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Record W1503729777

How Doctors Think.

2008· article· en· W1503729777 on OpenAlexvenueno aff
Chenjie Xia

Bibliographic record

VenueMcGill Journal of Medicine · 2008
Typearticle
Languageen
FieldMedicine
TopicEmpathy and Medical Education
Canadian institutionsnot available
Fundersnot available
KeywordsJargonMedicineDiscernmentStorytellingHealth carePsychologyNarrativeEpistemologyLiterature
DOInot available

Abstract

fetched live from OpenAlex

In his latest book, How Doctors Think, Dr. Groopman, a haematologist affiliated with Harvard Medical School, takes the readers on a tour of a wide range of medical fields while jumping swiftly back-and-forth between the physician and the patient’s perspective. Most chapters open with the story of an individual patient and his doctor, whose interactions introduce us to an aspect of problem-solving in medicine. The author then further expands upon the subject in an essay form by weaving into the storytelling opinions from experts of cognitive thinking in medicine as well as evidence from recent research work on the topic. The stories, although slightly melodramatic at times with their predictable climax followed by a happily-ever-after resolution, do provide an accurate and helpful glimpse of the complex infrastructures of health care to those unfamiliar with the field. Dr. Groopman possesses a quite impressive ability for stripping medical facts of their jargon and rendering them accessible to laymen. Each story directs his lens onto particular “cognitive errors” in the practice of medicine, a term he uses to describe flaws in the thinking of physicians that result in misdiagnosis and/or mismanagement of illnesses. Then, deftly alternating the focus between the analysis and the story, he intertwines theory and practice to demonstrate how these mental traps can be averted. A common belief among the general public, fuelled by popular entertainment media, unreservedly equates advanced technology with better medical care. Although health care providers attempt to show a bit more discernment toward the magnetic attraction of technology, we nevertheless find ourselves engulfed by this tornado of armamentarium that allows us to see deeper and smaller into the human body. Certainly, new technology is not portent of the downfall of medicine, on the contrary. But Dr. Groopman guards us against the looming danger of relegating to the back row the time-old skills of speaking and listening to the patient in favour of simply relying on faster and easier tests in making a diagnosis. Example after example, he highlights the risk of overlooking important subtleties, nuances and ambiguities in a patient’s illness if we are not tuned in to their speech, their body language, their personal background. In a similar argument, he calls upon our caution in facing the increasingly influential presence of algorithms and guidelines in clinical practice. He asserts that these recipe-like approaches lead to cognitive errors in hindering creativity and flexibility of our thinking. He concedes that medicine is dominated by uncertainty and practiced with trial-and-error, and it is thus by no hazard that an atmosphere of conformity in medical practice is required to provide a certain structure. However, he urges us to never become passive followers of orthodoxy, to always challenge the rigor and validity of what we are taught and what we believe to be the truth. To those who assert doctors will no longer be needed with the increasing widespread access to information and the technological advancement of diagnosis and treatment modalities, How Doctors Think provides a resounding counterargument to their preposterous claim. Through his vivid story-telling, where individual doctors, the pediatrician, the endocrinologist, the plastic surgeon or the radiologist, come to life each with their own distinct personality and emotional profile, Dr. Groopman reminds us that the most neglected and thus most threatening source of cognitive error is the physician himself. As fallible individuals, our own past experiences and current state of mind can greatly colour and sometimes cloud our judgement. For example, faced with a “difficult” patient who is failing treatment for a chronic illness because of non-compliance to medication, many physicians will feel annoyed or perhaps even disgusted. Dr. Groopman asserts that these are quite natural reactions from a physician; it would be ludicrous to demand complete emotional detachment from physicians, who are also human beings. The danger lies not within the existence of these emotions per se, but rather with the ignoring of them as potential sources of cognitive errors. He further argues that because each physician’s particular temperament precludes him from being compatible with all types of patients, when choosing a physician, one should always keep in mind that a “good doctor” for your neighbour might not turn out to be a “good doctor” for you. This book primarily targets the general public, but it is also of tremendous value to medical practitioners of all levels, especially for those on the giving and receiving ends of medical education. For example, we are taught as beginner medical students to pose diagnoses through a step-wise, logical approach. However, shortcuts and pattern recognition easily find their way into our daily work with patients, most often subconsciously. Again, Dr. Groopman argues that the use of gestalt in clinical practice need not be frowned upon, in fact, it is often necessary in situations of time-restraint. What needs to be amended in the curriculum is the explicit acknowledgment of pattern recognition in clinical practice in order to empower novice medical students to use it consciously and with full awareness of its pitfalls. Medical students are taught many skills to avoid technical errors; it is now time for cognitive errors to share some of the spotlight as well. And this new focus does not only apply to medical students, but to the entire medical community. In How Doctors Think, numerous examples are offered of individual physicians or teams of medical care providers openly discussing cognitive errors and reflecting on changes both at their own individual and institution levels to avoid similar future occurrences. In that respect, Dr. Groopman’s book is more than a candid reflection of our mistakes, it is also a celebration of those who, through creativity, open-mindedness and dedication, have been and will be learning from these mistakes to provide better patient care.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.033
Threshold uncertainty score0.110

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.022
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0060.011
Scholarly communication0.0110.008
Open science0.0010.005
Research integrity0.0060.011
Insufficient payload (model declined to judge)0.0330.025

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.056
GPT teacher head0.318
Teacher spread0.263 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations1
Published2008
Admission routes1
Has abstractyes

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