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Record W3157533115 · doi:10.1093/ajcp/aqab014

Addressing the Diagnostic Miscommunication in Pathology

2021· review· en· W3157533115 on OpenAlexafffund
Lorna Mirham, Jessica Hanna, George M. Yousef

Bibliographic record

VenueAmerican Journal of Clinical Pathology · 2021
Typereview
Languageen
FieldMedicine
TopicClinical Laboratory Practices and Quality Control
Canadian institutionsHospital for Sick ChildrenNorth York General HospitalMcMaster UniversityUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsJargonCLARITYGrading (engineering)MedicinePathologyAnatomical pathologyPsychological interventionSurgical pathologyMEDLINEConsistency (knowledge bases)Intensive care medicineMedical physicsComputer scienceNursingArtificial intelligence

Abstract

fetched live from OpenAlex

OBJECTIVES: The pathology report serves as a crucial communication tool among a number of stakeholders. It can sometimes be challenging to understand. A communication barrier exists among pathologists, other clinicians, and patients when interpreting the pathology report, leaving both clinicians and patients less empowered when making treatment decisions. Miscommunication can lead to delays in treatment or other costly medical interventions. METHODS: In this review, we highlight miscommunication in pathology reporting and provide potential solutions to improve communication. RESULTS: Up to one-third of clinicians do not always understand pathology reports. Several causes of report misinterpretation include the use of pathology-specific jargon, different versions of staging or grading systems, and expressions indicative of uncertainty in the pathologist's report. Active communication has proven to be crucial between the clinician and the pathologist to clarify different aspects of the pathology report. Direct communication between pathologists and patients is evolving, with promising success in proof-of-principle studies. Special attention needs to be paid to avoiding inaccuracy while trying to simplify the pathology report. CONCLUSIONS: There is a need for active and adequate communication among pathologists, other clinicians, and patients. Clarity and consistency in reporting, quantifying the level of confidence in diagnosis, and avoiding misnomers are key steps toward improving communications.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.083
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.992
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.083
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0070.002
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.005
Insufficient payload (model declined to judge)0.0000.000

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 head0.478
GPT teacher head0.599
Teacher spread0.121 · 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 teacher head, not a consensus.

Study designOther design
Domainnot available
GenreReview

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".

Quick stats

Citations19
Published2021
Admission routes2
Has abstractyes

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