Study design and population
This is a descriptive cross-sectional study. The study population included all participants of the Belgian health interview survey (BHIS) 2013 aged 15 years and older (n = 9112).
Date were derived from the HISLINK 2013 study, an individual linkage between the Belgian health interview survey (BHIS) 2013 data and the Belgian compulsory health insurance data (BCHI) from 2012 to 2018.
The BHIS is a national, cross-sectional household survey conducted every 5 years since 1997 by Sciensano, the Belgian health institute, among a representative sample of Belgian residents. Participants are selected from the national population register through a multistage stratified sampling procedure. The participation rate in the survey was 57% at the household level. In the BHIS, information is collected on health status, health behavior, health care consumption, sociodemographic characteristics and use of medicines. The detailed methodology of the survey is described elsewhere .
The BCHI data contain exhaustive and detailed information on the reimbursed health expenses of over 99% of the total population. The database also includes a limited amount of socio-demographic information. The BCHI data were provided by the Intermutualistic Agency (IMA). IMA is a joint venture of the seven national sickness funds and collects and manages all data on healthcare expenditures as well as prescription information on reimbursed medicines (Pharmanet data) . Pharmanet logs all data on reimbursed dispensed medication from public pharmacies in Belgium. Pharmanet data include information on the date of dispensing, the quantity per package (QPP), the daily defined dose (DDD) and the national code number of the medicine (CNK codes) which allows to link each medicine to its ATC-code. The list of ATC codes per CNK codes was provided by the NIHDI.
Individual BHIS 2013 data were linked with BCHI data using the unique national register number. The study population included all participants of the BHIS 2013 aged 15 years and older (n = 9112). The linkage was possible for 93% of them, resulting in a final sample of 8474 individuals. The HISLINK 2013 was used because it was the most recent linked database available at the moment of this study.
Identification of chronic diseases
The prevalence information from BHIS was collected using a list of CDs (35 in total) based on the following question: “Have you suffered during the last 12 months from the following disease?”. Since there is no specific indicator for CVDs in the BHIS, we considered a person to have CVDs (including hypertension) when they reported having had in the past 12 months at least one of the following CDs: myocardial infarction, coronary disease, hypertension, stroke, or other serious heart diseases.
In the BCHI data, the NIHDI algorithms were used to ascertained cases of CDs. In these algorithms, CDs cases were identified based on the ATC-codes of dispensed medication in public pharmacies, using the WHO guidelines on the ATC classification system . So, a CD was assigned to a participant if the total of DDDs reimbursed for all selected ATC-codes used in the treatment for this CD is greater or equal to 90  in the past 12 months preceding the participation in the BHIS. The selected ATC-codes for each CD are presented in Table 1.
We calculated the weighted prevalence rates from both data sources for the 7 selected CDs. The delta method  was applied to test if there was a significant difference between the estimates of both sources.
The agreement was measured by estimating sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) and their 95% CI, assuming BHIS data as gold standard. Sensitivity was defined as the percentage of true positive cases an algorithm detects among all positive disease cases. Positive disease cases are BHIS respondents who reported having the specified disease. Specificity was defined as the percentage of true negative cases an algorithm detects among all the negative disease cases. Negative disease cases are BHIS respondents who did not report having the specified disease. Positive predictive values (PPVs) and negative predictive values (NPVs) are also reported for each chronic disease algorithm. PPV refers to the percentage of individuals with a positive result for an algorithm among those who reported having the disease. NPV refers to the percentage of individuals with a negative result for an algorithm who did not report having the disease .
Furthermore, Kappa values were calculated to differentiate between true agreement and agreement produced by chance. Kappa values were interpreted as follows: κ ≤ 0.40, fair-to-poor agreement; κ = 0.41 to 0.60, moderate agreement; κ = 0.61 to 0.80, substantial agreement; and κ = 0.81 to 1.00, almost perfect agreement .
Sensitivity analyses were conducted by repeated analyses for different cut-off points of the DDD for all the CDs.
Finally, univariable and multivariable logistic regression analysis were performed for each CD (except for the Parkinson’s disease because of small number of cases unable to provide reliable estimates) to further investigate the effect of respondent’s characteristics on the total agreement (true positive or true negative) between BHIS and BCHI data sources. Participants characteristics included in the model are: gender, age-group (15–34, 35–54, 55–74 and 75+ years), education (low, intermediate, high), nationality (Belgian, EU-countries, other countries), household income (quintile), region of residence (Flanders, Brussels, Wallonia), self-perceived health (good to very good, very bad to fair), presence of multimorbidity (yes/no) and polypharmacy defined as simultaneous use 5 medicines or more on a typical day (yes/no).
A two-sided alpha level of 0.05 was considered statistically significant. All analyses were performed using SAS 9.4 (SAS Institute Inc., Cary, NC, USA) and Stata 16.1 and taking into account the survey settings.
As mentioned above, this study was carried out using the individual linkage between the BHIS 2013 data and the BCHI data. The BHIS 2013 was carried out in line with the Belgian privacy legislation and has been approved by the ethics committee of the University hospital of Ghent on October, 1st 2012 (advice EC UZG 2012/658). The participation to BHIS is voluntary. There was no formal written and signed consent foreseen as participation was considered as consent. In addition, for the data linkage, an authorization was obtained from the Information Security Committee (local reference: Deliberation No. 17/119 of December 19, 2017, amended on September 3, 2019).
This study is reported according to the STROBE statement.