Linking health survey data with health insurance data: methodology, challenges, opportunities and recommendations for public health research. An experience from the HISlink project in Belgium.
Health administrative insurance data; Health claims data; Health interview surveys; Record linkage; data linkage; Public Health, Environmental and Occupational Health
Abstract :
[en] In recent years, the linkage of survey data to health administrative data has increased. This offers new opportunities for research into the use of health services and public health. Building on the HISlink use case, the linkage of Belgian Health Interview Survey (BHIS) data and Belgian Compulsory Health Insurance (BCHI) data, this paper provides an overview of the practical implementation of linking data, the outcomes in terms of a linked dataset and of the studies conducted as well as the lessons learned and recommendations for future links.Individual BHIS 2013 and 2018 data was linked to BCHI data using the national register number. The overall linkage rate was 92.3% and 94.2% for HISlink 2013 and HISlink 2018, respectively. Linked BHIS-BCHI data were used in validation studies (e.g. self-reported breast cancer screening; chronic diseases, polypharmacy), in policy-driven research (e.g., mediation effect of health literacy in the relationship between socioeconomic status and health related outcomes, and in longitudinal study (e.g. identifying predictors of nursing home admission among older BHIS participants). The linkage of both data sources combines their strengths but does not overcome all weaknesses.The availability of a national register number was an asset for HISlink. Policy-makers and researchers must take initiatives to find a better balance between the right to privacy of respondents and society's right to evidence-based information to improve health. Researchers should be aware that the procedures necessary to implement a link may have an impact on the timeliness of their research. Although some aspects of HISlink are specific to the Belgian context, we believe that some lessons learned are useful in an international context, especially for other European Union member states that collect similar data.
Disciplines :
Public health, health care sciences & services
Author, co-author :
Berete, Finaba ; Université de Liège - ULiège > Unité de recherche Santé publique, épidémiologie et économie de la santé (URSAPES) ; Department of Epidemiology and Public Health, Sciensano, Juliette Wytsmanstraat 14, Brussels, 1050, Belgium. finaba.berete@sciensano.be
Demarest, Stefaan; Department of Epidemiology and Public Health, Sciensano, Juliette Wytsmanstraat 14, Brussels, 1050, Belgium
Charafeddine, Rana; Department of Epidemiology and Public Health, Sciensano, Juliette Wytsmanstraat 14, Brussels, 1050, Belgium
De Ridder, Karin; Department of Epidemiology and Public Health, Sciensano, Juliette Wytsmanstraat 14, Brussels, 1050, Belgium
Van Oyen, Herman; Department of Epidemiology and Public Health, Sciensano, Juliette Wytsmanstraat 14, Brussels, 1050, Belgium ; Department of Public Health and Primary Care, Ghent University, Ghent, Belgium
Van Hoof, Wannes; Department of Epidemiology and Public Health, Sciensano, Juliette Wytsmanstraat 14, Brussels, 1050, Belgium
Bruyère, Olivier ; Université de Liège - ULiège > Unité de recherche Santé publique, épidémiologie et économie de la santé (URSAPES)
Van der Heyden, Johan; Department of Epidemiology and Public Health, Sciensano, Juliette Wytsmanstraat 14, Brussels, 1050, Belgium
Language :
English
Title :
Linking health survey data with health insurance data: methodology, challenges, opportunities and recommendations for public health research. An experience from the HISlink project in Belgium.
This work did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. The Belgian Health Interview Survey (BHIS) is financed by the Federal and Inter-Federated Belgian Public Health authorities. The linkage between BHIS data and the Belgian Compulsory Health Insurance data is financed by the National Institute for Health and Disability Insurance.
March S, Andrich S, Drepper J, Horenkamp-Sonntag D, Icks A, Ihle P, et al. Good Practice Data linkage (GPD): a translation of the German version. IJERPH. 2020;17(21):7852.
Druschke D, Arnold K, Heinrich L, Reichert J, Rüdiger M, Schmitt J. Individual-level linkage of primary and secondary data from three sources for comprehensive analyses of low Birthweight effects. Gesundheitswesen. 2020;82(S 02):108–16.
Centre for Health Record Linkage (CHeReL). New South Wales (NSW) Gouvernment Website - Centre for Health Record Linkage. [cited 2023 Feb 9]. How record linkage works. Available from: https://www.cherel.org.au/how-record-linkage-works#:~:text=How%20record%20linkage%20works,of%20health%20events%20for%20individuals.
Brook EL, Rosman DL, Holman CDJ. Aust N Z J Public Health. 2008;32(1):19–23. Public good through data linkage: measuring research outputs from the Western Australian Data Linkage System.
Tew M, Dalziel KM, Petrie DJ, Clarke PM. Growth of linked hospital data use in Australia: a systematic review. Aust Health Review. 2017;41(4):394.
Young A, Flack F. Recent trends in the use of linked data in Australia. Aust Health Review. 2018;42(5):584.
Maret-Ouda J, Tao W, Wahlin K, Lagergren J. Nordic registry-based cohort studies: possibilities and pitfalls when combining nordic registry data. Scand J Public Health. 2017;45(17suppl):14–9.
Haneef R, Delnord M, Vernay M, Bauchet E, Gaidelyte R, Van Oyen H, et al. Innovative use of data sources: a cross-sectional study of data linkage and artificial intelligence practices across European countries. Arch Public Health. 2020;78(1):55.
March S. IJERPH. 2017;14(12):1543. Individual Data Linkage of Survey Data with Claims Data in Germany—An Overview Based on a Cohort Study.
Hall HI, Van Den Eeden SK, Tolsma DD, Rardin K, Thompson T, Hughes Sinclair A, et al. Testing for prostate and Colorectal cancer: comparison of self-report and medical record audit. Prev Med. 2004;39(1):27–35.
Van der Heyden J, Charafeddine R, De Bacquer D, Tafforeau J, Van Herck K. Regional differences in the validity of self-reported use of health care in Belgium: selection versus reporting bias. BMC Med Res Methodol. 2016;16(1):98.
Van der Heyden J, Van Oyen H, Berger N, De Bacquer D, Van Herck K. Activity limitations predict health care expenditures in the general population in Belgium. BMC Public Health. 2015;15(1):267.
Mimilidis Hélène D, Stefaan T, Jean. Van Der Heyden Johan. Projet De couplage de données issues de l’Enquête de Santé 2008 et des organismes assureurs. Bruxelles, Belgique;; 2014. Mai. Report No.: D/2014/2505/32.
Holman CDJ, Bass AJ, Rouse IL, Hobbs MST. Population-based linkage of health records in Western Australia: development of a health services research linked database. Aust N Z J Public Health. 1999;23(5):453–9.
Holman CDJ, Bass JA, Rosman DL, Smith MB, Semmens JB, Glasson EJ, et al. A decade of data linkage in Western Australia: strategic design, applications and benefits of the WA data linkage system. Aust Health Review. 2008;32(4):766.
Mirel LB. The NCHS Data Linkage Program: Leveraging the nation’s health data for evidence-based decision making. In 2020 [cited 2022 Jun 27]. p. 28. Available from: https://www.cdc.gov/nchs/data/datalinkage/Data-Linkage-Webinar.pdf
Harron K, Dibben C, Boyd J, Hjern A, Azimaee M, Barreto ML, et al. Challenges in administrative data linkage for research. Big Data & Society. 2017;4(2):205395171774567.
Harron K. Data linkage in medical research. Bmjmed. 2022;1(1):e000087.
Harron K, Gilbert R, Cromwell D, van der Meulen J. Linking Data for Mothers and Babies in De-Identified Electronic Health Data. Gebhardt S, editor. PLoS ONE. 2016;11(10):e0164667.
Demarest S, Van der Heyden J, Charafeddine R, Drieskens S, Gisle L, Tafforeau J. Methodological basics and evolution of the Belgian health interview survey 1997–2008. Arch Public Health. 2013;71(1):24.
Van der Heyden J. Validity of the Assessment of Population Health and Use of Health Care in a National Health Interview Survey. [Ghent, Belgium]: Ghent University - Faculty of medicine and health sciences; 2017 [cited 2023 Feb 9]. Available from: https://biblio.ugent.be/publication/8523878
Berete F, Van der Heyden J, Demarest S, Charafeddine R, Tafforeau J, Van Oyen H, et al. Validity of self-reported mammography uptake in the Belgian health interview survey: selection and reporting bias. Eur J Pub Health. 2021;31(1):214–20.
KORA Study Group, Hunger M, Schwarzkopf L, Heier M, Peters A, Holle R. Official statistics and claims data records indicate non-response and recall bias within survey-based estimates of health care utilization in the older population. BMC Health Serv Res. 2013;13(1):1.
Devos C, Cordon A, Lefevre M, Obyn C, Renard F, Bouckaert N, et al. Performance of the Belgian health system–report 2019. Health Services Research (HSR). Brussels: Belgian Health Care Knowledge Centre (KCE); 2019.
Noordhout CMD, Devos C, Adriaenssens J, Bouckaert N, Ricour C, Gerkens S. Health system performance assessment: care for people living with chronic conditions.
Bouckaert N, Maertens de Noordhout C, Van de Voorde C. Health System Performance Assessment: how equitable is the Belgian health system?. Brussels: Belgian: Health Services Research (HSR). Health Care Knowledge Centre (KCE); 2020 [cited 2022 Jun 27] p. 105. Report No.: KCE Reports 334. D/2020/10.273/30. Available from: https://kce.fgov.be/sites/default/files/2021-11/KCE_334_Equity_Belgian_health_system_Report.pdf
Berete F, Demarest S, Charafeddine R, Bruyère O, Van der Heyden J. Comparing health insurance data and health interview survey data for ascertaining chronic Disease prevalence in Belgium. Arch Public Health. 2020;78(1):120.
Maetens A, De Schreye R, Faes K, Houttekier D, Deliens L, Gielen B, et al. Using linked administrative and disease-specific databases to study end-of-life care on a population level. BMC Palliat Care. 2016;15(1):86.
Berete F, Demarest S, Charafeddine R, Ridder K, Vanoverloop J, Oyen H et al. Predictors of Nursing Home Admission in the Older Population in Belgium. In Review; 2022 Jan [cited 2022 Mar 3]. Available from: https://www.researchsquare.com/article/rs-1169480/v1
Van der Heyden J, Berete F, Renard F, Vanoverloop J, Devleesschauwer B, De Ridder K, et al. Assessing polypharmacy in the older population: comparison of a self-reported and prescription based method. Pharmacoepidemiol Drug Saf. 2021;30(12):1716–26.
Finaba Berete JV, Heyden S, Demarest. Rana Charafeddine. Couplage des données de l’enquête de santé avec les données des organismes assureurs - Hislink 2013 Méthodologie et étude comparative sur la prévalence des maladies chroniques. 2020 Apr.
Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April. 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive 95/46/EC (General Data Protection Regulation). 2016 [cited 2023 Sep 28]. Available from: https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:32016R0679&qid=1695900759326.
GDPR-in-short. European legislation related to data standards. 2021 [cited 2023 Oct 24]. Available from: https://www.polisnetwork.eu/wp-content/uploads/2021/03/GDPR-in-short2.pdf
Harron KL, Doidge JC, Knight HE, Gilbert RE, Goldstein H, Cromwell DA, et al. A guide to evaluating linkage quality for the analysis of linked data. Int J Epidemiol. 2017;46(5):1699–710.
Williams N, Hermans K, Stevens T, Hirdes JP, Declercq A, Cohen J, et al. Prognosis does not change the landscape: palliative home care clients experience high rates of pain and nausea, regardless of prognosis. BMC Palliat Care. 2021;20(1):165.
Austin PC. Using the standardized difference to compare the prevalence of a Binary Variable between two groups in Observational Research. Commun Stat - Simul Comput. 2009;38(6):1228–34.
Saunders NR, Janus M, Porter J, Lu H, Gaskin A, Kalappa G et al. Use of administrative record linkage to measure medical and social risk factors for early developmental vulnerability in Ontario, Canada. IJPDS. 2021 Feb 11 [cited 2022 Mar 3];6(1). Available from: https://ijpds.org/article/view/1407
Berete F, Van der Heyden J, Demarest S, Van Oyen H, Charafeddine R, Bruyère O. Effectiveness of protective measures on dental care utilization: analysis from linked database. Eur J Pub Health. 2020;30(5).
Berete F, Charafeddine R, Demarest S, der Heyden JV, Gisle L, Van Den Broucke S et al. Does health literacy mediate the relationship between socioeconomic status and health(-related) outcomes in the Belgian adult population? Will be submitted to BMC Public Health. 2023.
Gorasso V, Moyersoen I, Van der Heyden J, De Ridder K, Vandevijvere S, Vansteelandt S, et al. Health care costs and lost productivity costs related to excess weight in Belgium. BMC Public Health. 2022;22(1):1693.
Van der Heyden J, Berete F, Devleesschauwer B, De Ridder K, Bruyère O, Renard F, et al. Association between polypharmacy and mortality in the community-dwelling older population: a data linkage study. Int J Epidemiol. 2021;50:239–9.
Harron K, Doidge J, Challenges. and opportunities in using administrative data linkage for research: the importance of quality assessment for understanding bias. 2020; UCL Great Ormond Street Institute of Child Health. Available from: https://www.ucl.ac.uk/population-health-sciences/sites/population_health_sciences/files/1-nash-mina_katieharron_jan2020.pdf
Ludvigsson JF, Otterblad-Olausson P, Pettersson BU, Ekbom A. The Swedish personal identity number: possibilities and pitfalls in healthcare and medical research. Eur J Epidemiol. 2009;24(11):659–67.
Dusetzina SB, Tyree S, Meyer AM, Meyer A, Green L, Carpenter WR. Linking data for health services research: a framework and instructional guide. 2014.
Harron K, Mackay E, Elliot M. An introduction to data linkage. 2016.
Gilbert R, Lafferty R, Hagger-Johnson G, Harron K, Zhang LC, Smith P, et al. GUILD: GUidance for information about linking data sets†. J Public Health. 2018;40(1):191–8.
Bohensky MA, Jolley D, Sundararajan V, Evans S, Pilcher DV, Scott I, et al. Data linkage: a powerful research tool with potential problems. BMC Health Serv Res. 2010;10(1):346.
Sediq R, Van Der Schans J, Dotinga A, Alingh RA, Wilffert B, Bos JH et al. Concordance assessment of self-reported medication use in the Netherlands three-generation lifelines Cohort study with the pharmacy database iaDB. Nl: the PharmLines initiative. Clin Epidemiol. 2018;981–9.
van Brug HE, Rosendaal FR, van Steenbergen LN, Nelissen RG, Gademan MG. Data linkage of two national databases: lessons learned from linking the Dutch Arthroplasty Register with the Dutch Foundation for Pharmaceutical Statistics. PLoS ONE. 2023;18(3):e0282519.
Applying for linked data from the Lifelines Cohort Study and IADB.nl database. 2021. Available from: http://wiki-lifelines.web.rug.nl/lib/exe/fetch.php?media=pharmlines_procedures_20210415.pdf
Jutte DP, Roos LL, Brownell MD. Administrative record linkage as a Tool for Public Health Research. Annu Rev Public Health. 2011;32(1):91–108.
European Parliament and European Council. Regulation (EU) 2022/868 of the European Parliament and of the Council of 30 May 2022 on European data governance and amending Regulation (EU) 2018/1724 (Data Governance Act). 2022 [cited 2022 Sep 27]. Available from: https://data.consilium.europa.eu/doc/document/PE-85-2021-INIT/en/pdf
Sakshaug JW, Couper MP, Ofstedal MB, Weir DR. Linking Survey and Administrative records: mechanisms of Consent. Sociol Methods Res. 2012;41(4):535–69.
Sakshaug JW, Schmucker A, Kreuter F, Couper MP, Holtmann L. Respondent understanding of data linkage consent. Survey Methods: Insights from the Field (SMIF); 2021.
van Veen EB. Observational health research in Europe: understanding the General Data Protection Regulation and underlying debate. Eur J Cancer. 2018;104:70–80.
Hafferty JD, Campbell AI, Navrady LB, Adams MJ, MacIntyre D, Lawrie SM, et al. Self-reported medication use validated through record linkage to national prescribing data. J Clin Epidemiol. 2018;94:132–42.
Richardson K, Kenny RA, Peklar J, Bennett K. Agreement between patient interview data on prescription medication use and pharmacy records in those aged older than 50 years varied by therapeutic group and reporting of indicated health conditions. J Clin Epidemiol. 2013;66(11):1308–16.
Rosella LC, Manuel DG, Burchill C, Stukel TA. For the PHIAT-DM team. A population-based risk algorithm for the development of Diabetes: development and validation of the Diabetes Population Risk Tool (DPoRT). J Epidemiol Community Health. 2011;65(7):613–20.
Rosella LC, Fitzpatrick T, Wodchis WP, Calzavara A, Manson H, Goel V. High-cost health care users in Ontario, Canada: demographic, socio-economic, and health status characteristics. BMC Health Serv Res. 2014;14(1):532.
Gorman E, Leyland AH, McCartney G, White IR, Katikireddi SV, Rutherford L, et al. Assessing the representativeness of Population-Sampled health surveys through linkage to Administrative Data on Alcohol-related outcomes. Am J Epidemiol. 2014;180(9):941–8.
Meyer BD, Mittag N. Combining administrative and survey data to improve income measurement. Administrative Records for Survey Methodology. 2021;297–322.
Morgan K, Page N, Brown R, Long S, Hewitt G, Del Pozo-Banos M, et al. Sources of potential bias when combining routine data linkage and a national survey of secondary school-aged children: a record linkage study. BMC Med Res Methodol. 2020;20(1):178.
Linnenkamp U, Gontscharuk V, Brüne M, Chernyak N, Kvitkina T, Arend W, et al. Using statutory health insurance data to evaluate non-response in a cross-sectional study on depression among patients with Diabetes in Germany. Int J Epidemiol. 2020;49(2):629–37.
Bradley CJ, Penberthy L, Devers KJ, Holden DJ. Health Services Research and Data linkages: issues, methods, and directions for the future: Health Services Research and Data linkages. Health Serv Res. 2010;45(5p2):1468–88.
Maddocks J, Mathieu L, Richards R, Saelaert M, Van Hoof W. tehdas-healthy-data-an-online-citizen-consultation-about-health-data-reuse-intermediatereport.pdf. 2022 Jun [cited 2022 Sep 27]. Available from: https://tehdas.eu/app/uploads/2022/07/tehdas-healthy-data-an-online-citizen-consultation-about-health-data-reuse-intermediate-report.pdf.
Marie Thornby LC. Collecting Multiple Data Linkage Consents in a Mixed-mode Survey: Evidence from a large-scale longitudinal study in the UK. 2018 [cited 2022 Sep 27]; Available from: https://surveyinsights.org/?p=9734
Sakshaug JW, Vicari BJ. Obtaining record linkage consent from establishments: the Impact of Question Placement on Consent Rates and Bias. J Surv Stat Methodol. 2018;6(1):46–71.
Sakshaug JW, Schmucker A, Kreuter F, Couper MP, Singer E. The Effect of Framing and Placement on linkage consent. Pub Opin Q. 2019;83(S1):289–308.
European Commission, REGULATION OF THE EUROPEAN PARLIAMENT, AND OF THE COUNCIL on the European Health. Data Space. 2022 [cited 2023 Feb 9]. Available from: https://eur-lex.europa.eu/resource.html?uri=cellar:dbfd8974-cb79-11ec-b6f 4-01aa75ed71a1.0001.02/DOC_1&format=PDF.
McLennan S, Celi LA, Buyx A. COVID-19: putting the General Data Protection Regulation to the test. JMIR Public Health Surveill. 2020;6(2):e19279.
Kiseleva A, De Hert P. Creating a European Health Data Space: obstacles in four key legal area. EPLR. 2021;5:21.
Dibben C, Elliot M, Gowans H, Lightfoot D, Data Linkage Centres. The data linkage environment. In: Harron K, Dibben C, Goldstein H, editors. Methodological developments in data linkage chap. 3 ed. London: Wiley; 2015.
Jones KH, Ford DV, Jones C, Dsilva R, Thompson S, Brooks CJ, et al. A case study of the Secure Anonymous Information linkage (SAIL) gateway: a privacy-protecting remote access system for health-related research and evaluation. J Biomed Inform. 2014;50:196–204.
Boyd JH, Ferrante AM, O’Keefe CM, Bass AJ, Randall SM, Semmens JB. Data linkage infrastructure for cross-jurisdictional health-related research in Australia. BMC Health Serv Res. 2012;12(1):480.
Aldridge RW, Shaji K, Hayward AC, Abubakar I. Accuracy of Probabilistic Linkage Using the Enhanced Matching System for Public Health and Epidemiological Studies. Pacheco AG, editor. PLoS ONE. 2015;10(8):e0136179.
Harron K, Goldstein H, Wade A, Muller-Pebody B, Parslow R, Gilbert R, Linkage. Evaluation and Analysis of National Electronic Healthcare Data: Application to Providing Enhanced Blood-Stream Infection Surveillance in Paediatric Intensive Care. Trotter CL, editor. PLoS ONE. 2013;8(12):e85278.