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Record W1965288707 · doi:10.1377/hlthaff.20.3.233

Physicians’ Views On Quality Of Care: A Five-Country Comparison

2001· article· en· W1965288707 on OpenAlexaboutno aff
Robert J. Blendon, Cathy Schoen, Karen Donelan, Robin Osborn, Catherine M. DesRoches, Kimberly Scoles, K.M. Davis, Katherine Binns, Kinga Zapert

Bibliographic record

VenueHealth Affairs · 2001
Typearticle
Languageen
FieldHealth Professions
TopicMedical Malpractice and Liability Issues
Canadian institutionsnot available
Fundersnot available
KeywordsEconomic shortageMedical prescriptionMedicineFamily medicineQuality (philosophy)Health careMedical carePerspective (graphical)Medical emergencyNursingPolitical scienceGovernment (linguistics)

Abstract

fetched live from OpenAlex

Interest is resurging in the problems relating to the quality of patient care. This paper provides a comparative perspective on this issue from a five-country physician survey conducted in Australia, Canada, New Zealand, the United Kingdom, and the United States in 2000. Physicians in all five countries reported a recent decline in quality of care and concerns with how hospitals address medical errors. Physicians in four countries expressed serious concerns about shortages of medical specialists and inadequate facilities. U.S. physicians reported problems caused by patients' inability to pay for prescription drugs and medical care. Asked about efforts to improve quality of care in the future, physicians indicated support for electronic medical records, electronic prescribing, and initiatives to reduce medical errors.

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)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.003
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.144
GPT teacher head0.516
Teacher spread0.372 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations118
Published2001
Admission routes1
Has abstractyes

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