Advertisement

Data Collection

  • Mariken TijhuisEmail author
  • Jonas David Finger
  • Lany Slobbe
  • Reijo Sund
  • Hanna Tolonen
Chapter

Abstract

As described in the previous chapters, representative and high-quality data are essential for effective health information systems and monitoring strategies. Population health monitoring covers topics in the full range of human health and its influencing factors, and these domains are typically structured into conceptual frameworks and described in terms of indicators. These indicators can be derived from several different types of data sources, such as surveys, registers, and clinical and social epidemiological studies. The aim of this chapter is to provide insight into the various types of data sources available for public health monitoring purposes, their characteristics, specific applications, potential and limitations. The main focus of the chapter will be on the two major types of data sources used for population health monitoring: health surveys and registers. The main causes of bias, influencing data quality and validity, and issues with data access and linkage are addressed as the most important factors limiting the usability of data. The role of data protection and data governance in this is explored. The chapter will conclude with an overview of the most important current and expected future developments in the field of health-related data collection.

Keywords

Data source Health interview survey Health examination survey Health register Data quality Data validity Bias Data linkage Date governance Data protection Big data 

References

  1. Alkerwi, A., Sauvageot, N., Couffignal, S., Albert, A., Lair, M. L., & Guillaume, M. (2010). Comparison of participants and non-participants to the OVISCAR-LUX population-based study on cardiovascular risk factors in Luxembourg. BMC Medical Research Methodology, 10, 80.CrossRefGoogle Scholar
  2. Allebeck, P. (2002). The revised Helsinki declaration: Good for patients? Good for public health? Scandinavian Journal of Public Health, 30(1), 1–4.CrossRefGoogle Scholar
  3. Aromaa, A., & Tolonen, H. (2008). History of health examination surveys. In H. Tolonen, P. Koponen, A. Aromaa, et al. (Eds.), Review of health examination surveys in Europe. Helsinki: National Public Health Institute http://www.julkari.fi/bitstream/handle/10024/103057/2008b18.pdf. Accessed 10 Sept 2017.Google Scholar
  4. Baruch, Y., & Holtom, B. C. (2009). Survey response rate levels and trends in organizational research. Human Relations, 61(8), 1139–1160.CrossRefGoogle Scholar
  5. Boshuizen, H. C., Viet, A. L., Picavet, H. S., Botterweck, A., & van Loon, A. J. (2006). Non-response in a survey of cardiovascular risk factors in the Dutch population: Determinants and resulting biases. Public Health, 120(4), 297–308.CrossRefGoogle Scholar
  6. Brownstein, J. S., Freifeld, C. C., & Madoff, L. C. (2009). Digital disease detection-harnessing the Web for public health surveillance. The New England Journal of Medicine, 360(21), 2153–2157.CrossRefGoogle Scholar
  7. CDC. (2015). Centres for disease control and prevention: National health and nutrition examination surveys. https://www.cdc.gov/nchs/nhanes/nhanes_questionnaires.htm. Last updated/reviewed: October 2015. Accessed 2 Jul 2017.
  8. Council of the European Union, European Parliament. (2016). 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). https://publications.europa.eu/en/publication-detail/-/publication/3e485e15-11bd-11e6-ba9a-01aa75ed71a1/language-en. Accessed 16 Sept 2017.
  9. De Bruin, A., Picavet, H., & Nossikov, A. (1996). Health interview surveys: Towards international harmonisation of methods and instruments. WHO Regional Publications, European Series. 58. http://www.euro.who.int/en/publications/abstracts/health-interview-surveys.-towards-international-harmonization. Accessed 30 Aug 2017.
  10. Deville, P., Linard, C., Martin, S., Gilbert, M., Stevens, F. R., Gaughan, A. E., Blondel, V. D., & Tatem, A. J. (2014). Dynamic population mapping using mobile phone data. Proceedings of the National Academy of Sciences of the United States of America, 111(45), 15888–15893. https://doi.org/10.1073/pnas.1408439111.CrossRefPubMedPubMedCentralGoogle Scholar
  11. Dunn, H. L. (1946). Record linkage. American Journal of Public Health and the Nation's Health, 36(12), 1412–1416 PubMed PMID: 18016455; PubMed Central PMCID: PMC1624512.CrossRefGoogle Scholar
  12. Edwards, P. J., Roberts, I., Clarke, M. J., Diguiseppi, C., Wentz, R., Kwan, I., Cooper, R., Felix, L. M., & Pratap, S. (2009). Methods to increase response to postal and electronic questionnaires. Cochrane Database of Systematic Reviews, 3, MR000008. https://doi.org/10.1002/14651858.MR000008.pub4.CrossRefGoogle Scholar
  13. Ekholm, O., Gundgaard, J., Rasmussen, N. K. R., & Hansen, E. H. (2010). The effect of health, socio-economic position, and mode of data collection on non-response in health interview surveys. Scandinavian Journal of Public Health, 38, 699–706.CrossRefGoogle Scholar
  14. EPA. (2015). Learn about data standards. United States Environmental Protection Agency. https://www.epa.gov/data-standards/learn-about-data-standards. Accessed 2 Jul 2017.
  15. Eurostat. (2013). European Health Interview Survey (EHIS wave 2). Methodological manual. http://ec.europa.eu/eurostat/documents/3859598/5926729/KS-RA-13-018-EN.PDF/26c7ea80-d8-420e-bdc6-e9d5f6578e7c. Accessed 2 Jul 2017.
  16. Follett, R., & Strezov, V. (2015). An analysis of citizen science based research: Usage and publication patterns. PLoS One, 10(11), e0143687 https://doi.org/10.1371/journal.pone.0143687.CrossRefGoogle Scholar
  17. Gorber, S. C., Tremblay, M., Moher, D., & Gorber, B. (2007). A comparison of direct vs. self-report measures for assessing heigh, weight and body mass index: a systematic review. Obesity Reviews, 8, 307–326.CrossRefGoogle Scholar
  18. Hill, A., Roberts, J., Ewings, P., & Gunnell, D. (1997). Non-response bias in a lifestyle survey. Journal of Public Health Medicine, 19(2), 203–207.CrossRefGoogle Scholar
  19. IPH & THL. (2010). European health interview & health examination surveys database. Scientific Institute of Public Health Belgium & the National Institute of Public Health Finland. https://hishes.wiv-isp.be/index.php?hishes=home. Accessed 2 Jul 2017.
  20. Jousilahti, P., Salomaa, V., Kuulasmaa, K., Niemelä, M., & Vartiainen, E. (2005). Total and cause specific mortality among participants and non-participants of population based health surveys: a comprehensive follow up of 54 372 Finnish men and women. Journal of Epidemiology and Community Health, 49(4), 310–315.CrossRefGoogle Scholar
  21. Kardaun, J., de Bruin, A., van Polanen, P. V., van der Aart, S., van den Berg, J., & van Hilten, O. (2012). Health statistics in the Netherlands, review 1995–2009, preview 2010–2015. Statistical Journal of the IAOS, 28(1,2), 59–72.Google Scholar
  22. KCDC. (2017). Survey overview. Korea Centers for Disease Control and Prevention. https://knhanes.cdc.go.kr/knhanes/eng/sub01/sub01_02.do. Accessed 2 Jul 2017.
  23. Khoury, M. J. (2015). Planning for the future of epidemiology in the era of Big Data and precision medicine. American Journal of Epidemiology, 182(12), 977–979.PubMedPubMedCentralGoogle Scholar
  24. Korkeila, K., Suominen, S., Ahvenainen, J., Ojanlatva, A., Rautava, P., Helenius, H., et al. (2001). Non-response and related factors in a nation-wide health survey. European Journal of Epidemiology, 17(11), 991–999.CrossRefGoogle Scholar
  25. Korn, E. L., & Graubard, B. I. (1999). Sample weights and imputation, in analysis of health surveys. Hoboken: Wiley. https://doi.org/10.1002/9781118032619.ch4.CrossRefGoogle Scholar
  26. Kuulasmaa, K., & Tolonen, H. (2013). What is EHES and why it is needed? National Institute for Health and Welfare. Discussion Paper 2013_007. URN:ISBN: 978-952-245-844-5. http://urn.fi/URN:ISBN:978-952-245-844-5.
  27. Lauhaut, V. M., Jansen, H. A., Van de Mheen, D., & Garretsen, H. F. (2002). Non-response bias in a sample survey on alcohol consumption. Alcohol and Alcoholism, 37(3), 256–260.CrossRefGoogle Scholar
  28. Lynge, E. (2011). The Danish national patient register. Scandinavian Journal of Public Health, 39(7 suppl), 30–33.CrossRefGoogle Scholar
  29. Mindell, J. S., Giampaoli, S., Goesswald, A., Kamtriuris, P., Mann, C., Männistö, S., Morgan, K., Shelton, N. J., Verschuren, M., & Tolonen, H. (2015). Sample selection, recruitment and participation rates in health examination surveys in Europe – experience from seven national surveys. BMC Medical Research Methodology, 15, 78.CrossRefGoogle Scholar
  30. Nordbotten, S. (2010). The use of administrative data in official statistics – Past, present, and future – With special reference to the Nordic countries, in Carlson, Nyquist and Villani (eds), Official statistics – Methodology and applications in Honour of Daniel Thorburn; 05–225. http://www.nordbotten.com/articles/Adm_data.pdf. Accessed 10 Sept 2017.
  31. OECD. (2013a). Strengthening health information infrastructure for health care quality governance: Good practices, new opportunities and data privacy protection challenges. Paris: OECD Health Policy Studies. http://www.oecd.org/publications/strengthening-health-information-infrastructure-for-health-care-quality-governance-9789264193505-en.htm. Accessed 10 Sept 2017.
  32. OECD. (2013b). OECD privacy framework. Paris: OECD. http://www.oecd.org/sti/ieconomy/oecd_privacy_framework.pdf. Accessed 10 Sept 2017.
  33. OECD. (2015). Health data governance: Privacy, monitoring and research. Paris: OECD Publishing. http://www.oecd.org/publications/health-data-governance-9789264244566-en.htm. Accessed 10 Sept 2017.
  34. OECD. (2017a). New health technologies: Managing access, value and sustainability, Chapter 6. Digital technology: Making better use of health data. Paris: OECD Publishing. http://www.oecd.org/publications/managing-new-technologies-in-health-care-9789264266438-en.htm. Accessed 10 Sept 2017.
  35. OECD. (2017b). OECD recommendation on health data governance. http://www.oecd.org/els/health-systems/health-data-governance.htm. Accessed 23 Feb 2017. See also http://acts.oecd.org/Public/Info.aspx?lang=en&infoRef=C(2016)176.
  36. OECD/Eurostat/WHO. (2017). A system of health accounts 2011: Revised edition. Paris: OECD Publishing. http://www.oecd-ilibrary.org/social-issues-migration-health/a-system-of-health-accounts-2011_9789264270985-en. Accessed 10 Sept 2017.
  37. Rose, G., & Blackburn, H. (1968). Cardiovascular survey methods. World Health Organization Technical Report Series No. 56, Geneva: World Health Organization, pp. 1–188.Google Scholar
  38. Rubin, D. B. (1987). Multiple imputation for nonresponse in surveys. New York: Wiley.CrossRefGoogle Scholar
  39. Särndal, C.-E., Swensson, B., & Wretman, J. (1992). Model assisted survey sampling. New York: Springer.CrossRefGoogle Scholar
  40. Science Daily. (2013). Big Data, for better or worse: 90% of world’s data generated over last two years. https://www.sciencedaily.com/releases/2013/05/130522085217.htm. Accessed 2 Jul 2017.
  41. Statistics Canada. (2015). Sample design. Statistics Canada. http://www.statcan.gc.ca/pub/12-539-x/2009001/sample-plan-eng.htm. Accessed 10 Sept 2017.
  42. Statistics Canada. (2017). Canadian Health Measures Survey. Statistics Canada. http://www.statcan.gc.ca/eng/survey/household/5071. Accessed 2 Jul 2017.
  43. Sund R, Gissler M, Hakulinen T, Rosen M. Use of health registers. In: Ahrens, Wolfgang & Pigeot, Iris (Eds.): Handbook of epidemiology, 2nd edition. New York: Springer. 2014; 707–730.CrossRefGoogle Scholar
  44. Sundgren, B. (1996). Making statistical data more available. International Statistical Review, 64(1), 23–38.CrossRefGoogle Scholar
  45. THL. (2015). European health examination survey. National Institute for Health and Welfare. http://www.ehes.info/national_hes.htm. Accessed 2 Jul 2017.
  46. THL. (2016). The EHES Manual. National Institute for Health and Welfare Finland. http://www.ehes.info/manuals/EHES_manual/EHES_manual.htm. Accessed 2 Jul 2017.
  47. Tolonen, H. (2008). Sources of health data and uses of information from health examination surveys. In H. Tolonen, P. Koponen, A. Aromaa, et al. (Eds.), Review of health examination surveys in Europe. Finland: Publications for the National Public Health Institute http://urn.fi/URN:ISBN:978-951-740-843-1. Accessed 13 Sept 2017.Google Scholar
  48. Tolonen, H. (Ed.). (2016). EHES Manual. Part A. Planning and preparation of the survey. 2nd edition. National Institute for Health and Welfare Finland. http://urn.fi/URN:ISBN:978-952-302-700-8. Accessed 2 Jul 2017.
  49. Tolonen, H., Ferrario, M., & Kuulasmaa K for the WHO MONICA Project. (2005). Standardization of total cholesterol measurement in population surveys - pre-analytic sources of variation and their effect on the prevalence of hypercholesterolaemia. European Journal of Cardiovascular Prevention and Rehabilitation, 12, 257–267.PubMedGoogle Scholar
  50. Tolonen, H., Koponen, P., Mindell, J., Männistö, S., & Kuulasmaa, K. (2014a). European Health Examination Survey--towards a sustainable monitoring system (2014a). European Journal of Public Health, 2, 338–344. https://doi.org/10.1093/eurpub/ckt107 Epub 2013 Jul 18.CrossRefGoogle Scholar
  51. Tolonen, H., Aistrich, A., & Borodulin, K. (2014b). Increasing health examination survey participation rates by SMS reminders and flexible examination times. Scandinavian Journal of Public Health, 42(7), 712–717. https://doi.org/10.1177/1403494814544403 Epub 2014 Aug 12.CrossRefPubMedGoogle Scholar
  52. Tolonen, H., Koponen, P., Mindell, J. S., Männistö, S., Giampaoli, S., Dias, C. M., Tuovinen, T., Göβwald, A., Kuulasmaa, K., & European Health Examination Survey Pilot Project. (2014c). Under-estimation of obesity, hypertension and high cholesterol by self-reported data: Comparison of self-reported information and objective measures from health examination surveys. European Journal of Public Health, 24(6), 941–948. https://doi.org/10.1093/eurpub/cku074 Epub 2014 Jun 6. 2014c.CrossRefPubMedGoogle Scholar
  53. Tolonen, H., Ahonen, S., Jentoft, S., Kuulasmaa, K., Heldal, J., & European Health Examination Pilot Project. (2015). Differences in participation rates and lessons learned about recruitment of participants--the European Health Examination Survey Pilot Project. Scandinavian Journal of Public Health, 43(2), 212–219. https://doi.org/10.1177/1403494814565692.CrossRefPubMedGoogle Scholar
  54. Verschuuren, M., Achterberg, P. W., Gijsen, R., Harbers, M. M., Vijge, E., van der Wilk, E. A., & Kramers, P. G. N. (2012). ECHI indicator development and documentation. Joint Action for ECHIM final report Part II. National Institute for Public Health and the Environment (RIVM). Bilthoven, The Netherlands. https://www.volksgezondheidenzorg.info/sites/default/files/echim-final-report_part-ii_pdf.pdf. Accessed 13 Sept 2017.
  55. Wall, M., & Teeland, L. (2004). Non-participants in a preventive health examinations for cardiovascular disease: Characteristics, reasons for non-participation, and willingness to participate in the future. Scandinavian Journal of Primary Health Care, 22, 248–251.CrossRefGoogle Scholar
  56. Weibel, S., Kunze, J., Lagoze, C., & Wolf, M. (1998). Dublin core metadata for resource discovery. No. RFC 2413. http://www.rfc-editor.org/info/rfc2413. Accessed 13 Sept 2017.
  57. WHO. (2017a). Analysing mortality levels and causes-of-death (ANACoD). http://www.who.int/healthinfo/anacod/en/. Accessed 2 Jul 2017.
  58. WHO. (2017b). Classifications. World Health Organisation. www.who.int/classifications/en. Accessed 2 Jul 2017.

Further Reading

  1. Survey Methodology:Google Scholar
  2. Aday, L. U., & Cornelius, L. J. (2006). Designing and conducting health surveys (3rd ed.). New York: Wiley.Google Scholar
  3. Harkness, J. A., Braun, M., Edwards, B., et al. (2010). Survey methods in multinational, multiregional, and multicultural context. New York: Wiley.Google Scholar
  4. Thompson, S. K. (2002). Sampling (2nd ed.). New York: Wiley.Google Scholar
  5. Register-Based Data:Google Scholar
  6. Wallgren & Wallgren: Register-based Statistics: Statistical Methods for Administrative Data, 2nd Edition. 2014.Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Mariken Tijhuis
    • 1
    Email author
  • Jonas David Finger
    • 2
  • Lany Slobbe
    • 1
  • Reijo Sund
    • 3
    • 4
  • Hanna Tolonen
    • 5
  1. 1.Centre for Health Knowledge IntegrationNational Institute for Public Health and the Environment (RIVM)BilthovenThe Netherlands
  2. 2.Robert Koch Institute, Department of Epidemiology and Health MonitoringBerlinGermany
  3. 3.Institute of Clinical Medicine, University of Eastern FinlandKuopioFinland
  4. 4.Centre for Research Methods, Faculty of Social SciencesHelsinkiFinland
  5. 5.Department of Public Health SolutionsNational Institute for Health and WelfareHelsinkiFinland

Personalised recommendations