Barriers and enablers that influence guideline-based care of geriatric fall patients presenting to the emergency department
Bibliographic record
Abstract
BACKGROUND: Geriatric patients commonly present to the ED after a fall. Recent evidence suggests that ED physicians are poorly adherent to published ED-specific geriatric fall guidelines. This study applied a theoretical domains framework (TDF) approach to systematically investigate barriers and enablers in the provision of guideline-based care to ED geriatric fall patients. METHODS: From June to September 2017, semistructured interviews of staff ED physicians practising in Ontario, Canada, were conducted and analysed. An interview guide based on the TDF was used to capture 14 domains influencing provision of guideline-based care. Relevant domains were identified based on frequencies of beliefs, existence of conflicting beliefs and evidence of strong beliefs that would influence provision of guideline-based care. RESULTS: ). Prominent themes included lack of knowledge, paucity of evidence, heterogeneous self-perceived skills, perceived increased time and workload, importance of allied health support, inconsistently available allied health workers, lack of positive reinforcement, emotions negatively impacting these clinical encounters and support for memory aids. Overall, ED physicians were supportive of guideline implementation, and believe it will lead to better outcomes for geriatric fall patients. CONCLUSION: This study identified important barriers and enablers to provision of guideline-based care in geriatric ED fall patients. Based on these findings, future implementation of guidelines nationally and internationally should focus on improving knowledge and training on guidelines, improving positive reinforcement for guideline-appropriate management, greater allied health support and further research to support guidelines.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".