Ebola preparedness: a rapid needs assessment of critical care in a tertiary hospital
Bibliographic record
Abstract
BACKGROUND: The current outbreak of Ebola has been declared a public health emergency of international concern. We performed a rigorous and rapid needs assessment to identify the desired results, the gaps in current practice, and the barriers and facilitators to the development of solutions in the provision of critical care to patients with suspected or confirmed Ebola. METHODS: We conducted a qualitative study with an emergent design at a tertiary hospital in Ontario, Canada, recently designated as an Ebola centre, from Oct. 21 to Nov. 7, 2014. Participants included physicians, nurses, respiratory therapists, and staff from infection control, housekeeping, waste management, administration, facilities, and occupational health and safety. Data collection included document analysis, focus groups, interviews and walk-throughs of critical care areas with key stakeholders. RESULTS: Fifteen themes and 73 desired results were identified, of which 55 had gaps. During the study period, solutions were implemented to fully address 8 gaps and partially address 18 gaps. Themes identified included the following: screening; response team activation; personal protective equipment; postexposure to virus; patient placement, room setup, logging and signage; intrahospital patient movement; interhospital patient movement; critical care management; Ebola-specific diagnosis and treatment; critical care staffing; visitation and contacts; waste management, environmental cleaning and management of linens; postmortem; conflict resolution; and communication. INTERPRETATION: This investigation identified widespread gaps across numerous themes; as such, we have been able to develop a set of credible and measureable results. All hospitals need to be prepared for contact with a patient with Ebola, and the preparedness plan will need to vary based on local context, resources and site designation.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".