The challenges of measuring quality-of-care indicators in rural emergency departments: a cross-sectional descriptive study
Bibliographic record
Abstract
BACKGROUND: Evidence-based indicators of quality of care have been developed to improve care and performance in Canadian emergency departments. The feasibility of measuring these indicators has been assessed mainly in urban and academic emergency departments. We sought to assess the feasibility of measuring quality-of-care indicators in rural emergency departments in Quebec. METHODS: We previously identified rural emergency departments in Quebec that offered medical coverage with hospital beds 24 hours a day, 7 days a week and were located in rural areas or small towns as defined by Statistics Canada. A standardized protocol was sent to each emergency department to collect data on 27 validated quality-of-care indicators in 8 categories: duration of stay, patient safety, pain management, pediatrics, cardiology, respiratory care, stroke and sepsis/infection. Data were collected by local professional medical archivists between June and December 2013. RESULTS: Fifteen (58%) of the 26 emergency departments invited to participate completed data collection. The ability to measure the 27 quality-of-care indicators with the use of databases varied across departments. Centres 2, 5, 6 and 13 used databases for at least 21 of the indicators (78%-92%), whereas centres 3, 8, 9, 11, 12 and 15 used databases for 5 (18%) or fewer of the indicators. On average, the centres were able to measure only 41% of the indicators using heterogeneous databases and manual extraction. The 15 centres collected data from 15 different databases or combinations of databases. The average data collection time for each quality-of-care indicator varied from 5 to 88.5 minutes. The median data collection time was 15 minutes or less for most indicators. INTERPRETATION: Quality-of-care indicators were not easily captured with the use of existing databases in rural emergency departments in Quebec. Further work is warranted to improve standardized measurement of these indicators in rural emergency departments in the province and to generalize the information gathered in this study to other health care environments.
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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 | 0.013 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".