Implementation of a critical care outreach service: a qualitative study
Bibliographic record
Abstract
AIM: The aim of this study was to explore hospital staff perceptions of the perceived challenges and outcomes of implementing a critical care outreach service. BACKGROUND: A nurse-led critical care outreach service was designed and implemented to identify and treat acutely ill patients in a large tertiary care hospital in Iran. METHODS: A qualitative analysis of data from two focus groups and seven interviews was carried out using conventional content analyses techniques. A total of 24 hospital staff members participated, including critical care outreach team members, physicians, ward head nurses and ward staff. FINDINGS: Two main categories described the perceived challenges to the implementation of the critical care outreach service: 1) the hospital context, with four subcategories related to staff shortages, the instability of physician positions, the lack of specialized essential services and the absence of a system to establish do-not-resuscitate orders, and 2) staff resistance to different nursing priorities, routines and extra work. In two additional main categories, participants also described positive and negative perceived outcomes. The positive perceived outcomes included three subcategories of alleviating equipment shortages, improving nursing knowledge and patient care and improving patient and healthcare professional satisfaction. DISCUSSION: While critical care outreach has the potential to improve patient perceived outcomes and both patient and provider satisfaction with care, the contextual and clinical realities in hospitals are significant and must be examined during the planning and implementation of future outreach. CONCLUSION AND IMPLICATIONS FOR NURSING AND HEALTH POLICY: A critical care outreach service in the context of an Iranian hospital has the potential to improve ward nurse familiarity with the care of acutely ill patients and the quality of palliative care. However, attention ought to be paid to the hospital's structural and contextual factors. Alleviating nursing shortages, reducing staff resistance and preparing goals of care guidelines that address restrictions on resuscitation could facilitate implementation of critical care outreach services.
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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 | 0.011 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".