Discharges Against Medical Advice in Pregnant Patients at a Canadian Tertiary Care Center: Does Lack of Access to Childcare Play a Role? [ID 2683591]
Bibliographic record
Abstract
INTRODUCTION: Discharges against medical advice (AMA) during pregnancy have been associated with poor maternal and fetal outcomes. Moreover, one of the documented reasons why female patients might leave the hospital AMA is lack of access to childcare. In recent years, lack of access to childcare has been identified as a potential risk factor for discharge AMA and maternal mortality at a tertiary care center in Edmonton, Alberta, Canada. The goal of this chart review project is to study the characteristics of pregnant women who leave AMA from this center, and to determine what proportion of these discharges is due to difficulties securing childcare. METHODS: Ethics approval was obtained through the University of Alberta’s Health Research Ethics Board. All patients who were discharged AMA from the triage and antepartum units at the study site between May 28, 2021, and May 27, 2022, were identified. Patients were included in the chart review as long as they remained undelivered at the time of discharge. Reasons for admission and discharge AMA were extracted from each patient’s chart whenever available. Patients' age, gravidity, parity, and gestational age at the time of discharge were also collected. RESULTS: During the study period, approximately 9.3% of recorded discharges from the triage and antepartum units were for patients who left AMA. In total, we included 89 individual patient visits that ended with a discharge AMA. For these patients, the most frequent reason for admission was threatened preterm labor (including short cervix). Although the reason motivating discharges AMA was not documented in the majority of charts reviewed (49/89), lack of access to childcare was the most frequently documented reason provided by patients for leaving AMA (15/40). CONCLUSION: Improving access to childcare for pregnant patients who are admitted to the study site might help to decrease discharges AMA, and therefore help reduce perinatal complications.
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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 | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.009 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".