Physician versus non-physician CEOs: The effect of a leader’s professional background on the quality of hospital management and health care
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Since 1935, the number of hospitals managed by chief executive officers (CEOs) who are also physicians has decreased by 90%. Today, only 5% of hospitals in the United States are run by CEOs with a medical degree. However, higher ranked hospitals are more commonly run by CEOs with physician backgrounds. Additionally, overall quality scores in physician-run hospitals were 25% higher than those run by non-physicians. It is not clear whether this association between physician management and a higher quality of hospital management and health care results from the CEO’s professional (medical) background. Considering this, the following editorial discusses what characteristics of physicians and non-physicians may influence their capacity to lead a hospital and how that may impact the quality of management and health care within a hospital. Ultimately, this article aims to further the debate over physician versus. non-physician leadership, building a foundation for further research that may determine the characteristics of a CEO that are essential to guiding positive change in their hospital, refocusing health care back to its original intention: patient care.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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) | 0.000 | 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 it