Hacking teamwork in health care: Addressing adverse effects of ad hoc team composition in critical care medicine
Bibliographic record
Abstract
BACKGROUND: The continued need for improved teamwork in all areas of health care is widely recognized. The present article reports on the application of a hackathon to the teamwork problems specifically associated with ad hoc team formation in rapid response teams. PURPOSES: Hackathons-problem-solving events pioneered in computer science-are on the rise in health care management. The focus of these events tends to be on medical technologies, however, with calls for improvements in management practices as general recommendations. The hackathon reported here contributes to health care management practice by addressing improvements in teamwork as the focal problem. METHODOLOGY: The hackathon event took place over 2.5 days in conjunction with an academic conference focused on group research. Three teams comprised of practicing healthcare professionals, academic researchers and students developed solutions to problems of ad hoc team formation in rapid response teams. FINDINGS: The event fulfilled several goals. The teams produced three distinct, yet complementary solutions that were backed by both field-based experience and solid research evidence. The event provided the opportunity for two-way translation of research and practice through direct collaboration among key stakeholders. The hackathon produced long term effects through establishing or strengthening collaborations, dissemination of the ideas through presentations, workshops, and publications, and changes in participantsâ work practices. PRACTICE IMPLICATION: The event demonstrated that hackathons, classically focused on technology, can also offer a spur to innovation around organizational processes. The article provides advice for organizing other hackathons focused on similar topics. The solutions offered by the participants in the event yields the clear insight that multipronged solutions for emergency-oriented teamwork are needed. The hackathon highlighted the scaled of collaboration and effort needed to tackle the many complexities in health care that impact outcomes for providers, patients, and health organizations.
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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 | 0.029 | 0.118 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".