Factors influencing physician prognosis: A scoping review
Open accessAbstract
Introduction. Prognosis is an essential component of informed consent for medical decision making. Research shows that physicians display discrepancies in their prognostication, leading to variable, inaccurate, optimistic, or pessimistic prognosis. Factors driving these discrepancies and the supporting evidence have not been reviewed systematically. Methods. We undertook a scoping review to explore the literature on the factors leading to discrepancies in medical prognosis. We searched Medline (Ovid) and Embase (Ovid) databases for peer-reviewed articles from 1970 to 2017. We included articles that discussed prognosis variation or discrepancy and where factors influencing prognosis were evaluated. We extracted data outlining the participants, methodology, and prognosis discrepancy information and measured factors influencing prognosis. Results. Of 4,723 articles, 73 were included in the final analysis. There was significant variability in research methodologies. Most articles showed that physicians were pessimistic regarding patient outcomes, particularly in early trainees and acute care specialties. Accuracy rates were similar across all time periods. Factors influencing prognosis were clustered in 4 categories: patient-related factors (such as age, gender, race, diagnosis), physician-related factors (such as age, race, gender, specialty, training and experience, attitudes and values), clinical situation-related factors (such as physician-patient relationship, patient location, and clinical context), and environmental-related factors (such as country or hospital size). Discussion. Obtaining accurate prognostic information is one of the highest priorities for seriously ill patients. The literature shows trends toward pessimism, especially in early trainees and acute care specialties. While some factors may prove difficult to change, the physician’s personality and psychology influence prognosis accuracy and could be tackled using debiasing strategies. Exposure to long-term patient outcomes and a multidisciplinary practice setting are environmental debiasing strategies that may warrant further research. Highlights Literature on discrepancies in physician’s prognostication is heterogeneous and sparse. Literature shows that physicians are mostly pessimistic regarding patient outcomes. Literature shows that a physician’s personality and psychology influence prognostic accuracy and could be improved with evidence-based debiasing strategies. Medical specialty strongly influences prognosis, with specialties exposed to acutely ill patients being more pessimistic, whereas specialties following patients longitudinally being more optimistic. Physicians early in their training were more pessimist than more experienced physicians.
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Further research has shown that physicians tend to be pessimistic in their prognosis of outcomes in seriously ill patients, and factors such as the physician's personality and attitudes have been shown to bias their prognosis.
“Further research has shown that physicians tend to be pessimistic in their prognosis of outcomes in seriously ill patients, and factors such as the physician’s personality and attitudes have been shown to bias their prognosis (23).”
From Assisted death in eating disorders: a systematic review of cases and clinical rationales (2024) · cites this paper as [23]
Prognostic accuracy is a significant challenge for psychiatry, and physicians' predictions of prognosis are often inaccurate, with a trend toward pessimism.
“Prognostic accuracy is a significant challenge for psychiatry, and research by Ferrand et al. (23) indicates that physicians’ predictions of prognosis are often inaccurate, with a trend toward pessimism.”
From Assisted death in eating disorders: a systematic review of cases and clinical rationales (2024) · cites this paper as Ferrand et al. (23)
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Flagged first, then by citations
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Research works printed but not linked: 1
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“Further research has shown that physicians tend to be pessimistic in their prognosis of outcomes in seriously ill patients, and factors such as the physician ’ s personality and attitudes have been shown to bias their prognosis (23).”
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Super-Refractory Status Epilepticus Diagnosis, Management, and Prognostication
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- Authors
- Ferrand, A., Poleksic, J., & Racine, E.
- Affiliations
- Jewish General Hospital (CA)
- Western University (CA)
- Pragmatic Health Ethics Research Unit, Montreal Clinical Research Institute, Montreal, QC, Canada
- Corresponding author
- Ferrand, Amaryllis
- ORCID
- Ferrand, Amaryllis
- Venue
- MDM Policy & Practice
- Publisher
- SAGE Publications
- Published
- 2022-07
- Volume
- 7
- Issue
- 2
- Pages
- 23814683221145158-23814683221145158
- ISSN
- 2381-4683 (ISSN-L)
- PMC
- PMC9793048
- OpenAlex
- W4313179187
- Cited by
- 29
- References
- 98
- Citations by year
- 2026: 5 · 2025: 11 · 2024: 10 · 2023: 3
- FWCI
- 1.19
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- MDM Policy & Practice (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Canadian Institutes of Health Research (Vanier Canada Doctoral Scholarship)
- Fonds de Recherche du Québec - Santé (Career Award)
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Palliative Care and End-of-Life Issues
- Health Sciences › Medicine › Family Practice › Clinical Reasoning and Diagnostic Skills
- Health Sciences › Health Professions › General Health Professions › Patient-Provider Communication in Healthcare
- Keywords
- physician-patient relationship, debiasing strategies, physician specialty differences, patient factors, informed consent, multidisciplinary practice
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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