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BioMed Research International
Volume 2015, Article ID 380497, 13 pages
http://dx.doi.org/10.1155/2015/380497
Research Article

Effects of Shared Electronic Health Record Systems on Drug-Drug Interaction and Duplication Warning Detection

1Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna, 1090 Vienna, Austria
2Research Group Scientific Computing, University of Vienna, 1090 Vienna, Austria
3Department of Clinical Pharmacology, Medical University of Vienna, 1090 Vienna, Austria

Received 26 June 2015; Revised 8 September 2015; Accepted 18 October 2015

Academic Editor: Hans-Ulrich Prokosch

Copyright © 2015 Christoph Rinner et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. International Organization for Standardization, “Health informatics—electronic health record—definition, scope and context,” ISO/TR 20514:2005, International Organization for Standardization, London, UK, 2005. View at Google Scholar
  2. C. M. Cusack, “Electronic health records and electronic prescribing: promise and pitfalls,” Obstetrics and Gynecology Clinics of North America, vol. 35, no. 1, pp. 63–79, 2008. View at Publisher · View at Google Scholar · View at Scopus
  3. E. Ammenwerth, A.-F. Aly, T. Bürkle et al., “Memorandum on the use of information technology to improve medication safety,” Methods of Information in Medicine, vol. 53, no. 5, pp. 336–343, 2014. View at Publisher · View at Google Scholar · View at Scopus
  4. OECD, Improving Health Sector Efficiency. The Role of Information and Communication Technologies, 2010, http://ec.europa.eu/health/eu_world/docs/oecd_ict_en.pdf.
  5. J. L. Schnipper, C. Hamann, C. D. Ndumele et al., “Effect of an electronic medication reconciliation application and process redesign on potential adverse drug events: a cluster-randomized trial,” Archives of Internal Medicine, vol. 169, no. 8, pp. 771–780, 2009. View at Publisher · View at Google Scholar · View at Scopus
  6. A. D. Black, J. Car, C. Pagliari et al., “The impact of ehealth on the quality and safety of health care: a systematic overview,” PLoS Medicine, vol. 8, no. 1, Article ID e1000387, 2011. View at Publisher · View at Google Scholar · View at Scopus
  7. M. Lluch, “Healthcare professionals' organisational barriers to health information technologies—A literature review,” International Journal of Medical Informatics, vol. 80, no. 12, pp. 849–862, 2011. View at Publisher · View at Google Scholar · View at Scopus
  8. S. Herbek, H. A. Eisl, M. Hurch et al., “The electronic health record in Austria: a strong network between health care and patients,” European Surgery, vol. 44, no. 3, pp. 155–163, 2012. View at Publisher · View at Google Scholar · View at Scopus
  9. Integrating the Healthcare Enterprise (IHE), “IT Infrastructure Technical Framework,” 2010, http://www.ihe.net/Technical_Framework/index.cfm#IT.
  10. T. Steinschaden, G. Petersson, and B. Åstrand, “Physicians' attitudes towards eprescribing: a comparative web survey in Austria and Sweden,” Informatics in Primary Care, vol. 17, no. 4, pp. 241–248, 2009. View at Google Scholar · View at Scopus
  11. E. Ammenwerth, G. Duftschmid, W. Gall et al., “A nationwide computerized patient medication history: evaluation of the Austrian pilot project ‘e-Medikation’,” International Journal of Medical Informatics, vol. 83, no. 9, pp. 655–669, 2014. View at Publisher · View at Google Scholar · View at Scopus
  12. M. Mäkinen, P. Rautava, J. Forsström, and M. Äärimaa, “Electronic prescriptions are slowly spreading in the European Union,” Telemedicine and e-Health, vol. 17, no. 3, pp. 217–222, 2011. View at Publisher · View at Google Scholar · View at Scopus
  13. L. Hellström, K. Waern, E. Montelius, B. Strand, T. Rydberg, and G. Petersson, “Physicians' attitudes towards ePrescribing—evaluation of a Swedish full-scale implementation,” BMC Medical Informatics and Decision Making, vol. 9, article 37, 2009. View at Publisher · View at Google Scholar · View at Scopus
  14. I. Wolters, H. Hoogen, and D. Bakker, Evaluatie invoering Elektronisch Voorschrijf Systeem, Monitoringfase: de situatie in 2000, Institute for Health Services Research, Utrecht, The Netherlands, 2000, http://www.nivel.nl/pdf/evs.pdf.
  15. J. Harvey, A. J. Avery, R. Hibberd, and N. Barber, “Meeting user needs in national healthcare systems: lessons from early adopter community pharmacists using the electronic prescriptions service,” BMC Medical Informatics and Decision Making, vol. 14, article 16, 2014. View at Publisher · View at Google Scholar · View at Scopus
  16. A. Dogac, M. Yuksel, G. L. Ertürkmen et al., “Healthcare information technology infrastructures in Turkey,” Yearbook of Medical Informatics, vol. 9, no. 1, pp. 228–234, 2014. View at Publisher · View at Google Scholar
  17. A. F. Aly, K. Menges, C. H. Haas, L. Zimmermann, J. Kaltschmidt, and M. Criegee-Rieck, “Prerequisites for electronic systems evaluating safe and effective drug therapy. A contribution to the Action Plan of the Federal Health Ministry,” Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz, vol. 54, no. 11, pp. 1170–1178, 2011. View at Google Scholar
  18. S. Dechanont, S. Maphanta, B. Butthum, and C. Kongkaew, “Hospital admissions/visits associated with drug-drug interactions: a systematic review and meta-analysis,” Pharmacoepidemiology and Drug Safety, vol. 23, no. 5, pp. 489–497, 2014. View at Publisher · View at Google Scholar · View at Scopus
  19. R. M. Tamblyn, P. J. McLeod, M. Abrahamowicz, and R. Laprise, “Do too many cooks spoil the broth? Multiple physician involvement in medical management of elderly patients and potentially inappropriate drug combinations,” Canadian Medical Association Journal, vol. 154, no. 8, pp. 1177–1184, 1996. View at Google Scholar · View at Scopus
  20. M.-H. Hsu, Y.-T. Yeh, C.-Y. Chen, C.-H. Liu, and C.-T. Liu, “Online detection of potential duplicate medications and changes of physician behavior for outpatients visiting multiple hospitals using national health insurance smart cards in Taiwan,” International Journal of Medical Informatics, vol. 80, no. 3, pp. 181–189, 2011. View at Publisher · View at Google Scholar · View at Scopus
  21. A. Patapovas, H. Dormann, B. Sedlmayr et al., “Medication safety and knowledge-based functions: a stepwise approach against information overload,” British Journal of Clinical Pharmacology, vol. 76, supplement 1, pp. 14–24, 2013. View at Publisher · View at Google Scholar · View at Scopus
  22. K. C. Nanji, S. P. Slight, D. L. Seger et al., “Overrides of medication-related clinical decision support alerts in outpatients,” Journal of the American Medical Informatics Association, vol. 21, no. 3, pp. 487–491, 2014. View at Publisher · View at Google Scholar · View at Scopus
  23. S. Phansalkar, H. van der Sijs, A. D. Tucker et al., “Drug-drug interactions that should be non-interruptive in order to reduce alert fatigue in electronic health records,” Journal of the American Medical Informatics Association, vol. 20, no. 3, pp. 489–493, 2013. View at Publisher · View at Google Scholar · View at Scopus
  24. K. Furu, B. Wettermark, M. Andersen, J. E. Martikainen, A. B. Almarsdottir, and H. T. Sørensen, “The Nordic countries as a cohort for pharmacoepidemiological research,” Basic and Clinical Pharmacology and Toxicology, vol. 106, no. 2, pp. 86–94, 2010. View at Publisher · View at Google Scholar · View at Scopus
  25. S. A. Johannesdottir, E. Horváth-Puhó, V. Ehrenstein, M. Schmidt, L. Pedersen, and H. T. Sørensen, “Existing data sources for clinical epidemiology: the Danish National database of reimbursed prescriptions,” Clinical Epidemiology, vol. 4, no. 1, pp. 303–313, 2012. View at Google Scholar · View at Scopus
  26. E. Poluzzi, E. Raschi, C. Piccinni, and F. De Ponti, “Data mining techniques in pharmacovigilance: analysis of the publicly accessible FDA adverse event reporting system (AERS),” in Data Mining Applications in Engineering and Medicine, A. Karahoca, Ed., chapter 12, InTech, Rijeka, Croatia, 2012. View at Publisher · View at Google Scholar
  27. D. Edlinger, S. K. Sauter, C. Rinner et al., “JADE: a tool for medical researchers to explore adverse drug events using health claims data,” Applied Clinical Informatics, vol. 5, no. 3, pp. 621–629, 2014. View at Publisher · View at Google Scholar · View at Scopus
  28. C. Rinner, S. K. Sauter, L. M. Neuhofer et al., “Estimation of severe drug-drug interaction warnings by medical specialist groups for Austrian nationwide eMedication,” Applied Clinical Informatics, vol. 5, no. 3, pp. 603–611, 2014. View at Publisher · View at Google Scholar · View at Scopus
  29. E. C. Lehnbom, A. J. McLachlan, and J. A. Brien, “A qualitative study of swedes' opinions about shared electronic health records,” Studies in Health Technology and Informatics, vol. 192, pp. 3–7, 2013. View at Google Scholar
  30. A. Lux, “Cost-benefit analysis of a new health insurance card and electronic prescription in Germany,” Journal of Telemedicine and Telecare, vol. 8, supplement 2, pp. 54–55, 2002. View at Publisher · View at Google Scholar · View at Scopus
  31. S. T. Corley, “Electronic prescribing: a review of costs and benefits,” Topics in Health Information Management, vol. 24, no. 1, pp. 29–38, 2003. View at Google Scholar · View at Scopus
  32. S. Bowman, “Impact of electronic health record systems on information integrity: quality and safety implications,” Perspectives in Health Information Management, vol. 10, article 1c, 2013. View at Google Scholar
  33. WHO, The Nine Patient Safety Solutions: WHO Collaborating Centre for Patient Safety Solutions 2007, WHO, 2007, http://www.who.int/patientsafety/events/07/02_05_2007/en/index.html.
  34. Statistik Austria, “Jahresdurchschnittsbevölkerung seit 2002 nach fünfjährigen Altersgruppen und Geschlecht,” 2012, http://www.statistik.at/web_de/statistiken/bevoelkerung/bevoelkerungsstruktur/bevoelkerung_nach_alter_geschlecht/023427.html.
  35. WHO Collaborating Centre for Drug Statistics Methodology, “ATC/DDD Index 2014,” 2014, http://www.whocc.no/atc_ddd_index/.
  36. Österreichische Apotheker-Verlagsgesellschaft, Austria-Codex 2006, http://www3.apoverlag.at/dynasite.cfm?dsmid=106234.
  37. C. J. Clopper and E. S. Pearson, “The use of confidence or fiducial limits illustrated in the case of the binomial,” Biometrika, vol. 26, no. 4, pp. 404–413, 1934. View at Publisher · View at Google Scholar
  38. W. Gall, L. M. Neuhofer, C. Rinner et al., “Relationship of drug-drug interactions with hospital diagnoses associated to adverse drug reactions: a retrospective study of billing data in Austria,” International Journal of Clinical Pharmacology & Toxicology, pp. 1–6, 2015. View at Publisher · View at Google Scholar
  39. A. Tanskanen, H. Taipale, M. Koponen et al., “From prescription drug purchases to drug use periods—a second generation method (PRE2DUP),” BMC Medical Informatics and Decision Making, vol. 15, article 21, 2015. View at Publisher · View at Google Scholar
  40. W. O. Hackl, A. Hoerbst, G. Duftschmid et al., “Crucial factors for the acceptance of a computerized national medication list: insights into findings from the evaluation of the Austrian e-Medikation Pilot,” Applied Clinical Informatics, vol. 5, no. 2, pp. 527–537, 2014. View at Publisher · View at Google Scholar · View at Scopus