Left without being seen in a hybrid point of service collection model emergency department

Hitti, Eveline; Hadid, Dima; Tamim, Hani; Hariri, Moustafa Al; Sayed, Mazen El

doi:10.1016/j.ajem.2019.05.034

Cited by 8 publications

(6 citation statements)

References 18 publications

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“…However, some studies from Europe and the Middle East have reported male sex to be associated consistently with LWBS. 17,19 Pham et al 7 analyzed data from NHAMCS and reported higher levels of LWBS at the extremes of age, which was corroborated by our analyses. Contrary to our findings, many studies show the pediatric population as being more predisposed to LWBS.…”

Section: Discussionsupporting

confidence: 87%

“…Unlike our study, male sex has not been found to be a significant factor in studies carried out in the United States. However, some studies from Europe and the Middle East have reported male sex to be associated consistently with LWBS 17,19 . Pham et al 7 analyzed data from NHAMCS and reported higher levels of LWBS at the extremes of age, which was corroborated by our analyses.…”

Section: Discussionsupporting

confidence: 86%

“…Unlike survey data collected primarily for research purposes, our data set missed out on several variables that could have been important for predictive modeling. For example, race/ethnicity 16 and level of education, 17 which have been shown to be predictors in previous studies, were not available for analyses. As urban and larger volume EDs capture more minority visits, the proportion of influence of these variables on LWBS that could be attributed to the diversity is important.…”

Section: Resultsmentioning

confidence: 99%

See 2 more Smart Citations

Patients leaving without being seen from the emergency department: A prediction model using machine learning on a nationwide database

Sheraton¹,

Gooch²,

Kashyap

2020

JACEP Open

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Section: Discussionsupporting

confidence: 87%

Section: Discussionsupporting

confidence: 86%

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Patients leaving without being seen from the emergency department: A prediction model using machine learning on a nationwide database

Sheraton¹,

Gooch²,

Kashyap

2020

JACEP Open

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“…In some studies, non-native language speaking background or non-compensable coverage status have been a strong predictor for LWBS [25,26,27]. In this study, however, patients whose native language was not Finnish were not overrepresented in LWBS.…”

Section: Discussioncontrasting

confidence: 65%

Patients Left Without Being Seen in the Emergency Department – A Retrospective Observational Patient Record Study

Holmberg

Innamaa

Hällberg

et al. 2021

Preprint

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BackgroundThe share of patients leaving the emergency department without being seen by a physician (LWBS) is an important efficacy marker of emergency departments around the world. It has not however, been of special research interest in the Nordic countries. In this study, we assessed the LWBS rate in Kanta-Häme Central Hospital, in Hämeenlinna, Finland. Secondarily, we gathered information of LWBS patients along with all ED patients.MethodsIn this retrospective observational patient record study, our primary aim was to assess the LWBS rate of all patient visits (n = 41,631) over a 12-month period in a mid-sized Finnish secondary hospital ED. Alongside, we gathered specific information, such as age, gender, time of day and year for attendance, reason for attendance, return to healthcare and mortality after 7 and 30 days and after one year to show characteristics of LWBS patients. We present data and hourly distribution of the LWBS patients against all patient visits to the ED.ResultsA total of 305 LWBS cases were identified, leading to an LWBS rate of 0.73 %. Most LWBS took place during afternoon hours, when the ED was most crowded and waiting times were longest. Among LWBS patients, minor traumas and non-specific pain were the most common reasons for attending. Mortality among LWBS patients was naught (0.0 %) over a one-year follow-up.ConclusionsThe LWBS rate in the Kanta-Häme Central Hospital ED was low. Higher LWBS rate coincided with rush hours and longer waiting times. The proportion of minor traumas was greater than in some earlier studies. These results support the implementation of a fast track line for minor traumas in the ED.

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“…As a result, the LWBS was reduced by more than 30% along with cost savings and annual revenue of approximately $190 million. The rest of studies based on integrated methods used a combination of statistical methods [222] and a mix of OR techniques [125,223] for tackling elevated LWBS and their consequences mainly affecting the financial sustainability of EDs.…”

Section: Papers Focusing On Diminishing the Patient Flow Time In Edmentioning

confidence: 99%

Methodological Approaches to Support Process Improvement in Emergency Departments: A Systematic Review

Ortíz‐Barrios

Alfaro-Saiz

2020

IJERPH

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The most commonly used techniques for addressing each Emergency Department (ED) problem (overcrowding, prolonged waiting time, extended length of stay, excessive patient flow time, and high left-without-being-seen (LWBS) rates) were specified to provide healthcare managers and researchers with a useful framework for effectively solving these operational deficiencies. Finally, we identified the existing research tendencies and highlighted opportunities for future work. We implemented the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology to undertake a review including scholarly articles published between April 1993 and October 2019. The selected papers were categorized considering the leading ED problems and publication year. Two hundred and three (203) papers distributed in 120 journals were found to meet the inclusion criteria. Furthermore, computer simulation and lean manufacturing were concluded to be the most prominent approaches for addressing the leading operational problems in EDs. In future interventions, ED administrators and researchers are widely advised to combine Operations Research (OR) methods, quality-based techniques, and data-driven approaches for upgrading the performance of EDs. On a different tack, more interventions are required for tackling overcrowding and high left-without-being-seen rates.

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Left without being seen in a hybrid point of service collection model emergency department

Cited by 8 publications

References 18 publications

Patients leaving without being seen from the emergency department: A prediction model using machine learning on a nationwide database

Patients leaving without being seen from the emergency department: A prediction model using machine learning on a nationwide database

Patients Left Without Being Seen in the Emergency Department – A Retrospective Observational Patient Record Study

Methodological Approaches to Support Process Improvement in Emergency Departments: A Systematic Review

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