Cited by 959Electronic Health Records SystemsPatient Safety and Medication ErrorsClinical Reasoning and Diagnostic Skills

Reducing the Frequency of Errors in Medicine Using Information Technology

Open access
Bates, D. W., Cohen, M., Leape, L. L., Overhage, J. M., Shabot, M. M., Sheridan, T.·2001·Journal of the American Medical Informatics Association

Abstract

BACKGROUND: Increasing data suggest that error in medicine is frequent and results in substantial harm. The recent Institute of Medicine report (LT Kohn, JM Corrigan, MS Donaldson, eds: To Err Is Human: Building a Safer Health System. Washington, DC: National Academy Press, 1999) described the magnitude of the problem, and the public interest in this issue, which was already large, has grown. GOAL: The goal of this white paper is to describe how the frequency and consequences of errors in medical care can be reduced (although in some instances they are potentiated) by the use of information technology in the provision of care, and to make general and specific recommendations regarding error reduction through the use of information technology. RESULTS: General recommendations are to implement clinical decision support judiciously; to consider consequent actions when designing systems; to test existing systems to ensure they actually catch errors that injure patients; to promote adoption of standards for data and systems; to develop systems that communicate with each other; to use systems in new ways; to measure and prevent adverse consequences; to make existing quality structures meaningful; and to improve regulation and remove disincentives for vendors to provide clinical decision support. Specific recommendations are to implement provider order entry systems, especially computerized prescribing; to implement bar-coding for medications, blood, devices, and patients; and to utilize modern electronic systems to communicate key pieces of asynchronous data such as markedly abnormal laboratory values. CONCLUSIONS: Appropriate increases in the use of information technology in health care- especially the introduction of clinical decision support and better linkages in and among systems, resulting in process simplification-could result in substantial improvement in patient safety.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1136/jamia.2001.0080299

Cites

43 of 43 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

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?

  • Emerging evidence suggests that health information technology may cause new patient safety concerns and other unintended consequences due to usability issues, disruptions of clinical processes, and unsafe workarounds.

    “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”
  • Technology can introduce new uncertainties and patient safety risks by disrupting established work patterns, creating new risks in practice, and encouraging workarounds.

    “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.”

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 6

  1. [8]8. Reason J. Human Error. Cambridge, UK: Cambridge University Press, 1990.
  2. [18]18. Gandhi TK, Seger DL, Bates DW. Identifying drug safety issuesfrom research to practice. Int J Qual Health Care 2000;12:69-76.
  3. [35]35. Kuperman G, Sittig DF, Shabot M, Teich J. Clinical decision support for hospital and critical care. J HIMSS. 1999;13:81-96.
  4. [39]39. Glaser J, Teich JM, Kuperman G. Impact of information events on medical care. Proceedings of the 1996 HIMSS Annual Conference. Chicago, Ill.: Healthcare Information and Management Systems Society, 1996:1-9.
  5. [40]40. Sarasota Memorial Hospital documents millions in expected cost savings, reduced LOS through use of Eclipsys' Sunrise Clinical Manager [press release]. Delray Beach, Fla.: Eclipsys Corporation; Oct 11, 1999. Available at: http:/ /www. eclipsys.com. Accessed Nov 8, 2000.
  6. [44]44. California Senate Bill No. 1875. Chapter 816, Statutes of 2000.

Cited by

Sorted by citations

Authors
Bates, D. W., Cohen, M., Leape, L. L., Overhage, J. M., Shabot, M. M., & Sheridan, T.
Affiliations
Harvard University (US)
Corresponding author
Bates, D. W.
Venue
Journal of the American Medical Informatics Association
Published
2001-07-01
Volume
8
Issue
4
Pages
299-308
ISSN
  • 1067-5027 (ISSN-L)
  • 1527-974X
OpenAlex
W2147886517
Cited by
959
References
43
Citations by year
2026: 11 · 2025: 15 · 2024: 17 · 2023: 18 · 2022: 17 · 2021: 17 · 2020: 17 · 2019: 33 · 2018: 38 · 2017: 35 · 2016: 39 · 2015: 51 · 2014: 66 · 2013: 44 · 2012: 44
FWCI
116.74
Type
journal article
Language
en
Open access
Locations
  • Journal of the American Medical Informatics Association (publishedVersion)
  • Europe PMC (PubMed Central) (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
  • DigitalGeorgetown (Georgetown University Library) (submittedVersion)
Topics
  • Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
  • Health Sciences › Health Professions › Emergency Medical Services › Patient Safety and Medication Errors
  • Health Sciences › Medicine › Family Practice › Clinical Reasoning and Diagnostic Skills
Keywords
medical errors, patient safety, clinical decision support, computerized prescribing, electronic health records, health information exchange, adverse event prevention, health information technology, To Err Is Human
MeSH terms
Humans, Drug Prescriptions, Quality of Health Care, Medical Records Systems, Computerized, Systems Integration, 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.

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