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Record W2093446275 · doi:10.1001/jama.2011.1021

Facts, Facts, Facts: What Is a Physician to Do?

2011· article· en· W2093446275 on OpenAlexaboutno aff
Robert H. Brook

Bibliographic record

VenueJAMA · 2011
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineFamily medicineIntensive care medicine

Abstract

fetched live from OpenAlex

IT IS A CLICHE TO OBSERVE THAT EVERYONE LIVES IN A GLOBAL economy. Anyone who travels internationally can see how rapidly the world is becoming similar in terms of shops, goods, and services. Perhaps it is timely to reengage physicians in thediscussion of international comparativedata about health care and to ask why the United States is so provincial in designing the systems by which care is delivered. Recently the Organisation for Economic Co-operation and Development (OECD) published Health at a Glance 2009, the annual compilation of health statistics from 30 countries. Even though most of the data are from 2007, these statistics provide revealing snapshots of various aspects of health and health systems, especially when comparing several US statistics to comparable statistics from other countries. Seventeen comparisons were selected to be representative of the different concepts (health status, nonmedical determinants of health, health work force, health care activities, quality of care, and health expenditures) that are covered in the OECD report. The comparisons (reported as United States; another country) are as follows. 1. Life expectancy in the United States is 78.1 years; in Switzerland, it is 81.9 years. 2. Years of life lost before age 70 per 100 000 men is 6291; in Italy, it is 3605. 3. The age-standardized ischemic heart mortality rate per 100 000 males is 145; in France, it is 54. 4. The percentage of newborns weighing less than 2500 g is 8.3%; in Ireland, it is 5%. 5. The percentage of children aged 11 to 15 years who are overweight or obese is 29.8%; in Belgium, it is 10.5%. 6. The number of practicing physicians per 1000 population is 2.4; in Belgium, it is 4.0. 7. The percentage of US physicians who are non-US trained is 25.9%; in the Netherlands, the percentage of non-Netherlands−trained physicians is 6.3%. 8. The ratio of the self-employed specialist’s average salary to the average salary of a full-time employee is 5.6:1; in Germany, the ratio is 4.1:1. For a selfemployed general practitioner, the comparable ratio is 3.7:1; in Canada, it is 3.1:1. 9. The number of physician consultations per capita is 3.8; in Germany, it is 7.5, and in Japan, it is 13.6. 10. The number of consultations per physician per year (data are from administrative sources and include visits in physician offices, hospital outpatient clinics, or patient homes) is 1570; in Korea, it is 7251 and in Canada, it is 3335 (fee-for-service visits only). 11. The number of magnetic resonance imaging (MRI) machines per 1 000 000 of population is 25.9; in Japan, it is 40.1; in Canada, it is 6.7. 12. The number of MRI examinations per 1000 population is 91.2; in Canada, the number is 31.2. 13. The hospital discharge rate is 126 per 1000; in France, it is 274. 14. The coronary revascularization rate is 521 per 100 000; in Switzerland, it is 144 and in Ireland, it is 128. 15. The number of patients treated for end-stage renal failureis169per100 000population; intheNetherlands, it is 77. 16. The age-sex standardized in-hospital death rate for acute myocardial infarction is 5.1%; in Sweden, it is 2.9%. 17. Health expenditures are 16.0% of gross domestic product; in France, 11% and in Ireland, 7.6%.

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)0.014
metaresearch head score (Gemma)0.070
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 score0.027
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.070
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0070.013
Scholarly communication0.0090.025
Open science0.0020.005
Research integrity0.0100.015
Insufficient payload (model declined to judge)0.0270.012

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 head0.079
GPT teacher head0.272
Teacher spread0.193 · 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".

Quick stats

Citations2
Published2011
Admission routes1
Has abstractyes

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