Decision Making in an Academic Department of Medicine: The Role of a Management Control System
Bibliographic record
Abstract
Academic Departments of Medicine have several challenges in managing resources, meeting academic goals and clinical demands. In this paper, we describe a management control system installed in 2014: the Strategic Plan, a Balanced Scorecard reflecting clinical research and educational performance, Annual feedback and review by Departmental and Divisional Chairs, and Improvement Plans.
 This system over 8 years resulted in a reduction in 30-day re-admissions of 14%, a decline in length of stay of 0.55 days, and reduced absolute in-hospital mortality of nearly 2%. Clinical revenue increased 42% from 2016 to 2022 largely due to increased ambulatory and procedural volumes. Teaching time and ratings were unaffected by the installation of this system. Return on investment for newly hired researchers and scientists was 67.5% with a 12.7% increase in peer-reviewed funding. We conclude that the Decision Management Control System was feasible to create and allowed capable monitoring of performance and informed decision-making. Major metrics improved after its implementation.
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 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 | 0.008 | 0.003 |
| 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 | 0.000 |
| 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 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".