Evidence map›Paper›PMID 25872940›Full record

ArticleBMJ open2015

Use of the SONET score to evaluate Urgent Care Center overcrowding: a prospective pilot study.

Hao Wang, Richard D Robinson, Chad D Cowden, Violet A Gorman, Christopher D Cook, Eugene K Gicheru, Chet D Schrader, Rani D Jayswal, Nestor R Zenarosa

Abstract readEvaluation Study
PubMed Full text at PMC Publisher
In one paragraph

Article in BMJ open, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Outcomes of Crowding in Emergency Departments; a Systematic Review.Archives of academic emergency medicine · 2019
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Hao WangDepartment of Emergency Medicine, Integrative Emergency Services Physician Group, John Peter Smith Health Network, Fort Worth, Texas, USA.
Richard D RobinsonDepartment of Emergency Medicine and Urgent Care Center, Integrative Emergency Services Physician Group, John Peter Smith Health Network, Fort Worth, Texas, USA.
Chad D CowdenDepartment of Emergency Medicine and Urgent Care Center, Integrative Emergency Services Physician Group, John Peter Smith Health Network, Fort Worth, Texas, USA.
Violet A GormanDepartment of Emergency Medicine and Urgent Care Center, Integrative Emergency Services Physician Group, John Peter Smith Health Network, Fort Worth, Texas, USA.
Christopher D CookDepartment of Emergency Medicine and Urgent Care Center, Integrative Emergency Services Physician Group, John Peter Smith Health Network, Fort Worth, Texas, USA.
Eugene K GicheruDepartment of Emergency Medicine and Urgent Care Center, Integrative Emergency Services Physician Group, John Peter Smith Health Network, Fort Worth, Texas, USA.
Chet D SchraderDepartment of Emergency Medicine and Urgent Care Center, Integrative Emergency Services Physician Group, John Peter Smith Health Network, Fort Worth, Texas, USA.
Rani D JayswalDepartment of Emergency Medicine and Urgent Care Center, Integrative Emergency Services Physician Group, John Peter Smith Health Network, Fort Worth, Texas, USA.
Nestor R ZenarosaDepartment of Emergency Medicine and Urgent Care Center, Integrative Emergency Services Physician Group, John Peter Smith Health Network, Fort Worth, Texas, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo derive a tool to determine Urgent Care Center (UCC) crowding and investigate the association between different levels of UCC overcrowding and negative patient care outcomes.

designProspective pilot study.

settingSingle centre study in the USA.

participants3565 patients who registered at UCC during the 21-day study period were included. Patients who had no overcrowding statuses estimated due to incomplete collection of operational variables at the time of registration were excluded in this study. 3139 patients were enrolled in the final data analysis. PRIMARY AND SECONDARY OUTCOME MEASURES: A crowding estimation tool (SONET: Severely overcrowded, Overcrowded and Not overcrowded Estimation Tool) was derived using the linear regression analysis. The average length of stay (LOS) in UCC patients and the number of left without being seen (LWBS) patients were calculated and compared under the three different levels of UCC crowding.

resultsFour independent operational variables could affect the UCC overcrowding score including the total number of patients, the number of results pending for patients, the number of patients in the waiting room and the longest time a patient was stationed in the waiting room. In addition, UCC overcrowding was associated with longer average LOS (not overcrowded: 133±76 min, overcrowded: 169±79 min, and severely overcrowded: 196±87 min, p<0.001) and an increased number of LWBS patients (not overcrowded: 0.28±0.69 patients, overcrowded: 0.64±0.98, and severely overcrowded: 1.00±0.97).

conclusionsThe overcrowding estimation tool (SONET) derived in this study might be used to determine different levels of crowding in a high volume UCC setting. It also showed that UCC overcrowding might be associated with negative patient care outcomes.

Indexed as

CrowdingAdultAmbulatory Care FacilitiesEmergency Service, HospitalFemaleHumansMaleMiddle AgedPatient Outcome AssessmentPilot ProjectsProspective StudiesWaiting ListsACCIDENT & EMERGENCY MEDICINE

Identifiers

PMID25872940
PMCPMC4401867

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.