ArticleOman medical journal2020
'See and Treat' Clinic Service Evaluation at a Tertiary Care Hospital in Abu Dhabi.
Article in Oman medical journal, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Enlightening Hidden Nursing Care in Nurse-Led Clinics and See & Treat: An Observational Multicenter Protocol Study in Italy.Nursing reports (Pavia, Italy) · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesWe sought to evaluate the performance provided at a 'See and Treat' (ST) clinic at a tertiary hospital emergency department (ED) in Abu Dhabi, UAE, and to assess its impact on ED crowding.
methodsWe conducted a retrospective electronic medical chart review and database analyses. We included patients triaged as triage level 4 (T4) and triage level 5 (T5) as per the Emergency Severity Index treated at ED in the ST clinic and other ED areas, including the off-site Urgent Care Centre (UCC) between 1 June 2016 and 30 June 2017. We analyzed a group of process and outcome measures at our ST clinic and compared them to the same measures in other areas of our ED and the co-located UCC. The process measure analyzed was the door-to-doctor time. In addition, the outcome measures analyzed were the door-to-door time, unplanned return within 72 hours, and feedback from T4 and T5 triaged patients treated at the clinic.
resultsThe number of patients enrolled in the study was 43 109. Of these, 11 329 (26.3%) patients were treated at the ST clinic, 6328 (14.7%) were treated at the UCC, and 25 452 (59.0%) were treated at the main ED. The door-to-doctor time was within 30 minutes for 89.0% of ST clinic patients, and 94.0% of patients experienced a door-to-door time of within two hours; 2.1% of these patients returned within 72 hours. Among these, 78.7% returned for an issue related to their first visit. However, none of the patients were admitted on their return visit. For patients presenting to UCC and other parts of our ED, we recorded a door-to-doctor time of within 30 minutes for 80.5% of patients and a door-to-door time of within two hours for 73.0% of patients. We found the difference in waiting times (i.e., door-to-doctor times between ST clinic patients and the rest of ED) to be statistically significant (
conclusionsDoor-to-doctor times were shorter in ST clinics compared to other parts of our ED, but there was no statistically significant difference in door-to-door times when comparing ST clinics to the rest of the ED. ST clinic patients had a lower rate of unplanned return within 72 hours, of which, none required admission on the return attendance. We believe ST clinics have a positive impact on reducing ED crowding but acknowledge they are one of the many plausible solutions attributing to optimized patient flow in the ED.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.