Critical Care Organizations: Building and Integrating Academic Programs
Bibliographic record
Abstract
OBJECTIVE: Academic medical centers in North America are expanding their missions from the traditional triad of patient care, research, and education to include the broader issue of healthcare delivery improvement. In recent years, integrated Critical Care Organizations have developed within academic centers to better meet the challenges of this broadening mission. The goal of this article was to provide interested administrators and intensivists with the proper resources, lines of communication, and organizational approach to accomplish integration and Critical Care Organization formation effectively. DESIGN: The Academic Critical Care Organization Building section workgroup of the taskforce established regular monthly conference calls to reach consensus on the development of a toolkit utilizing methods proven to advance the development of their own academic Critical Care Organizations. Relevant medical literature was reviewed by literature search. Materials from federal agencies and other national organizations were accessed through the Internet. SETTING: The Society of Critical Care Medicine convened a taskforce entitled "Academic Leaders in Critical Care Medicine" on February 22, 2016 at the 45th Critical Care Congress using the expertise of successful leaders of advanced governance Critical Care Organizations in North America to develop a toolkit for advancing Critical Care Organizations. MEASUREMENTS AND MAIN RESULTS: Key elements of an academic Critical Care Organization are outlined. The vital missions of multidisciplinary patient care, safety, and quality are linked to the research, education, and professional development missions that enhance the value of such organizations. Core features, benefits, barriers, and recommendations for integration of academic programs within Critical Care Organizations are described. Selected readings and resources to successfully implement the recommendations are provided. Communication with medical school and hospital leadership is discussed. CONCLUSIONS: We present the rationale for critical care programs to transition to integrated Critical Care Organizations within academic medical centers and provide recommendations and resources to facilitate this transition and foster Critical Care Organization effectiveness and future success.
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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 | 0.035 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.010 | 0.014 |
| Open science | 0.004 | 0.018 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".