Exploring the Value of Electronic Health Records from Multiple Datasets
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Abstract
During the last decades, most European countries dedicated huge efforts in collecting and maintaining Electronic Health Records (EHR). With the continuous grow of these datasets, it became obvious that its secondary use for research may lead to new insights about diseases and treatments outcomes.
EHR databases can be used to speed up and reduce the cost of health research studies, which are essential for the advance and improvement of health services. However, many times, a single observational data source is not enough for a clinical study, thus data interoperability has a major impact on the exploration of value of EHRs. Despite the recognized benefit of data sharing, database owners remain reluctant in conceding access to the contents of their databases, mainly due to ownership, privacy and security issues.
In this paper, we exploit two major international initiatives, the European Medical Information Framework (EMIF) and the Observational Health Data Sciences and Informatics (OHDSI), to provide a methodology through which multiple longitudinal clinical repositories can be queried, without the data leaving its original repository.
Keywords
Electronic Health Records Observational studies Data interoperability Clinical research Secondary useNotes
Acknowledgements
This work has received support from the EU/EFPIA Innovative Medicines Initiative Joint Undertaking (EMIF grant n. 115372), and from the Integrated Programme of SR&TD ‘SOCA’ (CENTRO-01-0145-FEDER-000010), co-funded by Centro 2020 program, Portugal 2020, European Union, through the European Regional Development Fund.
References
- 1.Cheng, H.G., Phillips, M.R.: Secondary analysis of existing data: opportunities and implementation. Shanghai Arch. Psychiatry 26(6), 371 (2014)Google Scholar
- 2.Cushman, R., Froomkin, A.M., Cava, A., Abril, P., Goodman, K.W.: Ethical, legal and social issues for personal health records and applications. J. Biomed. Inform. 43(5), S51–S55 (2010)CrossRefGoogle Scholar
- 3.Daniel, C., et al.: Cross border semantic interoperability for clinical research: the EHR4CR semantic resources and services. AMIA Summits Transl. Sci. Proc. 2016, 51 (2016)Google Scholar
- 4.Doods, J., Botteri, F., Dugas, M., Fritz, F.: A European inventory of common electronic health record data elements for clinical trial feasibility. Trials 15(1), 18 (2014)CrossRefGoogle Scholar
- 5.Doolan, D.M., Winters, J., Nouredini, S.: Answering research questions using an existing data set. Med. Res. Arch. 5(9), 1–14 (2017)Google Scholar
- 6.Fajarda, O., Silva, L.B., Rijnbeek, P., Van Speybroeck, M., Oliveira, J.L.: A methodology to perform semi-automatic distributed EHR database queries. In: 11th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2018), vol. 5, pp. 127–134 (2018)Google Scholar
- 7.Gini, R., et al.: Data extraction and management in networks of observational health care databases for scientific research: a comparison of EU-ADR, OMOP, Mini-Sentinel and MATRICE strategies. Egems 4(1), 1189 (2016)MathSciNetCrossRefGoogle Scholar
- 8.Hripcsak, G., et al.: Observational health data sciences and informatics (OHDSI): opportunities for observational researchers. Stud. Health Technol. Inform. 216, 574 (2015) Google Scholar
- 9.Huser, V., Kahn, M.G., Brown, J.S., Gouripeddi, R.: Methods for examining data quality in healthcare integrated data repositories. In: Pacific Symposium on Biocomputing (PSB), pp. 628–633 (2017)Google Scholar
- 10.Köpcke, F., Prokosch, H.U.: Employing computers for the recruitment into clinical trials: a comprehensive systematic review. J. Med. Internet Res. 16(7), e161 (2014)CrossRefGoogle Scholar
- 11.Lopes, P., Silva, L.B., Oliveira, J.L.: Challenges and opportunities for exploring patient-level data. BioMed Res. Int. 2015, 11 (2015)Google Scholar
- 12.Mann, C.: Observational research methods II: cohort, cross sectional, and case-control studies. Research design. Emerg. Med. J. 20(1), 54–60 (2003)CrossRefGoogle Scholar
- 13.McMurry, A.J., et al.: SHRINE: enabling nationally scalable multi-site disease studies. PLoS One 8(3), e55811 (2013)CrossRefGoogle Scholar
- 14.Meystre, S., Lovis, C., Bürkle, T., Tognola, G., Budrionis, A., Lehmann, C., et al.: Clinical data reuse or secondary use: current status and potential future progress. IMIA Yearb. 26, 38–52 (2017)Google Scholar
- 15.Miller, A.R., Tucker, C.: Health information exchange, system size and information silos. J. Health Econ. 33, 28–42 (2014)CrossRefGoogle Scholar
- 16.Murphy, S.N., et al.: Serving the enterprise and beyond with informatics for integrating biology and the bedside (i2b2). J. Am. Med. Inform. Assoc. 17(2), 124–130 (2010)CrossRefGoogle Scholar
- 17.Nass, S.J., Levit, L.A., Gostin, L.O., et al.: The value, importance, and oversight of health research. In: Beyond the HIPAA Privacy Rule: Enhancing Privacy Improving Health Through Research (2009)Google Scholar
- 18.Ohmann, C., Kuchinke, W.: Meeting the challenges of patient recruitment. Int. J. Pharm. Med. 21(4), 263–270 (2007)CrossRefGoogle Scholar
- 19.Pakhomov, S., Weston, S.A., Jacobsen, S.J., Chute, C.G., Meverden, R., Roger, V.L., et al.: Electronic medical records for clinical research: application to the identification of heart failure. Am. J. Manag. Care 13(6 Part 1), 281–288 (2007)Google Scholar
- 20.Piwowar, H.A., Chapman, W.W.: Public sharing of research datasets: a pilot study of associations. J. Informetr. 4(2), 148–156 (2010)CrossRefGoogle Scholar
- 21.Platt, R., Carnahan, R.: The us food and drug administration’s mini-sentinel program. Pharmacoepidemiol. Drug Saf. 21(S1), 1–303 (2012)Google Scholar
- 22.Pringle, S., Lippitt, A.: Interoperability of electronic health records and personal health records: key interoperability issues associated with information exchange. J. Healthc. Inf. Manag.: JHIM 23(3), 31–37 (2009)Google Scholar
- 23.Reisman, M.: EHRs: the challenge of making electronic data usable and interoperable. Pharm. Ther. 42(9), 572 (2017)Google Scholar
- 24.Schneeweiss, S., Avorn, J.: A review of uses of health care utilization databases for epidemiologic research on therapeutics. J. Clin. Epidemiol. 58(4), 323–337 (2005)CrossRefGoogle Scholar
- 25.Si, Y., Weng, C.: An OMOP CDM-based relational database of clinical research eligibility criteria. Stud. Health Technol. Inform. 245, 950 (2017)Google Scholar
- 26.Silva, L.B., Trifan, A., Oliveira, J.L.: MONTRA: an agile architecture for data publishing and discovery. Comput. Methods Programs Biomed. 160, 33–42 (2018)CrossRefGoogle Scholar
- 27.Trifan, A., Díaz, C., Oliveira, J., et al.: A methodology for fine-grained access control in exposing biomedical data. Stud. Health Technol. Inform. 247, 561–565 (2018)Google Scholar
- 28.Trifirò, G., et al.: Combining multiple healthcare databases for postmarketing drug and vaccine safety surveillance: why and how? J. Intern. Med. 275(6), 551–561 (2014)CrossRefGoogle Scholar
- 29.Weber, G.M., et al.: The shared health research information network (SHRINE): a prototype federated query tool for clinical data repositories. J. Am. Med. Inform. Assoc. 16(5), 624–630 (2009)CrossRefGoogle Scholar