Hybrid management, organizational configuration, and medical professionalism: evidence from the establishment of a clinical directorate in Portugal
Bibliographic record
Abstract
BACKGROUND: The need of improving the governance of healthcare services has brought health professionals into management positions. However, both the processes and outcomes of this policy change highlight differences among the European countries. This article provides in-depth evidence that neither quantitative data nor cross-country comparisons have been able to provide regarding the influence of hybrids in the functioning of hospital organizations and impact on clinicians' autonomy and exposure to hybridization. METHODS: The study was designed to witness the process of institutional change from the inside and while that process was underway. It reports a case study carried out in a public hospital in Portugal when the establishment of a clinical directorate was being negotiated. Data collection comprises semi-structured interviews with general managers and surgeons complemented with observations. RESULTS: The clinical directorate under study illustrates a divisionalized professional bureaucracy model that combines features of professional bureaucracies and divisionalized forms. The hybrid manager is key to understand the extent to which practising clinicians are more accountable and to whom given that managerial tools of control have not been strengthened, and trust-based relations allow them to keep professional autonomy untouched. In sum, clinicians are allowed to profit from their activity and to perform autonomously from the hospital's board of directors. The advantageous conditions enjoyed by the clinical directorate intensify internal re-stratification in medicine, thus suggesting forms of divisionalized medical professionalism grounded in organizational dynamics. CONCLUSION: It is discussed the extent to which policy change to the governance of health organizations regarding the relationship between medicine and management is subject to specific constraints at the workplace level, thus conditioning the expected outcomes of policy setting. The study also highlights the role of hybrid managers in determining the extent to which practising professionals are more accountable to managerial criteria. The overall conclusion is that although medical and managerial values link to each other, clinicians reconfigure managerial criteria according to specific interests. Ultimately, medical autonomy and authority may be reinforced in organizational settings subject to NPM-driven reforms.
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How this classification was reachedexpand
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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".