Emergency Department Use in Patients with Cancer: A Population-Based Study
Bibliographic record
Abstract
IntroductionEmergency Department (ED) visits in cancer patients represent a significant burden to both patients and the health care system. Emergency Care of cancer patients is complex compared to the population. There is lack of knowledge regarding the pattern and reasons for ED visits in this population.
 Objectives and ApproachWe sought to identify factors and patterns associated with ED use among cancer patients, in the first year after diagnosis. Adult cancer patients diagnosed between 2011 and 2013 were identified from the Alberta Cancer Registry. This was linked with cancer related treatments extracted from medical records system at provincial cancer centers. ED visits and outpatient clinics were acquired from National Ambulatory Care Reporting System (NACRS). Databases were linked by unique patient identification number. Previous cancer patients were defined by having at least one cancer related diagnosis in NACRS before. The other patients were treated as non-cancer patients.
 ResultsCancer patients accounted for 6.7% of ED visits and 10\% of ED hours. They had higher male percentage (53% vs. 49%), higher admission rate (23% vs. 10%), ambulance usage (20% vs. 12%) and longer stay (LOS) (171 vs. 131 mins) compared to non-cancer patients. 24% of cancer patients had 4 or more ED visits/year and accounted for 59% of visits. Lung and liver cancer patients had higher ED utilization than patients with other cancers. Breast cancer patients had more after-treatment-ED-visits (41% within a week vs. 26% in lung cancer). Use of ED was highest within 1 month of diagnosis for all types except breast cancer, which was highest at 2 months after. Differences were observed between urban and rural area for numbers reported above.
 Conclusion/ImplicationsThese data suggest high ED utilization by cancer patients, and variation in utilization by cancer type. Identifying the timing and risk factors of ED visit for each cancer type, especially on frequent ED users presents opportunities to improve care in oncology clinics and ED.
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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 | 0.002 |
| 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".