The DOI matches its Crossref record; 85 of the 86 references it cites were found in a registry or an index.
Some Unintended Consequences of Information Technology in Health Care: The Nature of Patient Care Information System-related Errors
Open accessAbstract
Medical error reduction is an international issue, as is the implementation of patient care information systems (PCISs) as a potential means to achieving it. As researchers conducting separate studies in the United States, The Netherlands, and Australia, using similar qualitative methods to investigate implementing PCISs, the authors have encountered many instances in which PCIS applications seem to foster errors rather than reduce their likelihood. The authors describe the kinds of silent errors they have witnessed and, from their different social science perspectives (information science, sociology, and cognitive science), they interpret the nature of these errors. The errors fall into two main categories: those in the process of entering and retrieving information, and those in the communication and coordination process that the PCIS is supposed to support. The authors believe that with a heightened awareness of these issues, informaticians can educate, design systems, implement, and conduct research in such a way that they might be able to avoid the unintended consequences of these subtle silent errors.
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“Electronic health records (EHRs) are linked with documentation burden resulting in clinician burnout.”
From Measurement of clinical documentation burden among physicians and nurses using electronic health records: a scoping review (2021) · cites this paper as [9]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Poor accessibility of user interfaces may limit the benefits of health information systems and has been cited as a source of medical and user errors and health worker burnout.21–23”
From Effect of mobile application user interface improvements on minimum expected home visit coverage by community health workers in Mali: a randomised controlled trial (2021) · cites this paper as [21]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Application of AI systems in the real world may lead to many unintended outcomes, including alert fatigue,131 additional burdens for clinicians, disruption of interpersonal communications, and generation of specific threats requiring increased vigilance to recognize.132”
From Artificial intelligence in diabetes management: Advancements, opportunities, and challenges (2023) · cites this paper as [132]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“It is widely accepted that “alert fatigue” explains high override rates [7, 9–14].”
From Effects of workload, work complexity, and repeated alerts on alert fatigue in a clinical decision support system (2017) · cites this paper as [13]
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In the citing paper
“Digital systems frequently mediate clinical work in ways that reduce direct visibility of system state and process integrity.”
From Why digital health fails silently: a sociotechnical theory of health information technology–related risk (2026) · cites this paper as [5]
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In the citing paper
“CPOE systems prevent some types of errors while creating or propagating new ones.4,5,21,22,24,25,33,54 -61”
From Types of Unintended Consequences Related to Computerized Provider Order Entry (2006) · cites this paper as [5]
In the citing paper
“However, emerging evidence suggests that HIT may cause new patient safety concerns and other unintended consequences due to usability issues, disruptions of clinical processes, and unsafe workarounds to circumvent technology-related constraints.2–16”
From An analysis of electronic health record-related patient safety concerns (2014) · cites this paper as [3]
In the citing paper
“Building on previous approaches to examining healthcare IT incidents, our categorization expands the two high-level categories of humanecomputer and machine-related problems identified by others. 1 8”
From An analysis of computer-related patient safety incidents to inform the development of a classification (2010) · cites this paper as [1]
In the citing paper
“Two of our main categories map to the high-level error classes first identified by Ash et al. 1 'Information input problems' and 'information output problems' correspond to errors in 'entering and retrieving information', and 'information transfer problems' correspond to 'communication and co-ordination'.”
From An analysis of computer-related patient safety incidents to inform the development of a classification (2010) · cites this paper as [1]
In the citing paper
“research suggests that technology may lead to new uncertainties and risks for patient safety through disrupting established work patterns, creating new risks in practice, and encouraging workarounds.”
From Exploring the sociotechnical intersection of patient safety and electronic health record implementation (2014) · cites this paper as [3]
In the citing paper
“IT-based interventions alone, however, cannot assure improvements in communication.”
From Reducing Diagnostic Errors through Effective Communication: Harnessing the Power of Information Technology (2008) · cites this paper as [34]
In the citing paper
“In this paper, it is worthwhile to consider the goals of communication in the health care setting: often communication is not only intended to transfer information, but also to generate a response from the recipient of the information, such as taking an action and acknowledging receipt of the information.34”
From Reducing Diagnostic Errors through Effective Communication: Harnessing the Power of Information Technology (2008) · cites this paper as [34]
In the citing paper
“For instance, computerized information systems themselves can lead to unintended errors including those that involve communication processes.25,34,42”
From Reducing Diagnostic Errors through Effective Communication: Harnessing the Power of Information Technology (2008) · cites this paper as [34]
In the citing paper
“there is evidence that unintended adverse consequences can surround the implementation and ongoing maintenance of these systems.[8][9][10]”
From Computerized Provider Order Entry Adoption: Implications for Clinical Workflow (2009) · cites this paper as [8]
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Metadata
- Authors
- Ash, J. S.
- Affiliations
- Oregon Health & Science University (US)
- Corresponding author
- Ash, J. S.
- ORCID
- Ash, J. S.
- Venue
- Journal of the American Medical Informatics Association
- Publisher
- Oxford University Press (OUP)
- Published
- 2003-11-21
- Volume
- 11
- Issue
- 2
- Pages
- 104-112
- ISSN
- 1067-5027 (ISSN-L)
- 1527-974X
- PMC
- PMC353015
- OpenAlex
- W1787211267
- Cited by
- 1,789
- References
- 86
- Citations by year
- 2026: 45 · 2025: 32 · 2024: 42 · 2023: 45 · 2022: 42 · 2021: 62 · 2020: 69 · 2019: 93 · 2018: 75 · 2017: 78 · 2016: 108 · 2015: 106 · 2014: 106 · 2013: 132 · 2012: 142
- FWCI
- 101.69
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of the American Medical Informatics Association (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- U.S. National Library of Medicine (LM06942-02)
- Topics
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Patient Safety and Medication Errors
- Health Sciences › Health Professions › Health Information Management › Medical Coding and Health Information
- Keywords
- clinical information systems, medical errors, silent errors, medical error reduction, health informatics, system design and implementation
- MeSH terms
- Communication, Patient Care, Humans, Information Systems, Patient Care Management, User-Computer Interface, Information Storage and Retrieval, Medical Errors, Decision Support Systems, Clinical
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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