Improving emergency care through a dedicated redesigned obstetrics and gynecology emergency unit at the Women's Hospital, Doha, Qatar
Bibliographic record
Abstract
BACKGROUND: Emergencies in obstetrics and gynecology are important causes of morbidity and mortality. Consequently, the World Health Organization introduced the concept of emergency obstetrical and newborn care aimed at reducing maternal mortality by 75%. Worldwide, 15% of all births result in life-threatening complications during pregnancy. The Women's Hospital in Doha, Qatar, experienced a steady increase in births from approximately 13,000 in 2013 to more than 17,000 in 2016. This was accompanied by a rapid increase in the number of visits to the emergency unit-the main provider of emergency obstetrics and gynecology care to approximately 70,000 patients a year-overstretching the services and affecting the quality of care. To address this rapid increase, a redesign of the emergency services was undertaken and implemented in 2012. OBJECTIVE: This study aimed to present a 5-year audit of the emergency department's structural process redesign. STUDY DESIGN: We redesigned the emergency department into one of consultant-led teams of trained obstetrics and gynecology physicians, residents, and specialized nurses with immediate support from ancillary services and direct access to operating and labor rooms and wards. The Canadian Triage and Acuity Scale (levels I-V) was used to triage patients and determine the rapidity with which they were seen. An electronic medical record was introduced as part of the redesign, and different matrices were used to measure outcomes regularly. RESULTS: During the 5-year study period, an average of 70,000 patients were seen annually. The obstetrics-to-gynecology ratio of cases was 3:1. Using the Canadian Triage and Acuity Scale, most patients (63.4%) had acuity level IV. Moreover, 97% of women were seen and triaged scored within 15 minutes of presentation; furthermore, all patients with acuity level I and 95% of patients with acuity level II were seen within 15 minutes by a physician, and 89% of patients with acuity level III were seen within 60 minutes. Approximately 2.5% of patients returned to the emergency department within 48 hours of discharge, and 0.5% of patients who had been seen and discharged returned to the emergency department. Key performance indicators were exceeded in all domains, with 90% of patients rating the care they received as either excellent or good. CONCLUSION: The growing population in Qatar required improvements and innovation in services. Our results showed that innovating how emergency services can be provided results in considerable improvements in outcomes and satisfaction. Considering the peculiarities of the environments, it should be possible to adopt this approach in other settings.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".