The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index; none of the 3 sources its claims cite is checked for support yet.
"e-Iatrogenesis": The Most Critical Unintended Consequence of CPOE and other HIT
Open accessAbstract
In the September/October 2006 issues of JAMIA, Campbell et al.'s article “Types of Unintended Consequences Related to Computerized Provider Order Entry”1 lays out an innovative and comprehensive framework for categorizing the things that can go wrong when CPOE systems are implemented. We commend the authors for helping to move forward our collective understanding of this important area. As CPOE and other components of health information technology (HIT) logarithmically diffuse across the U.S. health care system, it is clear they will eventually become the standard all-encompassing platform for the delivery of medical care. As has been the case for all previous medical and non-medical technologies, HIT dissemination carries with it both positive and negative consequences. All nine types of “unintended consequences” outlined by Campbell et al. in their article should be of concern to health informaticists and others in involved in health care. We would like to suggest to the authors and your readers that one of the many unintended consequences they identified lurks as the most serious of all. Within Campbell et al.'s so-called “Type-7” category (new kinds of errors) is arguably the ultimate of unintended consequences: what we term “e-iatrogenesis.” We define e-iatrogenesis as patient harm caused at least in part by the application of health information technology. Our team has coined this new term as part of an ongoing Commonwealth Fund/Robert Wood Johnson Foundation supported project to develop new frameworks for measuring and promoting ambulatory care quality and safety within the HIT context. Using different labels, most scholarly discussion of actual or potential (i.e., “near-miss”) e-iatrogenic events have surrounded CPOE ordering errors, particularly relating to drugs or diagnostic tests.2–4 But we believe this is only the tip of the iceberg. An e-iatrogenic event can be associated with just about any aspect of a comprehensive HIT system and it may involve errors of commission or omission. These unintended adverse events may fall into technical, human-machine interface or organizational domains. Some e-iatrogenic events will represent the electronic version of “traditional” errors, such as a patient receiving the wrong drug dosage due to a human click-error. But other HIT precipitated or enabled errors may have no exact analog in the non-electronic context. For example, a clinical decision support system (CDSS) embedded within an electronic health record might contribute to a clinician's incorrect diagnosis or treatment plan; this could represent either a “type-one” or “two” error (e.g., making a diagnosis that was not present or missing one that was). Furthermore, while the focus of our discussion is human errors and technical design flaws, some e-iatrogenic events will not be due to errors, per se. Just as a properly used traditional medical intervention (e.g., a drug or procedure) may cause patient harm, it is inevitable that a well-designed HIT module used appropriately may also contribute to an undesirable outcome. As part of our ongoing development effort (known as the “e-indicator” quality measurement project) we are working with a consortium of five advanced HIT enabled integrated delivery systems, and we have also interviewed numerous early HIT adopters across the nation. Universally, we are hearing reports that e-iatrogenesis, and the broader area of unintended consequences, is of concern at all of these top-notch organizations. What will happen as HIT is rolled out at organizations further down the diffusion curve? By coining the term e-iatrogenesis and writing this letter our intent is to draw attention to this critical issue. We believe that both the health informatics and patient safety/quality communities must urgently collaborate to addresses this emerging problem. It is understandable that developers and vendors continue to promote the many ways that HIT can improve quality and reduce safety hazards. But we also believe it is imperative that all parties acknowledge that even with all its promise, CPOE and other types of health information technology represent a new 21st century vector for medical care-system induced harm—something we must all work to understand, measure, and mitigate.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
9 Own interpretation · 1 Not checked yet · 1 Own result
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Universally, we are hearing reports that e-iatrogenesis, and the broader area of unintended consequences, is of concern at all of these top-notch organizations.”
boosted- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Furthermore, while the focus of our discussion is human errors and technical design flaws, some e-iatrogenic events will not be due to errors, per se.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“But other HIT precipitated or enabled errors may have no exact analog in the non-electronic context.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: unclear — It is unclear why the paper says it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Some e-iatrogenic events will represent the electronic version of 'traditional' errors, such as a patient receiving the wrong drug dosage due to a human click-error.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“But we also believe it is imperative that all parties acknowledge that even with all its promise, CPOE and other types of health information technology represent a new 21st century vector for medical care-system induced harm-something we must all work to understand, measure, and mitigate.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Rests on an assumption: HIT dissemination carries both positive and negative consequences, as previous medical and non-medical technologies have done.
- Rests on an assumption: CPOE and other HIT will eventually become the standard all-encompassing platform for medical care delivery.
- Probably not a substantial claim. 4
- It may state two separate claims as one. 3
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Just as a properly used traditional medical intervention (e.g., a drug or procedure) may cause patient harm, it is inevitable that a well-designed HIT module used appropriately may also contribute to an undesirable outcome.”
boostedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“But we believe this is only the tip of the iceberg.”
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“These unintended adverse events may fall into technical, human-machine interface or organizational domains.”
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“For example, a clinical decision support system (CDSS) embedded within an electronic health record might contribute to a clinician's incorrect diagnosis or treatment plan; this could represent either a 'type-one' or 'two' error (e.g., making a diagnosis that was not present or missing one that was).”
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: unclear — It is unclear why the paper says it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“An e-iatrogenic event can be associated with just about any aspect of a comprehensive HIT system and it may involve errors of commission or omission.”
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“rounded CPOE ordering errors, particularly relating to drugs or diagnostic tests. 2-4”
What the sources say
- Not checked yetcites [2] 2. Ash JS, Sittig DS, Dykstra RH, Guappone, K, Carpenter, JD, Seshadri V. Categorizing the unintended societal consequences of computerized order entry. Int J Med Inform, (e-pub ahead of print) June 20, 2006. DOI 10.1016/ijmedinf.2006.05.017. Available at: http://intl.elsevierhealth.com/journals/ijmi/.
- Not checked yetcites [3] 3. Koppel R, Metlay JP, Cohen A, et al. Role of computerized physician order entry systems in facilitating medication errors. JAMA 2005;293(10):1197-1203. source
- Not checked yetcites [4] 4. McDonald CJ, Computerization can create safety hazards: A bar-coding near miss. Ann Int Med. 2006;144(7):510-516. source
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper relies on this without support.
HIT dissemination carries both positive and negative consequences, as previous medical and non-medical technologies have done.
“As has been the case for all previous medical and non-medical technologies, HIT dissemination carries with it both positive and negative consequences.”
The paper relies on this without support.
CPOE and other HIT will eventually become the standard all-encompassing platform for medical care delivery.
“As CPOE and other components of health information technology (HIT) logarithmically diffuse across the U.S. health care system, it is clear they will eventually become the standard all-encompassing platform for the delivery of medical care.”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“In particular, rapid adoption of electronic health records (EHRs) has revealed potential safety concerns related to EHR design, implementation, and use.12 17–21”
From An analysis of electronic health record-related patient safety concerns (2014) · cites this paper as [19]
In the citing paper
“the increasing adoption of electronic health records (EHR) has revealed potential safety implications related to EHR design, implementation, and use.”
From Exploring the sociotechnical intersection of patient safety and electronic health record implementation (2014) · cites this paper as [13]
Citations
Cites
Role of Computerized Physician Order Entry Systems in Facilitating Medication Errors
Koppel, R. (2005) · JAMA · doi:10.1001/jama.293.10.1197 · Cited by 2,126
Types of Unintended Consequences Related to Computerized Provider Order Entry
Campbell, E. M., Sittig, D. F., Ash, J. S., Guappone, K. P., & Dykstra, R. H. (2006) · Journal of the American Medical Informatics Association · doi:10.1197/jamia.m2042 · Cited by 823
Categorizing the unintended sociotechnical consequences of computerized provider order entry
Ash, J. S., Sittig, D. F., Dykstra, R. H., Guappone, K., Carpenter, J. D., & Seshadri, V. (2007) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2006.05.017 · Cited by 267
Computerization Can Create Safety Hazards: A Bar-Coding Near Miss
McDonald, C. J. (2006) · Annals of Internal Medicine · doi:10.7326/0003-4819-144-7-200604040-00010 · Cited by 146
Research works printed but not linked: 1
- International journal of medical informatics
Cited by
Sorted by citations
Harrison, M. I., Koppel, R., & Bar-Lev, S. (2007) · Journal of the American Medical Informatics Association · doi:10.1197/jamia.m2384 · Cited by 691
Middleton, B., Bloomrosen, M., Dente, M. A., Hashmat, B., Koppel, R., Overhage, J. M., Payne, T. H., Rosenbloom, S. T., Weaver, C., & Zhang, J. (2013) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2012-001458 · Cited by 618
GREENHALGH, T., POTTS, H. W. W., WONG, G., BARK, P., & SWINGLEHURST, D. (2009) · The Milbank Quarterly · doi:10.1111/j.1468-0009.2009.00578.x · Cited by 541
Clinical Information Technologies and Inpatient Outcomes
Amarasingham, R., Plantinga, L., Diener‐West, M., Gaskin, D. J., & Powe, N. R. (2009) · Archives of Internal Medicine · doi:10.1001/archinternmed.2008.520 · Cited by 355
An analysis of electronic health record-related patient safety concerns
Meeks, D. W., Smith, M. W., Taylor, L., Sittig, D. F., Scott, J. M., & Singh, H. (2014) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2013-002578 · Cited by 207
Metadata
- Authors
- Weiner, J. P., Kfuri, T., Chan, K., & Fowles, J. B.
- Affiliations
- Johns Hopkins University (US)
- Corresponding author
- Weiner, J. P.
- Venue
- Journal of the American Medical Informatics Association
- Publisher
- Oxford University Press (OUP)
- Published
- 2007-05-01
- Volume
- 14
- Issue
- 3
- Pages
- 387-388
- ISSN
- 1067-5027 (ISSN-L)
- 1527-974X
- PMC
- PMC2244888
- OpenAlex
- W2112033800
- Semantic Scholar
- ec32cd67f6ff2f654fd40bd38d08cc267dfc7d97
- Cited by
- 189
- References
- 4
- Citations by year
- 2026: 1 · 2025: 3 · 2024: 4 · 2023: 5 · 2022: 5 · 2021: 6 · 2020: 5 · 2019: 12 · 2018: 5 · 2017: 7 · 2016: 19 · 2015: 16 · 2014: 15 · 2013: 17 · 2012: 18
- FWCI
- 25.55
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of the American Medical Informatics Association (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- 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
- computerized physician order entry, patient harm, clinical decision support systems, electronic health records, medical errors, human-machine interaction, outpatient care, near misses, medication errors
- MeSH terms
- Humans, Iatrogenic Disease, Quality of Health Care, Medical Errors, Medical Order Entry Systems
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