Towards quality management of medical information on the internet: evaluation, labelling, and filtering of informationHallmarks for quality of informationQuality on the internetAssuring quality and relevance of internet information in the real world
Open accessAbstract
# Towards quality management of medical information on the internet: evaluation, labelling, and filtering of information {#article-title-2} The principal dilemma of the internet is that, while its anarchic nature is desirable for fostering open debate without censorship, this raises questions about the quality of information available, which could inhibit its usefulness. While the internet allows “medical minority interest groups to access information of critical interest to them so that morbidity in these rare conditions can be lessened,”1 it also gives quacks such as the “cancer healer” Ryke Geerd Hamer a platform (http://www.geocities.com/HotSprings/3374/index.htm).2–4 Quality is defined as “the totality of characteristics of an entity that bear on its ability to satisfy stated and implied needs.”5 For quality to be evaluated, these needs have to be defined and translated into a set of quantitatively or qualitatively stated requirements for the characteristics of an entity that reflect the stated and implied needs. So how can we define consumers' “needs” in the case of medical information on the internet? The quality of medical information is particularly important because misinformation could be a matter of life or death.6 Thus, studies investigating the “quality of medical information” on the various internet venues—websites,7 mailing lists and newsgroups, 8 9 and in email communication between patients and doctors10—are mostly driven by the concern of possible endangerment for patients by low quality medical information. Thus, quality control measures should aim for the Hippocratic injunction “first, do no harm.” Most papers published so far about the problem of quality of medical internet information focus on assessing reliability, but, as box 1 shows, this should be only one aspect of quality measures aiming for “first, do no harm.” Another should be to provide context. Although these two problems are different in nature and different measures may be proposed to solve them, we discuss a common measure that could … Correspondence to: Dr Bonati
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eHealth literacy and preferences for eHealth resources in parents of children with complex CHD
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Self-citationLabeling and Filtering of Medical Information on the Internet
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Ethical Principles for Physician Rating Sites
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- Authors
- Eysenbach, G., Gray, J. A. M., Bonati, M., Arunachalam, S., Diepgen, T. L., Impicciatore, P., & Pandolfini, C.
- Affiliations
- Mario Negri Institute for Pharmacological Research (IT)
- Venue
- BMJ
- Publisher
- BMJ
- Published
- 1998-11-28
- Volume
- 317
- Issue
- 7171
- Pages
- 1496-1502
- ISSN
- 0007-1447 (ISSN-L)
- 0959-8138
- 1468-5833
- PMC
- PMC1114339
- OpenAlex
- W2080271974
- Cited by
- 461
- References
- 26
- Citations by year
- 2025: 4 · 2024: 4 · 2023: 1 · 2022: 4 · 2021: 8 · 2020: 9 · 2019: 10 · 2018: 10 · 2017: 5 · 2016: 10 · 2015: 13 · 2014: 16 · 2013: 18 · 2012: 13
- FWCI
- 10.37
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.bmj.com/company/legal-information/terms-conditions/legal-information/tdm-licencepolicy (tdm)
- Locations
- BMJ (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- HighWire Press Open Archive (submittedVersion)
- DigitalGeorgetown (Georgetown University Library) (submittedVersion)
- Topics
- Health Sciences › Health Professions › General Health Professions › Health Literacy and Information Accessibility
- Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
- Physical Sciences › Computer Science › Information Systems › Information Retrieval and Search Behavior
- Keywords
- online health information, quality management, information evaluation, information filtering, misinformation, reliability, context, patient safety, online health information sources
- MeSH terms
- Medical Informatics, Quality Control, Reference Standards, Information Storage and Retrieval, Internet
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 ›
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