Healthc Inform Res.  2013 Jun;19(2):69-78. 10.4258/hir.2013.19.2.69.

Trends in Health Information Technology Safety: From Technology-Induced Errors to Current Approaches for Ensuring Technology Safety

Affiliations
  • 1School of Health Information Science, University of Victoria, Victoria, BC, Canada. emb@uvic.ca

Abstract


OBJECTIVES
Health information technology (HIT) research findings suggested that new healthcare technologies could reduce some types of medical errors while at the same time introducing classes of medical errors (i.e., technology-induced errors). Technology-induced errors have their origins in HIT, and/or HIT contribute to their occurrence. The objective of this paper is to review current trends in the published literature on HIT safety.
METHODS
A review and synthesis of the medical and life sciences literature focusing on the area of technology-induced error was conducted.
RESULTS
There were four main trends in the literature on technology-induced error. The following areas were addressed in the literature: definitions of technology-induced errors; models, frameworks and evidence for understanding how technology-induced errors occur; a discussion of monitoring; and methods for preventing and learning about technology-induced errors.
CONCLUSIONS
The literature focusing on technology-induced errors continues to grow. Research has focused on the defining what an error is, models and frameworks used to understand these new types of errors, monitoring of such errors and methods that can be used to prevent these errors. More research will be needed to better understand and mitigate these types of errors.

Keyword

Health Information Systems; Patient Safety; Risk Management; Technology-Induced Error

MeSH Terms

Biological Science Disciplines
Delivery of Health Care
Health Information Systems
Learning
Medical Errors
Medical Informatics
Patient Safety
Risk Management

Cited by  2 articles

Review of Social and Organizational Issues in Health Information Technology
Craig E. Kuziemsky
Healthc Inform Res. 2015;21(3):152-160.    doi: 10.4258/hir.2015.21.3.152.

Clinical Alarms in Intensive Care Units: Perceived Obstacles of Alarm Management and Alarm Fatigue in Nurses
Ok Min Cho, Hwasoon Kim, Young Whee Lee, Insook Cho
Healthc Inform Res. 2016;22(1):46-53.    doi: 10.4258/hir.2016.22.1.46.


Reference

1. Wilson RM, Runciman WB, Gibberd RW, Harrison BT, Newby L, Hamilton JD. The quality in australian health care study. Med J Aust. 1995. 163(9):458–471.
Article
2. Baker GR, Norton PG, Flintoft V, Blais R, Brown A, Cox J, et al. The Canadian Adverse Events Study: the incidence of adverse events among hospital patients in Canada. CMAJ. 2004. 170(11):1678–1686.
Article
3. Brennan TA, Leape LL, Laird NM, Hebert L, Localio AR, Lawthers AG, et al. Incidence of adverse events and negligence in hospitalized patients: results of the Harvard Medical Practice Study I. N Engl J Med. 1991. 324(6):370–376.
Article
4. Vincent C, Neale G, Woloshynowych M. Adverse events in British hospitals: preliminary retrospective record review. BMJ. 2001. 322(7285):517–519.
Article
5. Kohn LT, Corrigan JM, Donaldson MS. Institute of Medicine. To err is human: building a safer health system. 2000. Washington (DC): National Academy Press.
6. Committee on Data Standards for Patient Safety. Institute of Medicine. Patient safety: achieving a new standard for care. 2004. Washington (DC): National Academies Press.
7. Kaushal R, Shojania KG, Bates DW. Effects of computerized physician order entry and clinical decision support systems on medication safety: a systematic review. Arch Intern Med. 2003. 163(12):1409–1416.
Article
8. Bates DW. Using information technology to reduce rates of medication errors in hospitals. BMJ. 2000. 320(7237):788–791.
Article
9. Menke JA, Broner CW, Campbell DY, McKissick MY, Edwards-Beckett JA. Computerized clinical documentation system in the pediatric intensive care unit. BMC Med Inform Decis Mak. 2001. 1:3.
Article
10. Borycki EM, Kushniruk AW, Keay L, Kuo A. A framework for diagnosing and identifying where technology-induced errors come from. Stud Health Technol Inform. 2009. 148:181–187.
11. Koppel R, Metlay JP, Cohen A, Abaluck B, Localio AR, Kimmel SE, et al. Role of computerized physician order entry systems in facilitating medication errors. JAMA. 2005. 293(10):1197–1203.
Article
12. Kushniruk AW, Triola MM, Borycki EM, Stein B, Kannry JL. Technology induced error and usability: the relationship between usability problems and prescription errors when using a handheld application. Int J Med Inform. 2005. 74(7-8):519–526.
Article
13. Borycki E, Kushniruk A. Identifying and preventing technology-induced error using simulations: application of usability engineering techniques. Healthc Q. 2005. 8 Spec No:99–105.
Article
14. Magrabi F, Ong MS, Runciman W, Coiera E. An analysis of computer-related patient safety incidents to inform the development of a classification. J Am Med Inform Assoc. 2010. 17(6):663–670.
Article
15. Magrabi F, Ong MS, Runciman W, Coiera E. Using FDA reports to inform a classification for health information technology safety problems. J Am Med Inform Assoc. 2012. 19(1):45–53.
Article
16. Ash JS, Sittig DF, Poon EG, Guappone K, Campbell E, Dykstra RH. The extent and importance of unintended consequences related to computerized provider order entry. J Am Med Inform Assoc. 2007. 14(4):415–423.
Article
17. Borycki EM, Kushniruk AW. Towards an integrative cognitive-socio-technical approach in health informatics: analyzing technology-induced error involving health information systems to improve patient safety. Open Med Inform J. 2010. 4:181–187.
Article
18. Weiner JP, Kfuri T, Chan K, Fowles JB. "e-Iatrogenesis": the most critical unintended consequence of CPOE and other HIT. J Am Med Inform Assoc. 2007. 14(3):387–388.
Article
19. Kuziemsky CE, Borycki E, Nohr C, Cummings E. The nature of unintended benefits in health information systems. Stud Health Technol Inform. 2012. 180:896–900.
20. Institute of Medicine. Health IT and patient safety: building safer systems for better care. 2012. Washington (DC): National Academies Press.
21. Borycki EM, Kushniruk AW, Bellwood P, Brender J. Technology-induced errors. The current use of frameworks and models from the biomedical and life sciences literatures. Methods Inf Med. 2012. 51(2):95–103.
22. Aarts J. Towards Safe Electronic Health Records: a socio-technical perspective and the need for incident reporting. Health Policy Tech. 2012. 1(1):8–15.
Article
23. Horsky J, Kuperman GJ, Patel VL. Comprehensive analysis of a medication dosing error related to CPOE. J Am Med Inform Assoc. 2005. 12(4):377–382.
Article
24. Campbell EM, Sittig DF, Ash JS, Guappone KP, Dykstra RH. Types of unintended consequences related to computerized provider order entry. J Am Med Inform Assoc. 2006. 13(5):547–556.
Article
25. Borycki EM, Househ MS, Kushniruk AW, Nohr C, Takeda H. Empowering patients: making health information and systems safer for patients and the public. Contribution of the IMIA health informatics for patient safety working group. Yearb Med Inform. 2012. 7(1):56–64.
26. Kushniruk A, Beuscart-Zephir MC, Grzes A, Borycki E, Watbled L, Kannry J. Increasing the safety of healthcare information systems through improved procurement: toward a framework for selection of safe healthcare systems. Healthc Q. 2010. 13 Spec No:53–58.
Article
27. Singh H, Ash JS, Sittig DF. Safety Assurance Factors for Electronic Health Record Resilience (SAFER): study protocol. BMC Med Inform Decis Mak. 2013. 13:46.
Article
28. Kuwata S, Kushniruk A, Borycki E, Watanabe H. Using simulation methods to analyze and predict changes in workflow and potential problems in the use of a barcoding medication order entry system. AMIA Annu Symp Proc. 2006. 2006:994.
29. Koppel R, Wetterneck T, Telles JL, Karsh BT. Workarounds to barcode medication administration systems: their occurrences, causes, and threats to patient safety. J Am Med Inform Assoc. 2008. 15(4):408–423.
Article
30. Elkin PL. Human factors engineering in HI: so what? who cares? and what's in it for you? Healthc Inform Res. 2012. 18(4):237–241.
Article
31. Han YY, Carcillo JA, Venkataraman ST, Clark RS, Watson RS, Nguyen TC, et al. Unexpected increased mortality after implementation of a commercially sold computerized physician order entry system. Pediatrics. 2005. 116(6):1506–1512.
Article
32. Del Beccaro MA, Jeffries HE, Eisenberg MA, Harry ED. Computerized provider order entry implementation: no association with increased mortality rates in an intensive care unit. Pediatrics. 2006. 118(1):290–295.
Article
33. Ammenwerth E, Talmon J, Ash JS, Bates DW, Beuscart-Zephir MC, Duhamel A, et al. Impact of CPOE on mortality rates-contradictory findings, important messages. Methods Inf Med. 2006. 45(6):586–593.
34. Borycki E, Keay E. Methods to assess the safety of health information systems. Healthc Q. 2010. 13 Spec No:47–52.
Article
35. Samaranayake NR, Cheung ST, Chui WC, Cheung BM. Technology-related medication errors in a tertiary hospital: a 5-year analysis of reported medication incidents. Int J Med Inform. 2012. 81(12):828–833.
Article
36. Kaner C, Falk JL, Nguyen HQ. Testing computer software. 1999. 2nd ed. New York (NY): Wiley.
37. Carvalho CJ, Borycki EM, Kushniruk AW. Using heuristic evaluations to assess the safety of health information systems. Stud Health Technol Inform. 2009. 143:297–301.
38. Usability Body of Knowledge. Cognitive walkthrough [Internet]. 2010. cited at 2013 May 25. Bloomingdale (IL): User Experience Professionals Association;Available from: http://www.usabilitybok.org/cognitivewalkthrough.
39. Nielsen J. Heuristic evaluation [Internet]. 2013. cited at 2013 May 25. Fremont (CA): Nielsen Norman Group;Available from http://www.nngroup.com/topic/heuristic-evaluation/.
40. Kushniruk AW, Patel VL. Cognitive and usability engineering methods for the evaluation of clinical information systems. J Biomed Inform. 2004. 37(1):56–76.
Article
41. Borycki EM, Kushniruk AW, Kuwata S, Kannry J. Engineering the Electronic Health Record for safety: a multilevel video-based approach to diagnosing and preventing technology-induced error arising from usability problems. Stud Health Technol Inform. 2011. 166:197–205.
42. Borycki EM, Kushniruk AW, Kuwata S, Kannry J. Use of simulation in the study of clinician workflow. AMIA Annu Symp Proc. 2006. 2006:61–65.
43. Borycki E, Kushniruk A, Carvalho C. A methodology for validating safety heuristics using clinical simulations: identifying and preventing possible technology-induced errors related to using health information systems. Comput Math Methods Med. 2013. 2013:526419.
Article
44. Borycki EM, Kushniruk A, Keay E, Nicoll J, Anderson J, Anderson M. Toward an integrated simulation approach for predicting and preventing technology-induced errors in healthcare: implications for healthcare decision-makers. Healthc Q. 2009. 12 Spec No Patient:90–96.
Article
45. Anderson JG, Aydin CE. Evaluating the organizational impact of health care information systems. 2005. New York (NY): Springer.
46. Baylis TB, Kushniruk AW, Borycki EM. Low-cost rapid usability testing for health information systems: is it worth the effort? Stud Health Technol Inform. 2012. 180:363–367.
47. Ash JS, Sittig DF, McMullen CK, Guappone K, Dykstra R, Carpenter J. A rapid assessment process for clinical informatics interventions. AMIA Annu Symp Proc. 2008. 2008:26–30.
48. Patton R. Sofware testing. 2001. Indianapolis (IN): SAMS.
49. Martin J, McClure CL. Software maintenance: the problem and its solutions. 1983. Englewood Cliffs (NJ): Prentice-Hall.
Full Text Links
  • HIR
Actions
Cited
CITED
export Copy
Close
Share
  • Twitter
  • Facebook
Similar articles
Copyright © 2024 by Korean Association of Medical Journal Editors. All rights reserved.     E-mail: koreamed@kamje.or.kr