Drivers of Emergency Department Use Among Oncology Patients in the Era of Novel Cancer Therapeutics: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: Patients diagnosed with cancer are frequent users of the emergency department (ED). While many visits are unavoidable, a significant portion may be potentially preventable ED visits (PPEDs). Cancer treatments have greatly advanced, whereby patients may present with unique toxicities from targeted therapies and are often living longer with advanced disease. Prior work focused on patients undergoing cytotoxic chemotherapy, and often excluded those on supportive care alone. Other contributors to ED visits in oncology, such as patient-level variables, are less well-established. Finally, prior studies focused on ED diagnoses to describe trends and did not evaluate PPEDs. An updated systematic review was completed to focus on PPEDs, novel cancer therapies, and patient-level variables, including those on supportive care alone. METHODS: Three online databases were used. Included publications were in English, from 2012-2022, with sample sizes of ≥50, and reported predictors of ED presentation or ED diagnoses in oncology. RESULTS: 45 studies were included. Six studies highlighted PPEDs with variable definitions. Common reasons for ED visits included pain (66%) or chemotherapy toxicities (69.1%). PPEDs were most frequent amongst breast cancer patients (13.4%) or patients receiving cytotoxic chemotherapy (20%). Three manuscripts included immunotherapy agents, and only one focused on end-of-life patients. CONCLUSION: This updated systematic review highlights variability in oncology ED visits during the last decade. There is limited work on the concept of PPEDs, patient-level variables and patients on supportive care alone. Overall, pain and chemotherapy toxicities remain key drivers of ED visits in cancer patients. Further work is needed in this realm.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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".