Cost-consciousness among Iranian internal medicine residents
Bibliographic record
Abstract
Background: Study aimed at assessing residents' cost awareness and their attitude about health care costs.Methods: Internal medicine residents at teaching hospitals of Tehran University of Medical Sciences were surveyed during August–December 2016 using a researcher-made questionnaire comprising attitude statements and cost estimation of diagnostic and treatment items.Results: Eighty-nine residents completed the survey (response rate = 56.6%). The results indicate that less than one quarter (23.69%) of cost estimates were in the range of correct answers. The mean (SD) for correct estimation of medications (out of 8 scores), lab tests (out of 20 scores), and total (out of 35 scores) were 1.25 (0.96), 4.92 (0.27), and 7.97 (0.34), respectively. An analysis of variance showed that the level of residency was positively correlated with residents’ correct cost estimation (F (3, 77)=9.98, p = 0.029). There was a significant positive correlation between age of residents with the correct estimate of medication prices (p = 0.018, r = 0.261).Conclusions: The internal medicine residents of Tehran University of Medical Sciences have poor knowledge of health care costs, including medications, diagnostic tests, and hospitalization costs. The results of this study explain the necessity of developing a training program for the transfer of cost information to physicians.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".