Transition in care from paramedics to emergency department nurses: a systematic review protocol
Bibliographic record
Abstract
BACKGROUND: Effective and efficient transitions in care between emergency medical services (EMS) practitioners and emergency department (ED) nurses is vital as poor clinical transitions in care may place patients at increased risk for adverse events such as delay in treatment for time sensitive conditions (e.g., myocardial infarction) or worsening of status (e.g., sepsis). Such transitions in care are complex and prone to communication errors primarily caused by misunderstanding related to divergent professional perspectives leading to misunderstandings that are further susceptible to contextual factors and divergent professional lenses. In this systematic review, we aim to examine (1) factors that mitigate or improve transitions in care specifically from EMS practitioners to ED nurses, and (2) effectiveness of interventional strategies that lead to improvements in communication and fewer adverse events. METHODS: We will search electronic databases (DARE, MEDLINE, EMBASE, Cochrane, CINAHL, Joanna Briggs Institute EBP; Communication Abstracts); gray literature (gray literature databases, organization websites, querying experts in emergency medicine); and reference lists and conduct forward citation searches of included studies. All English-language primary studies will be eligible for inclusion if the study includes (1) EMS practitioners or ED nurses involved in transitions for arriving EMS patients; and (2) an intervention to improve transitions in care or description of factors that influence transitions in care (barriers/facilitators, perceptions, experiences, quality of information exchange). Two reviewers will independently screen titles/abstracts and full texts for inclusion and methodological quality. We will use narrative and thematic synthesis to integrate and explore relationships within the data. Should the data permit, a meta-analysis will be conducted. DISCUSSION: This systematic review will help identify factors that influence communication between EMS and ED nurses during transitions in care, and identify interventional strategies that lead to improved communication and decrease in adverse events. The findings can be used to develop an evidence-informed transitions in care tool that ensures efficient transfer of accurate patient information, continuity of care, enhances patient safety, and avoids duplication of services. This review will also identify gaps in the existing literature to inform future research efforts. TRIAL REGISTRATION: PROSPERO CRD42017068844.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.089 | 0.089 |
| Meta-epidemiology (narrow) | 0.006 | 0.008 |
| Meta-epidemiology (broad) | 0.024 | 0.016 |
| Bibliometrics | 0.020 | 0.018 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.008 | 0.006 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.074 | 0.010 |
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".