Skip to main content
SpringerLink
Log in

Future of Data Analytics in the Era of the General Data Protection Regulation in Europe

  • Current Opinion
  • Published:
PharmacoEconomics Aims and scope Submit manuscript

Abstract

The development of evidence to demonstrate ‘value for money’ is regarded as an important step in facilitating the search for the optimal allocation of limited resources and has become an essential component in healthcare decision making. Real-world evidence collected from de-identified individuals throughout the continuum of healthcare represents the most valuable source in technology evaluation. However, in the European Union, the value assessment based on real-world data has become challenging as individuals have recently been given the right to have their personal data erased in the case of consent withdrawal or when the data are regarded as being no longer necessary. This act may limit the usefulness of data in the future as it may introduce information bias. Among healthcare stakeholders, this has become an important topic of discussion because it relates to the importance of data on one side and to the need for personal data protection on the other side, especially when it comes to “personal data related to the physical or mental health of a natural person, including the provision of health care services, which reveals information about his or her health status”. At the forefront of these discussions are data protection issues as well as the population’s trust in digital services. It seems that the new era has begun, where citizens and patients will have the ability to manage their personal or self-generated data. The European Commission has laid the groundwork for this paradigm shift that will steadily emerge in the coming years. To prepare for this change, we believe attention should be given to data security and other rules of data privacy. It has become increasingly important to ensure that individuals are properly introduced into complex environments with multiple sources of Big Data for clinical and behavioral purposes to provide an optimal balance between societal and individual benefits. In this article, a number of issues are considered and discussed, based upon the authors’ experience, with the aim of helping the reader better understand the implications of the use of Big Data and the importance of data protection in the coming years.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Deloitte. Global health care outlook: shaping the future. 2019. Available from: https://www2.deloitte.com/content/dam/Deloitte/global/Documents/Life-Sciences-Health-Care/gx-lshc-hc-outlook-2019.pdf. Accessed 9 Mar 2019.

  2. Okoli C, Ezenduka C, Uzochukwu B, Okoronkwo I, Onwujekwe O. Achieving value for money in healthcare: principles, methods and empirical applications. Afr J Health Econ. 2014;2.

  3. Caro JJ, Brazier JE, Karnon J, Kolominsky-Rabas P, McGuire AJ, Nord E, et al. Determining value in health technology assessment: stay the course or tack away? Pharmacoeconomics. 2019;37(3):293–9.

    Article  Google Scholar 

  4. The Economist. The world’s most valuable resource is no longer oil, but data. 2017. Available from: https://www.economist.com/leaders/2017/05/06/the-worlds-most-valuable-resource-is-no-longer-oil-but-data. Accessed 9 Mar 2019.

  5. Data Age 2025. The digitization of the world from edge to core. An IDC White Paper. November 2018. Available from: https://www.seagate.com/files/www-content/our-story/trends/files/idc-seagate-dataage-whitepaper.pdf. Accessed 9 Mar 2019.

  6. Schwab K. The fourth industrial revolution: what it means, how to respond. 2016. Available from: https://www.weforum.org/agenda/2016/01/the-fourth-industrial-revolution-what-it-means-and-how-to-respond. Accessed 21 May 2020.

  7. Emilsson L, Lindahl B, Koster M, Lambe M, Ludvigsson JF. Review of 103 Swedish healthcare quality registries. J Intern Med. 2015;277(1):94–136.

    Article  CAS  Google Scholar 

  8. Oderkirk J. Findings of the 2016 OECD HCQI study of electronic health record system development and data use. 2016. Available from: https://www.oecd.org/officialdocuments/publicdisplaydocumentpdf/?cote=DELSA/HEA/WD/HWP(2017)9&docLanguage=En. Accessed 10 Jan 2020.

  9. Henry J, Pylypchuk Y, Searcy T, Patel V. Adoption of electronic health record systems among U.S. non-federal acute care hospitals: 2008–2015. ONC data brief, No. 35. Washington, DC: Office of the National Coordinator for Health Information Technology; 2016. Available from: https://www.healthit.gov/sites/default/files/briefs/2015_hospital_adoption_db_v17.pdf. Accessed 1 Jan 2020.

  10. Research to Guidance. 84,000 health app publishers in 2017: newcomers differ in their go-to-market approach. 2017. Available from: https://research2guidance.com/84000-health-app-publishers-in-2017/. Accessed 9 Mar 2019.

  11. Stefansson H, Ophoff RA, Steinberg S, Andreassen OA, Cichon S, Rujescu D, et al. Common variants conferring risk of schizophrenia. Nature. 2009;460(7256):744–7.

    Article  CAS  Google Scholar 

  12. Iturria-Medina Y, Sotero RC, Toussaint PJ, Mateos-Perez JM, Evans AC. Early role of vascular dysregulation on late-onset Alzheimer's disease based on multifactorial data-driven analysis. Nat Commun. 2016;7:11934.

    Article  CAS  Google Scholar 

  13. Eichstaedt JC, Schwartz HA, Kern ML, Park G, Labarthe DR, Merchant RM, et al. Psychological language on twitter predicts county-level heart disease mortality. Psychol Sci. 2015;26(2):159–69.

    Article  Google Scholar 

  14. European Commission. European assistance for innovation procurement: eafip. 2019. Available from: https://eafip.eu/about/. Accessed 26 Apr 2019.

  15. European Commission. Recovering life wellbeing through pain self-management techniques involving ICTs. 2017. Available from: https://cordis.europa.eu/project/id/689476. Accessed 26 Apr 2019.

  16. European Commission. The DECIPHER Project (Distributed European Community Individual Patient Healthcare Electronic Record). 2017. Available from: https://cordis.europa.eu/project/id/288028. Accessed 26 Apr 2019.

  17. European Commission. Procuring innovative ICT for patient empowerment and self-management for type 2 diabetes mellitus. 2019. Available from: https://cordis.europa.eu/project/id/727409. Accessed 26 Apr 2019.

  18. European Commission. Building a European data economy. 2019. Available from: https://ec.europa.eu/digital-single-market/en/policies/building-european-data-economy. Accessed 10 Jan 2020.

  19. European Commission. EU leaders' meeting in Sofia: completing a trusted digital single market for the benefit of all. 2018. Available from: https://ec.europa.eu/commission/presscorner/detail/en/IP_18_3740. Accessed 9 Mar 2019.

  20. Voss W. First the GDPR, now the proposed ePrivacy regulation. J Internet Law. 2017;21:3–11.

    Google Scholar 

  21. 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). Available from: https://eur-lex.europa.eu/eli/reg/2016/679/oj. Accessed.

  22. European Commission. A new era for data protection in the EU: what changes after May 2018? 2018. Available from: https://ec.europa.eu/commission/sites/beta-political/files/data-protection-factsheet-changes_en.pdf. Accessed 9 Mar 2019.

  23. European Public Health Alliance. Health and care in the digital single market: reflection paper. September 2017. Available from: https://epha.org/wp-content/uploads/2018/02/Health-and-care-in-digital-single-market-position-paper.pdf. Accessed 9 Mar 2017.

  24. Cornock M. General data protection regulation (GDPR) and implications for research. Maturitas. 2018;111:A1–2.

    Article  Google Scholar 

  25. Mourby M, Mackey E, Elliot M, Gowans H, Wallace SE, Bell J, et al. Are ‘pseudonymised’ data always personal data? Implications of the GDPR for administrative data research in the UK. Comput Law Secur Rev. 2018;34(2):222–33.

    Article  Google Scholar 

  26. Chassang G. The impact of the EU general data protection regulation on scientific research. Ecancermedicalscience. 2017;11:709.

    Article  Google Scholar 

  27. Hicks JL, Althoff T, Sosic R, Kuhar P, Bostjancic B, King AC, et al. Best practices for analyzing large-scale health data from wearables and smartphone apps. NPJ Digit Med. 2019;2:45.

    Article  Google Scholar 

  28. Voigt P, von dem Bussche A. The EU general data protection regulation (GDPR): a practical guide. Springer, Berlin 2017.

  29. European Commission Directorate-General for Health and Food Safety. Question and answers on the interplay between the Clinical Trials Regulation and the General Data Protection Regulation. 2019. Available from: https://ec.europa.eu/health/sites/health/files/files/documents/qa_clinicaltrials_gdpr_en.pdf. Accessed 2 Jan 2020.

  30. World Medical Association. World medical association declaration of Helsinki: ethical principles for medical research involving human subjects. JAMA. 2013;310(20):2191–4.

    Article  Google Scholar 

  31. Gefenas E, Cekanauskaite A, Lekstutiene J, Lukaseviciene V. Application challenges of the new EU clinical trials regulation. Eu J Clin Pharmacol. 2017;73(7):795–8.

    Article  Google Scholar 

  32. European Commission. Article 29 working party. 2016. Available from: https://ec.europa.eu/justice/article-29/documentation/index_en.htm. [Accessed 24 Feb 2020].

  33. Farrell AM, Devereux J, Karpin I, Weller P. Health law: frameworks and context. : Cambridge University Press; 2017;262

  34. European Commission. What does ‘grounds of legitimate interest’ mean? 2019. Available from: https://ec.europa.eu/info/law/law-topic/data-protection/reform/rules-business-and-organisations/legal-grounds-processing-data/grounds-processing/what-does-grounds-legitimate-interest-mean_en. Accessed 24 Feb 2020.

  35. World Health Organization. Who owns our genes? 1999. Available from: https://www.who.int/genomics/elsi/regulatory_data/region/international/073/en/. Accessed 24 Feb 2020.

  36. European Parliament Research Service. Rules for EU institutions' processing of personal data. 2018. Available from: https://www.europarl.europa.eu/RegData/etudes/BRIE/2017/608754/EPRS_BRI(2017)608754_EN.pdf. Accessed 29 Apr 2019.

  37. Agarwal R, Sands DZ, Schneider JD. Quantifying the economic impact of communication inefficiencies in U.S. hospitals. J Healthc Manag. 2010;55(4):265–81.

    PubMed  Google Scholar 

  38. Elliot M, Mackey E, O’Hara K, Tudor C. The anonymisation decision-making framework. 2016. Available from: https://ukanon.net/wp-content/uploads/2015/05/The-Anonymisation-Decision-making-Framework.pdf. Accessed 10 Jan 2020.

  39. Benschop T, Machingauta C, Welch M. Statistical disclosure control for microdata: a practice guide for sdcMicro. 2019. Available from: https://sdcpractice.readthedocs.io/en/latest/. Accessed 10 Jan 2020.

  40. IHE IT Infrastructure Technical Committee. Handbook on de-identification. 2014. Available from: https://www.ihe.net/uploadedFiles/Documents/ITI/IHE_ITI_Handbook_De-Identification_Rev1.1_2014-06-06.pdf. Accessed 27 Apr 2019.

  41. Gandomi A, Haider M. Beyond the hype: big data concepts, methods, and analytics. Int J Inform Manag. 2015;35(2):137–44.

    Article  Google Scholar 

  42. Tucker K, Branson J, Dilleen M, Hollis S, Loughlin P, Nixon MJ, et al. Protecting patient privacy when sharing patient-level data from clinical trials. BMC Med Res Methodol. 2016;16(1):77.

    Article  Google Scholar 

  43. Gliklich RE, Dreyer NA, Leavy MB (eds) Managing patient identity across data sources: registries for evaluating patient outcomes. A user's guide. 3rd ed. Rockville: Agency for Healthcare Research and Quality; 2014.

  44. Hoerbst A, Ammenwerth E. Quality and certification of electronic health records: an overview of current approaches from the US and Europe. Appl Clin Inform. 2010;1(2):149–64.

    Article  CAS  Google Scholar 

  45. Continua Design. Guidelines. 2017. Available from: https://www.pchalliance.org/continua-design-guidelines. Accessed 29 Apr 2019.

  46. Futurist TM. The top 12 health chatbots. 2018. Available from: https://medicalfuturist.com/top-12-health-chatbots/. Accessed 29 Apr 2019.

  47. Pereira J, Diaz O. Using health ChatBots for behavior change: a mapping study. J Med Syst. 2019;43(5):135.

    Article  Google Scholar 

  48. National Multiple Sclerosis Society. 9-hole peg test (9-HPT). 2015. Available from: https://www.nationalmssociety.org/For-Professionals/Researchers/Resources-for-Researchers/Clinical-Study-Measures/9-Hole-Peg-Test-(9-HPT). Accessed 29 Apr 2019.

  49. The Council of the European Communities. Council Directive 93/42/EEC of 14 June 1993 concerning medical devices. 1993.

  50. The European Parliament and The Council of the European Union. Regulation (EU) 2017/745 of The European Parliament and of The Council of April 2017 on Medical Devices, amending Directive 2001/83/EC, Regulation (EC) No. 178/2002 and Regulation (EC) No. 1223/2009 and repealing Council Directives 90/385/EEC and 93/42/EEC.

  51. Gordon WJ, Catalini C. Blockchain technology for healthcare: facilitating the transition to patient-driven interoperability. Comput Struct Biotechnol J. 2018;16:224–30.

    Article  Google Scholar 

  52. USPTO Patent Full-Text and Image Database. [Search in Term 1 for “blockchain technology”]. 2019. Available from: https://patft.uspto.gov/netahtml/PTO/search-bool.html. Accessed 9 Mar 2019.

  53. Houlding D. Eight opportunities to advance AI in healthcare using blockchain. 2018. Available from: https://www.linkedin.com/pulse/8-opportunities-advance-ai-healthcare-using-houlding-cissp-cipp/. Accessed 29 April 2019.

Download references

Acknowledgements

We give special thanks to the contributions made to this article by Mahault Piéchaud Boura from the Timelex law firm based in Brussels, which specializes in information and technology law. Portions of this work were presented during an Issue Panel at the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) 21st European Congress in Barcelona, Spain in November 2018.

Funding

No funding was received for the preparation of this article.

Author information

Authors and Affiliations

  1. Health Economics and Healthcare Management Division, Kozminski University, 57/59 Jagiellonska St., 03-301, Warsaw, Poland

    Katarzyna Kolasa

  2. Global Market Access, Straub Medical, Switzerland Straub Medical AG, Wangs, Switzerland

    Katarzyna Kolasa

  3. Erasmus School of Health Policy and Management, Erasmus University, Rotterdam, The Netherlands

    W. Ken Redekop

  4. ZRx Outcomes Research Inc, Mississauga, ON, Canada

    Vladimir Zah

  5. University of Illinois College of Medicine, Peoria, IL, USA

    Carl V. Asche

  6. Gnomon Informatics SA, Thessaloniki, Greece

    Alexander Berler

Authors
  1. Katarzyna Kolasa
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. W. Ken Redekop
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Alexander Berler
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Vladimir Zah
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Carl V. Asche
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

KK, CA, KR, AB and VZ conceived of the presented idea. KK drafted initial manuscript with input from all authors. CA, KR, AB and VZ aided in interpreting the idea and worked on the manuscript. KK, CA, KR, AB and VZ discussed and equally contributed to the final version of the manuscript.

Corresponding author

Correspondence to Katarzyna Kolasa.

Ethics declarations

Conflict of interest

Katarzyna Kolasa, W. Ken Redekop, Alexander Berler, Vladimir Zah, and Carl V. Asche have no conflicts of interest that are directly relevant to the content of this article.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kolasa, K., Ken Redekop, W., Berler, A. et al. Future of Data Analytics in the Era of the General Data Protection Regulation in Europe. PharmacoEconomics 38, 1021–1029 (2020). https://doi.org/10.1007/s40273-020-00927-1

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40273-020-00927-1

Search

Navigation