampled | clinical hospital data, socio-demographics, type of diabetes and complications, diabetes treatment, health examination data | -Clinical data -Focus on quality indicators -Based on principles of DiabCare | -Only type 1 and type 2 diabetic patients treated with 2 or more insulin injections per day (only a small part of the target population of this study) |
PATIENT RECORD DATA | ||||||
Patients records f | GPs in their practices | Longitudinal: period depends on GP-practice | Patient-population of GP | Depending on GP (diagnostic info, health services, medication, health behavior, severity of diseases, comorbidities, familial anamnesis, RISC score, ….) | -Data can be very comprehensive (BMI, blood pressure, waist circumcise, smoking behavior, etc.) -Diagnostic, health care use, medication prescription and clinical data (GPs have easily access to the lab data of their patients) | -Several software systems: no standardized way of registration -Low reporting quality & large differences between practices -Difficult & time-consuming to extract the data (a lot of efforts for GPs and in particular if there is no administrative staff) -Data is not centralized |
Primary care registry based on patient records (Electronic Health Record) | Intego datag Computerized morbidity registration network of participating practices. | Longitudinal: since 1999 | Patient population of +/− 50 participating practices | Morbidity in primary care; diagnostic data, sociodemographic data, health care and medication data. The data is aimed to perform audits of the primary care. | -Representative for Flemish population -A lot of diagnostic and clinical longitudinal data -Large number of patients | -Currently Intego is in a transition phase and Medidoc (the software) does not longer exist: as a result no recent data is available -Quality of data depends on coding behaviour of clinicians and there is a lot of variation therein between GPs -Data from specialists as well as events that occur in hospital are not fully captured |
HEALTH CLAIMS DATA (administrative) | ||||||
Databases of the Intermutualistic Agency (IMA)h: Population database, Health care data &Pharmanet | gathered from the seven Belgian health insurance funds that manage compulsory health insurance | Longitudinal | Entire insured Population data (> 99% of the population) | sociodemographic data, health care and costs data, medication data (all reimbursed medication and health services), hospital visits (duration), etc. | -inexpensive compared to original data collections -population data - detailed health care data -Continuously collected -Standardized data registration -Linkage based on a unique identifier number is possible -Previously used in research on chronic care | -Not collected and designed for scientific purposes: not structured in readily available variables for analyses, -Lack of clinical and diagnostic information -No information about health behavior, BMI, etc. -Time lag: data is available in February year X of Year X – 2 |
MEDICAL LAB DATA | ||||||
Data of the Medical laboratories | Laboratories (on request of GPs and specialists) | Depending on the lab | Each lab covers the patient population of several GPs/specialists/ hospitals | Clinical information (type and result value of test) | -Data extraction and linkage based on a unique identifier number is possible -Longitudinal data -Comprehensive clinical information | -Only clinical information −+/− 70 accredited labs -Several Lab information systems (LIS) |