The Medical Profession’s Future: A Struggle Between Caring For Patients And Bottom-Line Pressures
Bibliographic record
Abstract
In this issue of Health Affairs, Lawrence Casalino and coauthors establish that physicians in common specialty practices spend an average of 2.6 hours per week dealing with external quality measures. This gives rise to general questions about the future of the medical profession. To what extent will quality-tracking requirements and similar practice intrusions reshape who physicians are, how many physicians there are, and how they practice? In turn, how will these changes affect patients' access to care? Data derived from the 2014 Survey of America's Physicians: Practice Patterns and Perspectives, conducted by Merritt Hawkins on behalf of the Physicians Foundation, make it clear that physician practice patterns are evolving. Responding to an increasingly intrusive practice environment, physicians report that they will choose a variety of practice models likely to reduce patients' access to care or that they will retire early, which will exacerbate the physician shortage and fundamentally change the nature of the medical profession.
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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 | 0.012 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.014 |
| Scholarly communication | 0.020 | 0.016 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.019 | 0.034 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".