Guide to strategic planning in critical care medicine
Bibliographic record
Abstract
Strategic planning is increasing in value. More organizations are implementing such strategies to help achieve their corporate goals. Strategic planning can help improve morale and satisfaction amongst staff, managers and stakeholders. It can help improve efficiency within the organization and ideally the quality of care as well. Most importantly, it helps an organization to focus and prioritize its goals therefore increasing its chances for success. Critical care medicine is a unique branch of medicine because of the high costs associated with care. It is reasonable to perceive that these costs will go up in the future. Our population is aging and our abilities to sustain life are constantly improving. ICU is also unique because it is associated with high stress for the patients, families, nurses, physicians and allied health professionals. Care is often associated with post-traumatic stress and burnout. For these reasons strategic planning is essential for critical care to thrive, provide good care for patients and to allow for efficient use of resources. There are several approaches to strategic planning. This article will look at the 10-step method described in Bryson’s Strategic Planning for Public and Non-Profit Organizations and how it can apply to critical care medicine.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.060 | 0.050 |
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".