Yearb Med Inform 2016; 25(01): 163-169
DOI: 10.15265/IY-2016-014
IMIA and Schattauer GmbH
Georg Thieme Verlag KG Stuttgart

The Unintended Consequences of Health Information Technology Revisited

E. Coiera
1   Australian Institute of Health Innovation, Macquarie University, Australia
,
J. Ash
2   Department of Medical Informatics and Clinical Epidemiology, School of Medicine, Oregon Health & Science University, USA
,
M. Berg
3   Principal, Advisory, KPMG LLP (US)
› Author Affiliations
Further Information

Publication History

10 November 2016

Publication Date:
06 March 2018 (online)

Summary

Introduction: The introduction of health information technology into clinical settings is associated with unintended negative consequences, some with the potential to lead to error and patient harm. As adoption rates soar, the impact of these hazards will increase.

Objective: Over the last decade, unintended consequences have received great attention in the medical informatics literature, and this paper seeks to identify the major themes that have emerged.

Results: Rich typologies of the causes of unintended consequences have been developed, along with a number of explanatory frameworks based on socio-technical systems theory. We however still have only limited data on the frequency and impact of these events, as most studies rely on data sets from incident reporting or patient chart reviews, rather than undertaking detailed observational studies. Such data are increasingly needed as more organizations implement health information technologies. When outcome studies have been done in different organizations, they reveal different outcomes for identical systems. From a theoretical perspective, recent advances in the emerging discipline of implementation science have much to offer in explaining the origin, and variability, of unintended consequences.

Conclusion: The dynamic nature of health care service organizations, and the rapid development and adoption of health information technologies means that unintended consequences are unlikely to disappear, and we therefore must commit to developing robust systems to detect and manage them.

 
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