Left Without Being Seen: A Scoping Review of a Silent Crisis in Emergency Departments

Abstract

Background

Left Without Being Seen (LWBS) rates are widely recognized as a key quality indicator in Emergency Departments (ED) worldwide. Their clinical relevance is substantial, given the documented association between LWBS and increased morbidity and mortality among patients presenting to the ED. However, the available evidence is extensive and highly heterogeneous; therefore, a scoping review represents a more appropriate approach for synthesizing the evidence than a systematic review or meta-analysis.

Objective

This scoping review aims to synthesize current evidence regarding population characteristics, underlying determinants, and potential interventions associated with LWBS rates, pondering the need to strengthen strategies for identifying and reducing these events.

Design

Scoping review conducted according to PRISMA-ScR guidelines. We searched four databases (PubMed, Scopus, Oxford Academic, and EBSCO) between Jan 01, 2020 – Dec 31,2025. To meet the eligibility criteria, studies were required to be observational analytical, interventional, or evidence synthesis, given the limited evidence found, posters involving studies of human participants in ED settings.

Results

Ninety-four publications were included with de eligibility criteria Most studies were interventional and conducted in North America; however, systematic reviews and additional studies from Europe, Asia, Australia, South America, and the Middle East were also identified. Reported LWBS rates varied widely across settings and were influenced by both community-level and individual-level factors, including demographic characteristics, EDs staffing, time of presentation, chief complaint, and facility resources, as well as contextual factors such as the COVID-19 pandemic. The available evidence demonstrated considerable heterogeneity in the definition and characterization of LWBS causes, largely due to differences in reporting practices, documentation, and descriptions of events related to this outcome. Numerous interventions aimed at reducing LWBS rates were described.

Conclusion

LWBS is a key emergency care quality indicator driven by waiting times, crowding, and temporal factors. It predominantly affects low-acuity, socioeconomically vulnerable adults. Physician-in-triage reduces LWBS, while predictive models identify high-risk patients. Associated with revisits and mortality, LWBS requires flow optimization and context-adapted strategies. Standardized frameworks are needed to strengthen evidence.

Introduction

Rationale and Objectives

LWBS refers to patients who register at an emergency department (ED) but leave before being evaluated by a physician. The literature uses multiple terms to describe this quality indicator (Appendix A). This phenomenon is recognized as a critical performance metric by regulatory agencies, such as the Centers for Medicare and Medicaid Services in the United States, which use it to assess the accessibility, efficiency, and safety of emergency care.¹

Evidence indicates that several factors are associated with LWBS, particularly ED crowding—manifested by prolonged waiting times—which is the primary determinant of patient departure before evaluation.² However, findings also suggest that LWBS rates do not increase linearly with patient volume; instead, they rise sharply once ED capacity exceeds critical thresholds, reflecting the nonlinear and systemic nature of this problem. This challenge appears to arise predominantly from internal process bottlenecks and constraints in hospital discharge capacity, rather than from individual patient characteristics.³ The “input–throughput–output” conceptual framework has been widely applied to explain how patient inflow, internal ED processes, and discharge capacity interact to influence LWBS rates¹. In line with this framework, several interventions have been tested or implemented to reduce LWBS rates, including the integration of primary healthcare professionals into triage processes, such as nurse practitioners and triage liaison providers (TLP).^4,5

Historically, LWBS rates have ranged from 1% to 15% of total visits, with averages between 2% and 4% before the COVID-19 pandemic, underscoring the persistence and progressive worsening of this issue. In the aftermath of the most acute waves of the COVID-19 pandemic, both adult and pediatric ED have experienced a dramatic and sustained increase in LWBS rates, establishing an alarming new baseline.¹ Another factor associated with LWBS is patient demographic characteristics, as individuals are typically younger, male, and present with lower-acuity conditions. Additionally, factors related to the time of presentation are relevant, as patients frequently arrive during evening hours or periods of high demand.^6,7 Furthermore, LWBS prevalence is higher in hospitals serving low-income or underinsured populations.² Evidence regarding outcomes associated with LWBS remains limited; however, some studies have reported 30-day mortality, as well as increased rates of readmission and emergency department reconsultation.^8–10

This scoping review aims to synthesize current knowledge and identify research gaps arising from the fragmented and heterogeneous evidence on LWBS through the mapping of existing literature, with the goal of promoting future research and contributing to ED quality improvement. To achieve this objective, the following research questions guided the methodological framework: What findings have been reported in the scientific literature regarding the characteristics, causes, and outcomes of patients who leave the emergency department without being seen during the last five years? What interventions have been implemented in emergency department settings to reduce LWBS? These questions were developed in collaboration with an emergency physician who, in contrast to the academic literature, encounters practical challenges related to patient care and participation in daily clinical practice.

Methods

Protocol and Registration

This scoping review was conducted without a predefined review protocol. The study received ethical approval from the Ethics Committee of the Pontificia Universidad Javeriana.

Eligibility Criteria

We included analytical, experimental, and evidence synthesis studies published in English or Spanish that reported data related to LWBS in the emergency department (ED) and involved human participants only. Eligible studies were those published within the last five years (2020–2025). We excluded theoretical works (eg, practice guidelines or protocols) and studies without an abstract. Grey literature was not included in the search strategy. Given the limited evidence found, posters involving studies of human participants in ED settings.

Information Sources

A bibliographic search was conducted across multiple databases (PubMed, ScienceDirect, Scopus, EBSCO, Embase, and Ovid) covering the period from January 2020 to August 2025, along with additional sources identified through reference lists.

Search Strategy

The database search was independently conducted using the following search strategy: (“emergency department” OR “emergency room” OR “emergency service”) AND (“left without being seen” OR LWBS OR “leave without being seen”) AND (characteristics OR demographics OR “patient profile” OR predictors OR “risk factors” OR causes OR “associated factors” OR barriers OR outcomes OR revisits OR “follow-up” OR readmission OR mortality). Filters were applied in accordance with the established eligibility criteria.

Selection of Sources of Evidence

The screening process was conducted by the research team using the Rayyan platform.¹¹ A paired-review approach was used, whereby the total number of records was evenly allocated across three reviewer pairs. Each pair independently evaluated titles and abstracts. Subsequently, the full research team convened to discuss and resolve discrepancies regarding study inclusion or exclusion, achieving consensus when required.

Data Charting Process and Items

A data-charting form was developed to identify the variables for extraction and was subsequently completed. The collected data was then reviewed. Information related to article characteristics, contextual factors, and details concerning LWBS was extracted.

Synthesis of Results

Data from the included studies were extracted according to the following criteria: study design, inclusion of an intervention, country of origin, study quality, population characteristics, and quantitative data related to LWBS. Subsequently, the studies were classified into two main categories: Administrative or Technological Interventions and Population Characterization, with a subcategory for those conducted during the COVID-19 pandemic. The evidence will be presented in both tabular and narrative formats, and a diagram will be provided to illustrate selected data.

Results

Selection of Sources of Evidence

Database searches identified 446 records. After removal of 202 duplicates, 244 records were screened by title and abstract, and 129 were excluded at this stage. The remaining 115 reports underwent full-text eligibility assessment. During full-text review, 21 studies were excluded due to the absence of LWBS outcome reporting, unclear study design, duplicate publication, lack of full-text availability, or non–emergency department settings. Ultimately, 95 studies met the inclusion criteria and were included in this scoping review. (Figure 1).

Figure 1.

Flow chart PRISMA: Identification of studies via databases.

Characteristics of Sources of Evidence

Of the 94 studies; most of them are full-length journal articles (88.3%) and poster abstracts (11.7%), published between 2020 and 2025. A substantial majority were conducted in North America (73.4%), with the remainder distributed across Europe (9.5%), Asia (5.3%), Australia (3.1%), South America (4.2%), and the Middle East (4.2%). Most studies employed an interventional design, primarily retrospective observational studies (20.2%) or cross-sectional observational studies (3.1%); the remaining studies included analytic designs (20.2%), systematic reviews (6.3%), experimental studies (4.2%), descriptive studies (44.6%), and one editor letter (1.1%). The median duration of the interventions reported was 19 months, ranging from 30 days to 96 months. Most studies were conducted in urban ED (86.2%), with a smaller portion in rural facilities (13.8%). The ED population was pediatric (11.7%), adult (61.7%), or mixed adult-pediatric (26.6%). Study quality was assessed using the GRADE system,¹² with 6 studies rated as high quality, 30 as moderate quality, and 56 as low quality.

General Aspects

Upon review of the included studies, LWBS rate data were summarized graphically in Figure 2 to illustrate the global distribution.

Figure 2.

Global distribution of patients LWBS in emergency departments, 2020–2025.

Studies conducted across multiple regions provided valuable insights into LWBS. A summary of the principal demographic characteristics is presented in Appendix B. In Spain, an LWBS/LAMA (leave against medical advice) rate of 2.1% was reported, together with care complexity and individual factors encompassing five domains. complicate care delivery (comorbidity and complications, developmental, psycho-emotional, mental-cognitive, and sociocultural); identified as protective against LWBS/DAMA (OR: 0.64; 95% CI: 0.55–0.74).¹³

In Canada, reports from the Canadian Institute for Health Information indicate that the acceptable LWBS rate should remain below 3%.¹⁴ However, studies suggest otherwise with high-system users, representing the top 10% of ED visits, demonstrated a greater likelihood of LWBS (OR: 1.1; 95% CI).¹⁵ In the United Kingdom (UK), unexpected surges in patient volume increased the probability of non-avoidable patients leaving the hospital without treatment.¹⁶ Finally, in Saudi Arabia, prolonged waiting times were identified as a major determinant, with 80% of participants citing fatigue from waiting as the main reason for leaving, and 61.7% subsequently seeking medical attention elsewhere.¹⁷

In Lebanon, a case-control study with a stepwise multivariate logistic regression analyzed factors associated with LWBS, where males were more likely to LWBS (OR (95% CI): 2.87 (1.45–5.66), p = 0.002), and each 10-minute increase in waiting time elevated the likelihood of LWBS by 1.45 times (OR 1.45, CI: 1.20–1.74, p < 0.0001). Furthermore, patients with undergraduate or lower education levels leave more than those holding graduate or higher degrees (OR 3.83, CI: 1.70–8.62, p = 0.001). Conversely, individuals with one or more ED visits in the previous year were less likely to LWBS (OR 0.32, CI:0.14–0.71, p = 0.005; OR 0.19, CI: 0.08–0.47, p < 0.0001, respectively).¹⁸

Multiple studies from the US offer significant insights into LWBS patterns. A study found that older patients demonstrated a higher likelihood of returning for a subsequent visit (OR 1.08, CI: 1.01–1.15), whereas Black patients (OR 0.68, CI: 0.50–0.93), weekend visitors (OR 0.63, CI: 0.45–0.89), and those presenting with HEENT (head, eyes, ears, nose, and throat) complaints (OR 0.41, CI: 0.19–0.87) were less likely to revisit within three weeks. A large-scale analysis including 32,680,232 ED patients found that male individuals had higher odds of LWBS (OR 1.15, CI: 1.12–1.18), while pediatric and older adult populations (>64 years) exhibited lower odds compared to middle-aged adults (OR 0.28, CI: 0.24–0.32; OR 0.46, CI: 0.42–0.50).¹⁹ Another study conducted in Boston reported an overall LWBS rate of 1.82%, with the highest rates observed on Wednesdays (2.4%) and during late-night hours between 10:00 and 11:00 PM (3.7%). A strong correlation was identified between LWBS frequency and total ED volume (R2 = 0.95).³ Similarly, an additional analysis revealed a significant positive association between high-acuity LWBS cases and total daily ED visits (rs = 0.41, p < 0.001).²⁰

Several studies have examined LWBS in specific populations and contexts. Patients with a history of incarceration showed a higher likelihood of LWBS (OR: 1.32; CI: 0.82–2.01).²¹ In a multivariate regression model evaluating the SEP-1 score for sepsis care,²² LWBS was independently and negatively associated with hospital SEP-1 performance (CI: −1.42 to −0.58).²³ The Social Vulnerability Index (SVI) was also identified as a predictor of LWBS, showing a 7% increase in odds for every 0.1-unit rise in SVI (OR: 1.07; CI: 1.06–1.09; p < 0.01).²³ Among patients with alcohol-related facial injuries, the LWBS rate was significantly higher (3.8% vs 1.8%; p < 0.001).²⁴ Lastly, an analysis of monthly ED volumes (mean = 10,636; range: 9,581–11,437) and LWBS counts (mean = 181; range: 54–430) found that LWBS accounted for 0.5–4.0% of visits, with a minimal correlation between LWBS and ED volume (Pearson = 0.19).²⁵

Additionally, several studies have examined LWBS in pediatric populations to describe demographic profile (Appendix C). In the US, a study reported a 1.4% LWBS rate, with younger age associated with a higher likelihood of leaving (OR: 0.98 per year decrease in age); evening and overnight arrivals significantly increased LWBS odds (OR: 6.7 and 7.3, respectively), and uninsured patients were 2.4 times more likely to leave compared with those privately insured (3.6%).²⁶ A study of 54,890 patients reported a 1.22% LWBS rate, with both National Emergency Department Overcrowding Scale (NEDOCS)²⁷ and occupancy rate showing strong predictive performance (AUC ≈ 0.87). For every 10-point NEDOCS or 10% occupancy increase, LWBS odds rose 1.30- and 1.23-fold, respectively, explaining 54–56% of LWBS variance.¹ Similarly, another study using the Modified NEDOCS reported that LWBS odds doubled with each category increase (OR: 2.03; CI: 2.00–2.06).²⁷ In Canada, a departmental complexity score (based on registration volume, triage acuity, and length of stay) was strongly correlated with LWBS, rates increased from 3% to 13% as complexity rose. Higher complexity was also associated with longer physician assessment times among higher-acuity patients (CTAS 4–5).²⁸ In Japan, predictors of LWBS included low acuity (OR: 2.33; CI: 1.71–3.19), weekend/holiday visits (OR: 1.71; CI: 1.26–2.33), and evening presentations (OR: 1.44; CI: 1.06–1.96). Longer LOS (length of stay) and waiting times were major risk factors, with LWBS odds increasing to 3.48 for LOS >1 hour and rising dramatically with prolonged waits (>1 hour OR: 41.93; >2 hours OR: 359).²⁹ Lower triage and arrival between 8 PM and 4 AM were also associated with higher LWBS risk.³⁰ There is a study involving 31 caregivers (from 80,000 patients with 10% LWBS rate), identified communication as the most critical factor in preventing LWBS, concluding that the LWBS decision is multifactorial;³¹ however, enhancing the quality of the waiting experience through consistent and effective staff-family communication plays a key role in reducing LWBS rates.³²

Regarding reasons for leaving among pediatric patients, studies from Japan identified symptom improvement (55%), long waiting times (16%), sufficient information at triage (11%), competing priorities (6%), and emergency department crowding (4%); additional reasons accounted for 14%.²⁹

A study conducted in the US examined the association between the ED nursing work environment and ED outcomes, including LWBS. The authors reported that “mixed” work environments had the highest median LWBS rate (2.2%) and that improvements in the ED work environment from poor to mixed, and from mixed to better, were associated with a 19% reduction in LWBS rates (P ≤.01).³²

Studies have also compared different types of emergency care facilities. One investigation found that freestanding emergency departments (FSED) had a 40% lower LWBS rate compared with hospital-based emergency departments (HBED) (0.9% vs 1.5%; 95% CI, −0.5 to −0.2).³³ Another US study reported that LWBS rates in hospital-based ED decreased from 2.7% in 2012 to 2.0% in 2016. Moreover, the decline occurred regardless of the number FSED entering the local market, suggesting that the presence of FSED did not significantly influence LWBS trends in HBED.³⁴

Readmission/Reconsultations

Multiple studies have examined readmission patterns among LWBS patients across various time frames. In Turkey, 10.2% of LWBS patients were readmitted within 72 hours, with individuals aged 65 years and older exhibiting higher rehospitalization rates.⁸ In the US, among 8,206 LWBS patients, 35.6% (CI: 34.6–36.7) returned within 30 days, with a median return time of 23.9 hours (CI: 21.9–27.9) and a 14.5% admission rate upon return.⁹ In Japan, 12 patients (7.1%) returned to the ED, three with higher triage acuity, and only one (0.6%) required hospitalization.²⁹ Similarly, in Qatar, among 1,753 patients, 32.8% (CI: 30.6–35.1%) of unexpected return visits involved LWBS cases.¹⁰

A US study involving 1,474,395 patients where 1.2% were LWBS found that 17.7% of LWBS individuals returned within 72 hours—significantly higher than those evaluated and discharged (6.5%, p < 0.001)—and 28.8% returned within 30 days. Compared with discharged patients, LWBS individuals were younger (44.8 vs 48.1 years, p < 0.001), more likely male (48.9% vs 45.2%, p < 0.001), and had lower acuity (ESI 3.08 vs 3.17, p < 0.001). Of these patients that LWBS 0.5% were mentioned with the outcome of mortality within the next 30 days.¹⁰ Another US study confirmed similar findings, reporting that younger age (OR: 0.98; CI: 0.98–0.99) and lower acuity (OR: 2.01; CI: 1.84–2.20) were associated with LWBS.³⁵ Additionally, returning patients tended to be older (OR: 1.09; CI: 1.01–1.18), while weekend arrivals (OR: 0.64; CI: 0.41–0.97) and HEENT complaints (OR: 0.30; CI: 0.10–0.86) were linked to lower return likelihood.³⁶

Regarding First Nations populations, an Australian study reported that 27% of LWBS patients returned within seven days.³⁷ In Canada, 23.4% of First Nations LWBS patients revisited the ED within 72 hours compared with 20.2% of non–First Nations patients (p < 0.001), with similar hospitalization rates between both groups (4.9% vs 5.2%, p = 0.14).³⁸

Reasons to Consult or Complaints

Studies from US, Saudi Arabia, Turkey and Lebanon reported the complaints for consultation of LWBS patients, and between the most common were abdominal/gastrointestinal with rates from 18.33% to 23%, chest pain/cardiovascular with rates from 10% to 15.2%, neurologic/headache with rates from 12% to 14.2%, musculoskeletal around 20.3%, injury/pain/trauma from around 24%.^8,39 Also, an US study identified 331 unique complaints, with 8 of the 10 most frequent having an ESI level of 3 or higher.³⁹ More specifically, in Australia, a study involving psychiatric patients found that the predominant reasons for seeking care included experiencing an unmanageable crisis—most commonly a suicidal attempt—not knowing where else to go, being brought by others out of concern, or presenting with physical symptoms. The reasons cited for leaving were categorized as “tipping point”, “waiting time”, “no treatment”, and feeling “not understood or judged”.⁴⁰

Historical Data on Interventions from Systematic Reviews

The integration of primary healthcare professionals, such as nurse practitioners and nurses with expanded authority, ED triage has consistently demonstrated reductions in rates of LWBS patients. Among ten studies that evaluated LWBS outcomes, eight reported reductions, five of which were statistically significant. The median decrease in LWBS was 2.31% (IQR: −0.39 to −3.77), with individual studies conducted between 2012 and 2017 reporting reductions ranging from 1.4% to 6.7%.⁴¹ Similarly, in an analysis of triage liaison provider (TLP) interventions across 12 studies encompassing 329,340 patients, significant reductions in LWBS were observed. Although ten studies provided LWBS data with risk ratios ranging from 0.15 to 0.95, substantial heterogeneity (I² = 96%) initially prevented data pooling. Sensitivity analysis by provider type revealed that TLP interventions led by attending physicians significantly reduced LWBS rates (RR 0.62, CI 0.54–0.71; 6 studies, 146,775 patients), whereas findings for resident physicians (I² = 83%) and non-physician providers (I² = 92%) were inconclusive. These outcomes were attributed to early provider engagement at triage, which mitigates the principal driver of LWBS prolonged waiting times. These results are consistent with previous meta-analyses that reported comparable effect sizes (RR 0.56, CI 0.51–0.61) for senior physician-led triage intervention.⁴

Furthermore, another study examining the relationship between ED nurse staffing levels and patient outcomes found that decreased staffing was consistently associated with higher LWBS rates. Statistically significant associations were reported across three analyses: shifts with registered nurse (RN) staffing below 90% of scheduled hours were associated with a 2.4-fold increase in LWBS (OR 2.4; CI 1.3–4.5), and days in the lowest quartile of nursing hours had nine additional LWBS patients compared with adequately staffed days. In addition, implementation of mandated nurse-to-patient ratios was associated with significant reductions in LWBS (from 11.9% to 11.2%, p<0.0001).⁴²

A scoping review of 31 studies evaluating the role of physician assistants (PA) in ED settings similarly revealed consistent evidence of LWBS reduction following PA integration. Six studies specifically assessed LWBS as an outcome, and all reported significant reductions: PAs serving as triage liaison providers (TLPs) reduced LWBS from 9.7% to 1.4% (p < 0.001), whereas general PA involvement decreased LWBS from 5.2% to 3.4% (p < 0.001) compared with physician-only models. Adjusted analyses indicated reductions of up to 50%, with the greatest benefit observed among patients with low- to moderate-acuity presentations and concurrent improvements in ED throughput measures, including waiting times and length of stay (LOS).⁴³

In contrast, a systematic review of 20 studies on medical scribe programs in ED revealed limited evidence regarding LWBS outcomes. Only one study reported LWBS data and noted an unexpected increase from 2.9% to 4.4%.⁴⁴ Additionally, a systematic review of 12 studies investigating team triage (physicians and nurses collaborating in triage) showed consistent reductions in LWBS across most studies. Ten studies demonstrated mean waiting time decreases of 32.3 minutes (range: 3–122 minutes). Two studies specifically reported significant LWBS reductions, attributing improvements to expedited patient evaluation and management through early physician involvement at triage. However, two studies noted no improvement, potentially due to ED presentations unsuitable for emergency care. Overall, the review concluded that team triage reduces LWBS by enhancing patient perceptions of care through earlier interaction with healthcare providers.⁴⁵

Interventions: Administrative and Technological

We categorized the interventions into two groups: administrative and technological. Detailed descriptions of each category are presented in Table 1 and Table 2.

Table 1.

Adminstrative Interventions

Study (Author, Year)	Country	Design	Intervention	Model/Approach	N	Δ LWBS (%)	Performance Metrics	Quality
Staffing Interventions
Heslin S.M et al 202546	US	RT	PNT	Triage staffing	23,516	−3.4	p<0.001	B
Shah R et al 202047	US	RT	PIT	Triage staffing	5230	−2.5	Sig	B
Mahmood F.T et al 202448	Saudi Arabia	RT	PIT	Triage staffing	7826	>-1	p<0.001	B
Brodrick Z et al 202149	US	OB	PIT	Triage staffing	115,414	−3.9	p < 0.005	D
Schwartz H et al 202450	US	PRO	TTL	Team triage	50,198	−2.0 and 3.8	p<0.001	C
Crowder K et al 202351	Canada	OB	EP flow lead	Staffing model	55,201	−2.1	p= 0.01	B
De la Roche M.R.P et al 202152	Canada	Cohort	Physician assistant added	Clinical staff	20,477	−1.8	p<0.001	B
King N.M.A et al 20245	UK	RT	PA vs FY1	Clinical staff	7405	1.98 vs 1.20	NR	C
Sember M et al 202153	US	RT	Advanced practice provider	Clinical staff	2162	−4	p=0.005	C
Wing SR et al 202554	US	Cohort	Guest service ambassadors	Non-clinical	50,507	−1.4	p< 0.001	B
Process/Flow Interventions
Peng L.S et al 202155	Malaysia	RT	2-tier triage	Triage redesign	9977	−2.1	p < 0.001	B
Leggio, W.J et al 202256	US	RT	Flow model	Pivot triage + vertical flow	17,394	−2.4	NR	B
DeVore K et al 202457	US	RT	RDH	Process redesign	19,596	−6.2	p <0.001	B
Kenny B et al 202458	US	RT	Lean FT	Lean	20,093	−5.3	p=0.11	B
Goenka A et al 202459	India	INT	PDCA	Lean	1200	−0.2	NR	B
Landis C et al 202560	US	CIP	Cluster	Bundle	45,814	−10.2	p <0.001	C
Sethi S et al 202061	UK	RT	Flow routine	Throughput	160,373	−1.4	NR	B
Devia J et al 202462	Colombia	RT	FT + AMU	Flow pathway	22,743	-0.05	↓ NS	B
Rittenberger J et al 202463	US	RT	Discharge	Disposition	NR	−0.64	p =0.007	D
Randall L et al 202064	US	Project	SOrT	Process redesign	NR	−7.05		D
Hemmert K.C et al 202065	US	RT	SFP pathways	Split flow	88,894	−4.7	p= <0.00001	D
De la Roche M.R.P et al 202166	Canada	RT	Waiting room	Environmental	37,799	−3	p<0.01	B
Alishahi A et al 202067	US	RT	Multi-level	System process	269,721	−0.95	p< 0.001	B
Organizational Interventions
Adriani et al 202268	Italy	RT	New model	System redesign	30,407	−7.0	p< 0.001	B
Wilkins T et al 202469	US	PT	Surge plan	Capacity	12,269	−0.8	↓ NS	C
DeLeon E et al 202070	US	RT	ACS	Alt care site	180	−0.58	p=0.001	D
Digital Interventions
Joshi A.U et al 202071	US	RT	Tele-intake	Telehealth	39,538	−0.7	↓ NS	B
Peuser D et al 202172	US	PRO	Tele-triage	Telehealth	22	0	No efecct	C
Mcleod S.L et al 202173	Canada	Cohort	eCTAS	Decision-support	354,176	+0.2	↑ Significant	B
Milne LW et al 202074	US	Experimental	Triage tool	Screening tool	214,219	−1	p < 0.001	B

Abbreviations: LWBS, Leave without being seen; RT, Retrospective; PRO, Prospective; OB, Observational; INT, Interventional; PIT, Provider in triage; PNT, Physician–nurse team; TTL, Triage team lead; PA, Physician assistant; APP, Advanced practice provider; GSA, Guest service ambassador; AMU, Acute Medical Unit; PDCA, Plan–Do–Check–Act; RDH, Receiver-driven handoff; SFP, Split flow pathway; ACS, Alternate care site; NS, Not significant; NR, Not reported; OR, Odds ratio; FY1s, Foundation year 1 doctor in training; PHCP, Primary healthcare professionals; FTS, Fast Track strategy; LWT, Leave without treatment; SOrT, sort, order, and treatment.

Table 2.

Technological Interventions

Study	Setting (Country)/Sample	Intervention	Model/Approach	LWBS Outcome (%)	Performance Metrics	Quality
Organizational/Process
Jewer et al (2022)75	Rural hospital (Canada)/NR	WST-based redesign	-	12.1 → 4.6	-	B
Kirby et al (2024)76	Trauma center (USA)/1,919	PMML + process optimization	XGBoost, RF + flow chang	4.82 → 1.93	Accuracy 88% (XGBoost) and 89% RF	C
Mullins et al (2022)77	Trauma center (USA)/19,958	Telehealth (VTR)	Virtual rounding	25→8	-	D
Predictive Models (PMML)
Marino et al (2024)78	Univ. hospital (Italy)/688,870	PMML	Decision Tree	5.68	Accuracy 94%	B
Sheraton et al (2020)19	Multicenter (USA)/32.6M	National model	-	1.27	Concordance 63.1%	B
Scala et al (2025)79	Single hospital (Italy)/80,614	PMML	RF, NB, DT, LR	12.12	AUC 58–65%	B
Hunter et al (2024)80	Mayo Clinic (USA)/161,933	PMML	XGBoost	3.54	Acc 96%, AUC 85%	C
Sarty et al (2023)81	Pediatric ED (Canada)/101,266	PMML	XGBoost	5.7	Recall 95%, Sens 87%	C
Simulation Models
Tian et al (2023)82	6 hospitals (Canada)/253,177	Simulation	Discrete-event	↓ 0.1–4.9%	-	C

Abbreviations: LWBS, Leave Without Being Seen; ML, Machine Learning; PMML, Predictive Models; RF, Random Forest; NB, Naïve Bayes; DT, Decision Tree; LR, Logistic Regression; AUC, Area Under the Curve; VTR, Virtual Telehealth Rounding; NR, Not Reported.

Changes During the Pandemic

The COVID-19 pandemic compelled numerous countries to restructure their healthcare systems to address the emergent situation, resulting in the exacerbation of pre-existing deficiencies in supply and nurse/physician staffing.⁸³ Eight studies presented data from pre-pandemic, pandemic, and post-pandemic periods. Most studies originated from the US, with others from South Korea and Canada. A 2020 US study, demonstrated that atypical discharges during the pandemic included 16% LWBS cases, compared to 89.58% in the pre-pandemic period. Furthermore, the majority of LWBS cases involved COVID-related concerns, accounting for 10.71%.⁸⁴ In another mental health study, LWBS rates increased from 5.5 per 1,000 encounters at the 5th percentile of monthly mental and behavioral health hours to 16.6 per 1,000 encounters at the 95th percentile (defined as the duration of ED LOS).⁸⁵ Another study examined the Community Resources for Emergency Department Overuse (CREDO) program, which targeted frequent users with 10 or more ED visits within the preceding year. They found that the pre-COVID rate of LWCS (including LAMA and LWBS) in the CREDO group was 11.8% versus 35.1% post-COVID (p<0.001), whereas the LWCS rate for the general population was 6.7% pre-COVID and 14.8% post-COVID (p<0.001). Post-COVID, CREDO patients demonstrated 3.4 times the odds (CI 3.1–3.6, p<0.001) of leaving LWCS compared to all other patients.⁸⁶ A letter to the editor, reported only a minor increase from 0.82% to 0.91% in LWBS rates in the AHMC Health System.⁸⁷ In South Korea, 240 (2.8%) and 1,106 (19.2%) LWBS cases involving fever/respiratory patients (FRPs) were documented during the pre-COVID-19 and post-COVID-19 periods, respectively, with the LWBS rate within 60 minutes being higher during the post-COVID-19 period. FRPs (odds ratio 1.76; 95% confidence interval 1.59–1.84) and the post-COVID-19 period (odds ratio 2.29; 95% confidence interval 2.15–2.44) were associated with LWBS.⁸⁸ Conversely, another study observed that during the pre-pandemic period, 1.8% of patients LWBS; this rate decreased to 1.4% during the COVID period and subsequently increased to 10.7% during the post-pandemic period.³⁰ A 2021 study reported that the LWBS rate was 1.66% in 2019 and 2.82% in 2020, hypothesizing that patient walkouts were likely attributable to fear of viral exposure while in the ED.⁸⁹

Finally, in Canada, the proportion of LWBS visits categorized as emergent on the Canadian Triage and Acuity Scale (CTAS) was higher during the recent period (only post-pandemic) (12.9% recent vs 9.2% baseline, standardized difference 0.12).⁹⁰

Discussion

Findings on LWBS are characterized by substantial heterogeneity in reporting, registration, and definitions. LWBS remains an unstandardized metric, functioning as an umbrella term that includes concepts such as LAMA and LBTC, both identified in multiple studies within this review. This terminological overlap generates inconsistencies in administrative records and contributes to global underreporting, making it unclear whether observed variations reflect differences in clinical efficiency, health system structures, or patient demographics. Reported LWBS rates range from 0.43% to 10.2%, underscoring the need for standardized definitions and registration practices. This gap is particularly evident in Latin America, Africa, and Asia, where limited data restrict generalizability and hinder analysis in low-resource settings.

Although not all studies provided detailed demographic data, those that did showed consistent patterns. LWBS patients are predominantly low-acuity at triage, indicating no immediate need for urgent stabilization. Adults aged 18–60 years are more likely to leave the emergency department compared with pediatric (<18 years) and older populations (≥60–65 years), which report lower LWBS rates globally. However, these findings require further validation through more rigorous analyses of patient characteristics. Temporal patterns indicate fewer LWBS cases on weekends among adults, whereas pediatric cases increase during weekends.

Across studies, LWBS occurs more frequently during nighttime hours and periods of high emergency department volume, when perceived delays in care increase the likelihood of departure. A female predominance was observed in both adult and pediatric populations; however, the underlying causes of this sex-based difference remain unclear and warrant further investigation within a robust analytical framework incorporating demographic and contextual factors.

Among evaluated interventions, the most common was the inclusion of a physician in triage (Triage Liaison Provider model). Most studies were conducted in high-income settings, such as the United States and Saudi Arabia, where resource availability facilitates implementation. In contrast, resource constraints in low- and middle-income countries may limit feasibility, increasing the relevance of alternative strategies such as patient flow redistribution, redesign of waiting areas, and telemedicine integration. Machine learning–based prediction models demonstrated strong performance, particularly in discrimination and predictive accuracy, suggesting that artificial intelligence may support early identification of patients at risk of LWBS. Prior systematic reviews have examined similar strategies, although the triage liaison provider model appears to yield the most consistent reductions in LWBS rates.

Several studies reported an association between the SARS-CoV-2 pandemic and increased LWBS rates. Fear of contagion was identified as a contributing factor, consistent with broader uncertainty and the persistence of transmission risk despite protective measures.

Regarding consequences, evidence indicates that LWBS affects multiple domains, including mortality, quality of care, healthcare costs, and reconsultation rates. LWBS has been independently associated with lower SEP-1 sepsis care scores,²² reflecting deficiencies in timely care. Increasing emergency department complexity has also been correlated with higher LWBS rates (from 3% to 13%), suggesting that system strain may compromise care quality and outcomes. Importantly, LWBS is not a benign event; a large US study reported a 0.5% 30-day mortality rate among these patients. While interventions such as physician-in-triage models may improve throughput, they are resource-intensive, particularly in low- and middle-income settings. Overall, LWBS should be considered not only a process metric but also an indicator associated with adverse outcomes, reduced quality of care, increased costs, and higher reconsultation rates.

Limitations

This scoping review has several limitations. First, most included studies were conducted in North America; therefore, both their findings and our analysis primarily reflect the characteristics of this population, potentially limiting generalizability to other contexts.

Second, the literature does not clearly define the clinical consequences for patients who LWBS before medical evaluation. Further research is needed to determine the true impact on patient outcomes, including quality of life, re-presentation to other healthcare facilities, legal implications, and healthcare system costs given finite resources.

Third, additional studies are required to evaluate mortality in this heterogeneous population, considering both demographic variability and differing care environments. Future research should include larger, more representative samples with greater demographic diversity.

Finally, a key methodological limitation of this review is the inclusion of highly heterogeneous data. The lack of standardized research frameworks hinders evidence synthesis and highlights the need for conceptual standardization, which would strengthen the validity of LWBS as a quality indicator and support the implementation of comparable interventions across diverse clinical settings.

Conclusions

LWBS is considered an important quality indicator for emergency services; however, available information remains limited across many regions of the world. The evidence collected and synthesized in this scoping review provides valuable insights. Regarding population characteristics, patients who LWBS are more likely to present with lower triage acuity, be adults rather than children or older adults, be male, have lower educational levels, and lack health insurance; these represent the most frequently reported characteristics in the literature. In terms of determinants, the evidence indicates that LWBS is influenced by day of the week, time of day, symptom progression, communication with healthcare staff, and emergency department patient volume. Across most studies, prolonged waiting time emerged as the strongest and most consistent predictor of LWBS. Based on the available evidence, it is not possible to determine which intervention is most effective; however, commonly implemented strategies include PIT and the use of PMML. Further research is required to evaluate the effectiveness of these strategies across diverse settings and populations. Nevertheless, the evidence synthesized in this review suggests that interventions targeting early provider contact at triage have demonstrated the most consistent reductions in LWBS rates. A limited number of studies have reported consequences of LWBS, including increased rates of emergency department readmissions and, in some cases, mortality. Additionally, the available evidence remains heterogeneous, and decision-makers should consider this when designing future studies employing standardized conceptual frameworks for LWBS. Furthermore, when applying existing evidence, it is essential to account for contextual variability and adapt interventions accordingly. Overall, LWBS should not be interpreted solely as an operational metric but as a critical indicator of gaps in timely access to care.

Funding Statement

This research received no external funding.

Disclosure

The authors declare no conflicts of interest or financial relationships relevant to this article. All stages of the review were conducted independently by the authors, and no funding bodies influenced the study design, data extraction, interpretation, or preparation of the manuscript.