Unplanned emergency department visits after mastectomy in Alberta: Informing a quality improvement initiative.
Bibliographic record
Abstract
412 Background: Same day surgery (SDS) for mastectomy increased in Alberta from 1.7% to 73% in 2022, after implementation of a perioperative care pathway in 2016. However, unplanned visits to the emergency department (ED) remained high at 22-27% with <5% requiring readmission. Our study aims to explore factors associated with unplanned ED visits by 1) describing patients with unplanned ED visits within 30 days of mastectomy, and 2) exploring characteristics for unplanned ED visits from the patient perspective. Methods: A survey study was conducted of patients who underwent a mastectomy in Alberta between 07/01/2021 to 06/30/2022 by a general surgeon, and had an unplanned ED visit within 30 days. Patients were identified from the CIHI database; chart review was performed to confirm ED visit details. Patients were excluded if their presentation was unrelated to surgery. Survey questions evaluated 3 domains: medical, socioeconomic, and psychologic, as well as patient-reported experiences of post-operative care. Results: Of 549 patients who underwent mastectomy during the study period, 132 (24%) presented to ED within 30 days. The survey was sent to 87 patients meeting inclusion criteria; 38% responded. Average age was 56. Most patients had no comorbidities (30%) or 2+ (27%), and 85% had prior surgery. The majority (79%) had college education or higher. Treatment included neoadjuvant chemotherapy (24%), sentinel lymph node biopsy (39%), axillary dissection (12%), concurrent reconstruction (24%), and mastectomy alone (27%). Most patients had 2+ drains (70%). Many patients (38%) presented on a weekend, 50% stating the ED was the only choice available at the time. Comparatively, 22% reported being told to go, and 16% felt the ED was the best place for their problem. Patients were seen by an ED physician (89%), nurse (40%) and/or surgeon (28%). Most common reasons for ED visit were infection (38%) and drain concerns (38%). Re-operation and readmission rates were 25% and 19%, respectively. Overall, 84% felt prepared for surgery; only 15% felt uncomfortable with drain management. Patients identified peer support and wound information as areas lacking. While 78% of patients were mostly or very satisfied with surgery, difficulty accessing their surgical team post-operatively was reported as the main flaw. Conclusions: Our study cohort identified infection and drain concerns as the most common reason for unplanned ED visit after mastectomy. Overall, patients were satisfied with education and surgical care, but identified problems with accessing medical/surgical care after discharge. Future initiatives should focus on improved access to outpatient care, and education on post-mastectomy emergencies.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".