Written informed consent and selection bias in observational studies using medical records: systematic review
Open accessAbstract
OBJECTIVES: To determine whether informed consent introduces selection bias in prospective observational studies using data from medical records, and consent rates for such studies. DESIGN: Systematic review. DATA SOURCES: Embase, Medline, and the Cochrane Library up to March 2008, reference lists from pertinent articles, and searches of electronic citations. STUDY SELECTION: Prospective observational studies reporting characteristics of participants and non-participants approached for informed consent to use their medical records. Studies were selected independently in duplicate; a third reviewer resolved disagreements. DATA EXTRACTION: Age, sex, race, education, income, or health status of participants and non-participants, the participation rate in each study, and susceptibility of these calculations to threats of selection and reporting bias. RESULTS: Of 1650 citations 17 unique studies met inclusion criteria and had analysable data. Across all outcomes there were differences between participants and non-participants; however, there was a lack of consistency in the direction and the magnitude of effect. Of 161 604 eligible patients, 66.9% consented to use of data from their medical records. CONCLUSIONS: Significant differences between participants and non-participants may threaten the validity of results from observational studies that require consent for use of data from medical records. To ensure that legislation on privacy does not unduly bias observational studies using medical records, thoughtful decision making by research ethics boards on the need for mandatory consent is necessary.
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The prospective 6-month study reported here showed similar results to 3-month data presented previously and similar glycemic control to a retrospective cohort using Bigfoot Unity.
“In general, the prospective 6-month study reported here showed similar results to 3-month data presented previously (35) and similar glycemic control to a retrospective cohort using Bigfoot Unity (34); here, the baseline HbA1c was higher (9.1% vs 8.4%), which may reflect health status or other demographic biases in those who consent to participate in an ongoing study vs those who do not (36).”
From Observed Glycemic and Psychosocial Benefits in the Prospective Bigfoot Unity Real World Study: A 6-Month Analysis (2025) · cites this paper as [36]
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- Authors
- Kho, M. E., Duffett, M., Willison, D. J., Cook, D. J., & Brouwers, M. C.
- Affiliations
- McMaster University (CA)
- McMaster Children's Hospital (CA)
- Cancer Care Ontario (CA)
- Corresponding author
- Kho, M. E
- Venue
- BMJ
- Publisher
- BMJ
- Published
- 2009-03-12
- Volume
- 338
- Issue
- mar12 2
- Pages
- b866-b866
- ISSN
- 0007-1447 (ISSN-L)
- 0959-8138
- 1468-5833
- PMC
- PMC2769263
- OpenAlex
- W2022496558
- Cited by
- 269
- References
- 22
- Citations by year
- 2026: 12 · 2025: 15 · 2024: 23 · 2023: 22 · 2022: 9 · 2021: 12 · 2020: 15 · 2019: 24 · 2018: 16 · 2017: 9 · 2016: 12 · 2015: 25 · 2014: 11 · 2013: 19 · 2012: 15
- FWCI
- 2.03
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by-nc
- Locations
- BMJ (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Funders
- Canadian Institutes of Health Research
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Ethics in Clinical Research
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Ethics and bioethics in healthcare
- Keywords
- written informed consent, selection bias, medical records, consent rates, research ethics committees, reporting bias
- MeSH terms
- Humans, Informed Consent, Medical Records, Research Design, Selection Bias
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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