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
Bloomrosen, M., Starren, J. B., Lorenzi, N. M., Ash, J. S., Patel, V. L., & Shortliffe, E. H. (2010) · Journal of the American Medical Informatics Association · doi:10.1136/jamia.2010.007567 · Cited by 187
“have called attention to and coined a term for what they describe as the ultimate of unintended consequences associated with HIT: ‘e-iatrogenesis,’ defined as “patient harm caused at least in part by the application of health information technology.” They urge the healthcare industry to acknowledge that HIT represents…”
BackgroundDefining Health Information Technology–Related Errors
Sittig, D. F. (2011) · Archives of Internal Medicine · doi:10.1001/archinternmed.2011.327 · Cited by 167
Magrabi, F., Ong, M.-S., Runciman, W., & Coiera, E. (2010) · Journal of the American Medical Informatics Association · doi:10.1136/jamia.2009.002444 · Cited by 162
“The impact of computer use on patient safety is less well understood. Weiner and colleagues”
BackgroundHolden, R. J. (2010) · Cognition Technology & Work · doi:10.1007/s10111-010-0141-8 · Cited by 134
“C’’ error-based paradigm influences thinking about EMR is the newly coined term ‘‘e-iatrogenesis,’’ which can be defined as ‘‘error/harm caused (in part) by IT’’ (Weiner et al. 2007; but see Palmieri et al. 2009, for a more sophisticated treatment of the concept).”
BackgroundClinical decision support systems
Beeler, P. E., Bates, D. W., & Hug, B. L. (2014) · Swiss Medical Weekly · doi:10.4414/smw.2014.14073 · Cited by 168
Lainer, M., Mann, E., & Sönnichsen, A. C. (2013) · International Journal for Quality in Health Care · doi:10.1093/intqhc/mzt043 · Cited by 124
“Even more importantly, they raise safety concerns, which must be seen as an important component of e-iatrogenesis [28].”
BackgroundZiébland, S., Hyde, E., & powell, J. A. (2021) · Social Science & Medicine · doi:10.1016/j.socscimed.2021.114419 · Cited by 128
Adoption of Clinical Decision Support in Multimorbidity: A Systematic Review
Fraccaro, P., Casteleiro, M. A., Ainsworth, J. D., & Buchan, I. E. (2015) · JMIR Medical Informatics · doi:10.2196/medinform.3503 · Cited by 111
“The so called “e-iatrogenesis” [97] arising from information systems has more potential pitfalls when there are multiple conditions.”
Westbrook, J. I., Baysari, M. T., Li, L., Burke, R. A., Richardson, K. L., & Day, R. O. (2013) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2013-001745 · Cited by 113
The unintended consequences of health information technology revisited
Ash, J., Berg, M., & Coiera, E. (2016) · Yearbook of Medical Informatics · doi:10.15265/iy-2016-014 · Cited by 101
“These “new kinds of errors” are of particular interest because of their potential to do the greatest harm to patients, and have since been labeled by some as “e-iatrogenesis”[26], although patient harm can come from any of the classes identified.”
Singh, H., Mani, S., Espadas, D., Petersen, N., Franklin, V., & Petersen, L. A. (2009) · Archives of Internal Medicine · doi:10.1001/archinternmed.2009.102 · Cited by 104
Barlev, A. (2010) · Journal of Managed Care Pharmacy · doi:10.18553/jmcp.2010.16.9.693 · Cited by 104
Meeks, D. W., Takian, A., Sittig, D. F., Singh, H., & Barber, N. (2014) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2013-001762 · Cited by 91
The best person (or machine) for the job: Rethinking task shifting in healthcare
van Schalkwyk, M. C., Bourek, A., Kringos, D. S., Siciliani, L., Barry, M. M., Maeseneer, J. D., & McKee, M. (2020) · Health Policy · doi:10.1016/j.healthpol.2020.08.008 · Cited by 98
Harrington, L., Kennerly, D., & Johnson, C. (2011) · Journal of Healthcare Management · doi:10.1097/00115514-201101000-00006 · Cited by 93
McKee, M., van Schalkwyk, M. C., & Stückler, D. (2019) · European Journal of Public Health · doi:10.1093/eurpub/ckz160 · Cited by 81
Mediating the intersections of organizational routines during the introduction of a health IT system
Novak, L. L., Brooks, J. M., Gadd, C. S., Anders, S. H., & Lorenzi, N. M. (2012) · European Journal of Information Systems · doi:10.1057/ejis.2012.2 · Cited by 81
“…in health care informatics (Campbell et al , 2006; Ash et al , 2007) that points to a newly defined category of system failure and subsequent adverse patient outcomes referred to as ‘e-iatrogenesis’, or patient harm caused by health care technology (Koppel et al , 2005; Weiner et al , 2007).”
BackgroundA comparative review of patient safety initiatives for national health information technology
Magrabi, F., Aarts, J., Nøhr, C. G., Baker, M., Harrison, S., Sylvia Pelayo, A., Talmon, J. L., Sittig, D. F., & Coiera, E. W. (2012) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2012.11.014 · Cited by 74
Saleem, J. J., Russ, A. L., Sanderson, P., Johnson, T. R., Zhang, J., & Sittig, D. F. (2009) · Yearbook of Medical Informatics · doi:10.1055/s-0038-1638638 · Cited by 72
March, C. A., Steiger, D., Scholl, G., Mohan, V., Hersh, W., & Gold, J. A. (2013) · BMJ Open · doi:10.1136/bmjopen-2013-002549 · Cited by 64
“While EHRs can offer significant benefits, they can also foster errors in ways that paper documentation did not, a phenomenon that has been termed ‘e-iatrogenesis’.(9) At the most fundamental level, EHR software itself can be poorly designed and may promote errors such as radiation overdosing or miscalculating patient…”
BackgroundRedwood, S., Rajakumar, A., Hodson, J. A., & Coleman, J. J. (2011) · BMC Medical Informatics and Decision Making · doi:10.1186/1472-6947-11-29 · Cited by 71
“Some of the issues that have been identified are cognitive overload; loss of overview of the clinical situation; errors in data entry and retrieval; excessive reliance on electronically held data; disruptions of established workflow patterns and the tendency to infer that data entry equates to communication within and…”
BackgroundPalchuk, M. B., Fang, E., Cygielnik, J. M., Labreche, M. J., Shubina, M., Ramelson, H. Z., Hamann, C., Broverman, C. A., Einbinder, J. S., & Turchin, A. (2010) · Journal of the American Medical Informatics Association · doi:10.1136/jamia.2010.003335 · Cited by 71
Alami, H., Gagnon, M., & Fortin, J. (2019) · International Journal of Health Policy and Management · doi:10.15171/ijhpm.2019.12 · Cited by 58
Abraham, J., Novak, L. L., Reynolds, T. L., Gettinger, A., & Zheng, K. (2016) · Yearbook of Medical Informatics · doi:10.15265/iy-2016-036 · Cited by 61
McKee, M., & Wouters, O. J. (2022) · International Journal of Health Policy and Management · doi:10.34172/ijhpm.2022.7261 · Cited by 67
Frimpong, J. A., Jackson, B. E., Stewart, L. M., Singh, K. P., Rivers, P. A., & Bae, S. (2013) · BMC Health Services Research · doi:10.1186/1472-6963-13-35 · Cited by 70
“While technology may facilitate mechanisms that support process improvements, providers must implement systems (i.e., planning, training, technology driven improvements in physician productivity) that materialize technology based benefits [30,35,40].”
BackgroundKorb‐Savoldelli, V., Boussadi, A., Durieux, P., & Sabatier, B. (2017) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2017.12.022 · Cited by 69
Classification of medication incidents associated with information technology
Cheung, K., van der Veen, W., Bouvy, M. L., Wensing, M., van den Bemt, P. M. L. A., & Smet, P. A. G. M. D. (2013) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2013-001818 · Cited by 62
Wynn, M. O., Garwood‐Cross, L., Vasilica, C. M., Griffiths, M., Heaslip, V., & Phillips, N. (2023) · Journal of Advanced Nursing · doi:10.1111/jan.15810 · Cited by 53
Healthcare information technology and economics
Payne, T. H., Bates, D. W., Berner, E. S., Bernstam, E. V., Covvey, H. D., Frisse, M. E., Graf, T. R., Greenes, R. A., Hoffer, E. P., Kuperman, G. J., et al. (2012) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2012-000821 · Cited by 48
“The VA has made substantial investment in health IT.”
BackgroundInfluentialSafety huddles to proactively identify and address electronic health record safety
Menon, S., Singh, H., Giardina, T. D., Rayburn, W. L., Davis, B. P., Russo, E. M., & Sittig, D. F. (2016) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocw153 · Cited by 48
“These risks can emerge due to poor system design and usability, ineffective implementation of the system by the health care organization (HCO), or improper use of the system.(5,6) While some of the risks may not be apparent to users in a complex health care environment,(7) they have significant implications for patien…”
BackgroundPotential medication errors associated with computer prescriber order entry
Villamañán, E., Larrubia, Y., Ruano, M., Vélez, M., Armada, E., Herrero, A., & Álvarez-Sala, R. (2013) · International Journal of Clinical Pharmacy · doi:10.1007/s11096-013-9771-2 · Cited by 52
New paradigms for measuring clinical performance using electronic health records
Weiner, J. P., Fowles, J. B., & Chan, K. S. (2012) · International Journal for Quality in Health Care · doi:10.1093/intqhc/mzs011 · Cited by 53
“These measures document patient harm caused at least in part by the application of HIT [6].”
BackgroundSelf-citationRuss, A. L., Saleem, J. J., Justice, C. F., Woodward-Hagg, H., Woodbridge, P. A., & Doebbeling, B. N. (2010) · Health Informatics Journal · doi:10.1177/1460458210365981 · Cited by 44
Barnett, M. L., Mehrotra, A., & Jena, A. B. (2016) · BMJ · doi:10.1136/bmj.i3835 · Cited by 47
Kushniruk, A. W., Bellwood, P. S., Brender, J., & Borycki, E. M. (2011) · Methods of Information in Medicine · doi:10.3414/me11-02-0009 · Cited by 38
Общественное здоровье и здравоохранение
Глушанко, В. С. (2011) · Electronic archive of the library (Vitebsk State Medical University) · Cited by 39
Scott, I. A., Sullivan, C. M., & Staib, A. N. (2018) · Australian Health Review · doi:10.1071/ah17153 · Cited by 47
The anatomy and physiology of error in adverse health care events
Palmieri, P. A., DeLucia, P. R., Peterson, L. T., Ott, T. E., & Green, A. (2008) · Advances in health care management · doi:10.1016/s1474-8231(08)07003-1 · Cited by 38
Usability Flaws in Medication Alerting Systems: Impact on Usage and Work System
Ammenwerth, E., Roehrer, E., Sylvia Pelayo, A., Vasseur, F., Beuscart-Zéphir, M. C., & Marcilly, R. (2015) · Yearbook of Medical Informatics · doi:10.15265/iy-2015-006 · Cited by 35
“Scientific literature reports numerous case studies where the introduction of HIT in a work system has negative consequences on clinicians, and on different components of the work system, including patient safety [10-15].”
BackgroundCornu, P., Steurbaut, S., Gentens, K., de Velde, R. V., & Dupont, A. G. (2015) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2015.05.005 · Cited by 37
“close follow up of CDS interventions is warranted as uninended consequences may occur [37–40].”
BackgroundCritical information technology issues in Turkish healthcare
Turan, A. H., & Palvia, P. (2013) · Information & Management · doi:10.1016/j.im.2013.09.007 · Cited by 36
Failure to Provide Clinicians Useful IT Systems: Opportunities to Leapfrog Current Technologies
Silva, J. S., Bierstock, S., Douglas, J. V., Norcio, A. F., Chakraborty, J., Srini, J., & Ball, M. J. (2008) · Methods of Information in Medicine · doi:10.1055/s-0038-1625125 · Cited by 33
“Recent research on unintended adverse consequences [6] and “e-iatrogenesis” [7] (patient harm enabled or precipitated by health IT) documents the impact human factors have on healthcare delivery and outcomes – areas that health IT is intended to improve.”
BackgroundKuper, K. M., Nagel, J. L., RPhD, J. W. K., May, L. S., & Lee, F. M. (2019) · Infection Control and Hospital Epidemiology · doi:10.1017/ice.2019.51 · Cited by 35
“” 42 Although published studies have focused more on the frequency of e-iatrogenic events that occur upon computerized physician order entry, the potential for harm can occur at any point across with the technology spectrum.”
BackgroundForrer, C., Shaha, S. H., & Magid, S. K. (2012) · Applied Clinical Informatics · doi:10.4338/aci-2012-01-ra-0002 · Cited by 35
“The term “e-Iatrogenesis” was coined to describe patient harm caused “by the application of health information technology” [16].”
BackgroundWu, R. C., Tzanetos, K., Morra, D. J., Quan, S. D., Lo, V., & Wong, B. M. (2013) · Journal of Hospital Medicine · doi:10.1002/jhm.2037 · Cited by 34
Elshayib, M., & Pawola, L. M. (2020) · Health Informatics Journal · doi:10.1177/1460458220941750 · Cited by 33
“Researchers 45 have postulated that the “generating new kinds of errors” category is the most serious type of CPOE-related UCs.”
BackgroundSakata, K. K., Stephenson, L., Mulanax, A., Bierman, J., McGrath, K., Scholl, G., Adrienne, M., Bearden, D. T., Mohan, V., & Gold, J. A. (2016) · Journal of Interprofessional Care · doi:10.1080/13561820.2016.1193479 · Cited by 27
Electronic health record–related safety concerns: A cross‐sectional survey
Menon, S., Singh, H., Meyer, A. N. D., Belmont, E., & Sittig, D. F. (2014) · Journal of Healthcare Risk Management · doi:10.1002/jhrm.21146 · Cited by 29
Flamm, M., Fritsch, G., Hysek, M. H., Klausner, S., Entacher, K., Panisch, S., & Sönnichsen, A. C. (2013) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2012-001178 · Cited by 29
Borycki, E. M. (2013) · Healthcare Informatics Research · doi:10.4258/hir.2013.19.2.69 · Cited by 26
“There is general agreement among researchers and policymakers that technology-induced errors arise from a number of sources [10-16,18-20].”
BackgroundInfluentialInformation Technology Issues in Healthcare: Hospital CEO and CIO Perspectives
Palvia, P., Lowe, K. B., Nemati, H., & Jacks, T. (2012) · Communications of the Association for Information Systems · doi:10.17705/1cais.03019 · Cited by 29
Effects of CPOE-based medication ordering on outcomes: an overview of systematic reviews
Abraham, J., Kitsiou, S., Meng, A., Burton, S., Vatani, H., & Kannampallil, T. (2020) · BMJ Quality & Safety · doi:10.1136/bmjqs-2019-010436 · Cited by 31
“13 14 20 Most importantly, the direct impact of CPOEs in reducing medication errors and ADEs has also been questioned.”
BackgroundEffect of an electronic medication administration record application on patient safety
Oliveros, N. V., Gramage, T., Menéndez-Conde, C. P., et al. (2017) · Journal of Evaluation in Clinical Practice · doi:10.1111/jep.12753 · Cited by 27
“It is now well recognized that HIT innovations offer many benefits through the improved management of health information, but it should be taken into account that any new developments have the potential to introduce new errors and risks in healthcare delivery.(3,8,9) Thus, the unanticipated negative consequences of su…”
BackgroundSennesael, A., Krug, B., Sneyers, B., & Spinewine, A. (2020) · Thrombosis Research · doi:10.1016/j.thromres.2019.12.023 · Cited by 23
Vialle, V., Tiphine, T., Poirier, Y., Raingeard, E., Feldman, D., & Fréville, J.-C. (2011) · Annales Pharmaceutiques Françaises · doi:10.1016/j.pharma.2011.01.005 · Cited by 27
Novel Approaches and Their Applications in Risk Assessment
Luo, Y. (2012) · InTech eBooks · doi:10.5772/2548 · Cited by 26
Technological iatrogenesis: New risks force heightened management awareness
Palmieri, P. A., Peterson, L. T., & Ford, E. W. (2007) · Journal of Healthcare Risk Management · doi:10.1002/jhrm.5600270405 · Cited by 26
Improving Evaluation to Address the Unintended Consequences of Health Information Technology
Ammenwerth, E., Hyppönen, H., de Keizer, N. F., Nykänen, P., Rigby, M., Scott, P., Talmon, J. L., Georgiou, A., & Magrabi, F. (2016) · Yearbook of Medical Informatics · doi:10.15265/iy-2016-013 · Cited by 22
“While this paper specifically focused on the consequences of errors at the interface of IT and work practice, subsequent studies have examined a range of unintended consequences associated with the different types of IT [1, 3-5].”
BackgroundHealth Information Technology and Victory
Wears, R. L. (2014) · Annals of Emergency Medicine · doi:10.1016/j.annemergmed.2014.08.024 · Cited by 23
Pell, J. M., Cheung, D., Jones, M. A., & Cumbler, E. (2014) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2014-002777 · Cited by 22
Sittig, D. F., Campbell, E. M., Guappone, K. P., Dykstra, R. H., & Ash, J. S. (2007) · PubMed Central · Cited by 24
Challenges to ethics and professionalism facing the contemporary neurologist
Bernat, J. L. (2014) · Neurology · doi:10.1212/wnl.0000000000000845 · Cited by 20
“The harm to patients as a consequence of these practices has been termed e-iatrogenesis.(25) One common problem is caused by the ease of transferring electronic patient data.”
BackgroundMiller, M. E., Scholl, G., Corby, S., Mohan, V., & Gold, J. A. (2021) · JMIR Medical Education · doi:10.2196/25828 · Cited by 21
“The first is the increase in patient harm if the information is not entered, retrieved, or processed correctly, coined e-iatrogenesis [2].”
Background(2011) · American Journal of Health-System Pharmacy · doi:10.2146/sp100011e · Cited by 20
“These new problems are collectively known as e-iatrogenesis, which is defined as patient harm caused at least in part by the application of health IT.22 Though the systems themselves may contribute to these problems, design and implementation decisions play a role in the avoidance of these new errors. use process; and…”
Background(2015) · doi:10.3233/978-1-61499-564-7-264 · Cited by 20
“[12] as “patient harm caused at least in part by the application of health information technology”.”
BackgroundIntelligent Simulation Model To Facilitate EHR Training.
Mohan, V., Scholl, G., & Gold, J. A. (2015) · PubMed Central · Cited by 18
The Effect of a Novel Housestaff Quality Council on Quality and Patient Safety
Fleischut, P. M., Faggiani, S. L., Evans, A. S., Brenner, S. K., Liebowitz, R. S., Forese, L. L., Kerr, G. E., & Lazar, E. J. (2012) · The Joint Commission Journal on Quality and Patient Safety · doi:10.1016/s1553-7250(12)38041-0 · Cited by 18
Cornu, P., Steurbaut, S., Beukeleer, M. D., Putman, K. D., Velde, R. V. D., & Dupont, A. G. (2014) · Acta Clinica Belgica · doi:10.1179/2295333714y.0000000015 · Cited by 15
Abdelaziz, S., Garfield, S., Neves, A. L., Lloyd, J., Norton, J., van Dael, J., Wheeler, C., McLeod, M., & Franklin, B. D. (2024) · BMJ Open · doi:10.1136/bmjopen-2024-089026 · Cited by 19
“11 They may also have other unintended consequences, such as reducing patients’ opportunities for engaging with their healthcare.”
Phased implementation of electronic health records through an office of clinical transformation
Banas, C. A., Erskine, A., Sun, S. S., & Retchin, S. M. (2011) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2011-000165 · Cited by 17
“12 The term ‘ e-iatrogenesis ’ 13 has even been coined to refer to harm introduced as a result of conversion to electronic records.”
BackgroundThompson, C. A., Mebrahtu, T. F., Skyrme, S., Bloor, K. E., Andre, D., Keenan, A., Ledward, A., Yang, H., & Randell, R. (2023) · Health and Social Care Delivery Research · doi:10.3310/grnm5147 · Cited by 19
Integration of the Enterprise Electronic Health Record and Anesthesia Information Management Systems
Springman, S. R. (2011) · Anesthesiology Clinics · doi:10.1016/j.anclin.2011.05.007 · Cited by 17
Basit, M. A., Baldwin, K. L., Kannan, V., Flahaven, E. L., Parks, C. J., Ott, J. M., & Willett, D. L. (2018) · JMIR Medical Informatics · doi:10.2196/medinform.9679 · Cited by 15
“With the move to EHRs came recognition that unintended consequences can ensue [3,4], even jeopardizing patient safety [5,6].”
BackgroundMartin, G., Arora, S., Shah, N., King, D., & Darzi, A. W. (2019) · Health Informatics Journal · doi:10.1177/1460458219854602 · Cited by 15
POTTS, H. W. W., Keen, J., Denby, T., Featherstone, I., Patterson, D., Anderson, J. E., Greenhalgh, T., Colligan, L., Bark, P., Nicholls, J., et al. (2011) · White Rose Research Online (University of Leeds, The University of Sheffield, University of York) · Cited by 15
Health Care Information Technology
Liebovitz, D. (2009) · Archives of Internal Medicine · doi:10.1001/archinternmed.2009.79 · Cited by 14
Unintended consequences of health information technology: A need for biomedical informatics
Bernstam, E. V., Hersh, W., Sim, I., Eichmann, D. A., Silverstein, J. C., Smith, J. W., & Becich, M. J. (2009) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2009.05.009 · Cited by 14
“” [5] e-Iatrogenesis can result from a variety of factors involving any type of HIT.”
Small, K., Sidebotham, M., Gamble, J. A., & Fenwick, J. (2021) · Midwifery · doi:10.1016/j.midw.2021.103074 · Cited by 12
Hellot-Guersing, M., Jarre, C., Molina, C., Leromain, A., Derharoutunian, C., Gadot, A., & Roubille, R. (2015) · Annales Pharmaceutiques Françaises · doi:10.1016/j.pharma.2015.06.001 · Cited by 12
Pfeiffer, Y., Zimmermann, C., & Schwappach, D. L. B. (2020) · Journal of Patient Safety · doi:10.1097/pts.0000000000000640 · Cited by 12
“The term e-iatrogenesis has been coined to describe patient harm coming from HIT use.(12) Analyzing retrospectively patient safety event reports to investigate the negative impact of HITuse on patient safety(13,14) identified important HIT-related risks, such as poor user interface design leading to selecting the wron…”
BackgroundDiaz‐Garelli, F., Strowd, R. E., III, Ahmed, T., Lycan, T. W., Daley, S., Wells, B. J., & Topaloĝlu, Ü. (2021) · JCO Clinical Cancer Informatics · doi:10.1200/cci.20.00174 · Cited by 10
Harrington, L., Clyne, K. E., Fuchs, M. A., Hardison, V., & Johnson, C. (2013) · JONA The Journal of Nursing Administration · doi:10.1097/01.nna.0000434504.69428.a2 · Cited by 12
“Bar-code medication administration is a relatively new technology intended to prevent medication errors, yet problems were reported that are related to its use and in some cases have been the cause of medication errors.(7) As a high-risk, highvolume activity with potential serious consequences, the use of BCMA undersc…”
BackgroundTroubled Waters: Navigating Unintended Consequences of Health Information Technology
Lehmann, C. U., Brigitte Séroussi, A., & Jaulent, M. (2016) · Yearbook of Medical Informatics · doi:10.15265/iy-2016-056 · Cited by 13
“They described the introduction of technology-induced errors or “e-iatrogenesis” (as defined by Weiner et al [2]) as “patient harm caused at least in part by the application of health information technology”.”
BackgroundPerformance Measures Using Electronic Health Records: Five Case Studies
Fowles, J. B., Kind, E. A., & Awwad, S. (2008) · Cited by 12
Self-citationA Sociotechnical Approach to Electronic Health Record Related Safety
Sittig, D. F., & Singh, H. (2017) · Elsevier eBooks · doi:10.1016/b978-0-12-809523-2.00014-5 · Cited by 11
Vahabzadeh, M., Lin, J., Mezghanni, M., et al. (2009) · Drug and Alcohol Review · doi:10.1111/j.1465-3362.2008.00007.x · Cited by 11
“Readers interested in automating their own research clinics should be aware that automation in healthcare settings (which often have much in common with clinical-research settings) can result in a variety of unintended adverse consequences, such as loss of procedural flexibility, or commission of errors that would not…”
Wynn, M. O. (2025) · Nursing Inquiry · doi:10.1111/nin.70011 · Cited by 10
“This may result in what has been described as ‘ e ‐ iatrogensis ’ or harm related to the use of health information technology (Weiner et al. 2007).”
Palmieri, P. A., Peterson, L. T., & Corazzo, L. B. (2011) · Advances in health care management · doi:10.1108/s1474-8231(2011)0000010023 · Cited by 10
“These workflow changes often lead to adverse consequences (Kurtzman & Kizer, 2005), which manifest as e-iatrogenic errors (Weiner et al., 2007), the error product of technological iatrogenesis.”
Dufendach, K. R., Koch, S., Unertl, K., & Lehmann, C. U. (2017) · Methods of Information in Medicine · doi:10.3414/me16-01-0098 · Cited by 8
“E-iatrogenesis – the unintended negative consequences of implementing health information technology – had been described as early as 2007 [2].”
BackgroundDesign and Evaluation of a Smart Medication Recommendation System for the Electronic Prescription.
Zaveisadat, S. H. G., Etminani, K., Dehghan, H., Eslami, S., Hasibian, M. R., Vakili-Arki, H., Saberi, M. R., Aghabagheri, M., & Namayandeh, S. M. (2019) · PubMed · Cited by 11
Park, H. (2016) · Yearbook of Medical Informatics · doi:10.15265/iy-2016-028 · Cited by 7
Engineering an emr system in the developing world necessity is the mother of invention
Gadd, C. S., & Douglas, G. P. (2009) · D-Scholarship@Pitt (University of Pittsburgh) · Cited by 8
The 2016 AANS Presidential Address: Leading the way
Batjer, H. H., & Ban, V. S. (2016) · Journal of neurosurgery · doi:10.3171/2016.7.jns161273 · Cited by 8
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
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.
A language model drew the claims from the paper on 2026-10-07, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-10-07 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
