Characteristics of ED crowding in the Lazio Region (Italy) and short-term health outcomes

Measures of Emergency Department Crowding, a Systematic Review. How to Make Sense of a Long List

Emergency department (ED) crowding, a common and serious phenomenon in many countries, lacks standardized definition and measurement methods. This systematic review critically analyzes the most commonly studied ED crowding measures. We followed the Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) guidelines. We searched PubMed/Medline Database for all studies published in English from January 1st, 1990, until December 1st, 2020. We used the National Institute of Health (NIH) Quality Assessment Tool to grade the included studies. The initial search yielded 2293 titles and abstracts, of whom we thoroughly reviewed 109 studies, then, after adding seven additional, included 90 in the final analysis. We excluded simple surveys, reviews, opinions, case reports, and letters to the editors. We included relevant papers published in English from 1990 to 2020. We did not grade any study as poor and graded 18 as fair and 72 as good. Most studies were conducted in the USA. The most studied crowding measures were the ED occupancy, the ED length of stay, and the ED volume. The most heterogeneous crowding measures were the boarding time and number of boarders. Except for the National ED Overcrowding Scale (NEDOCS) and the Emergency Department Work Index (EDWIN) scores, the studied measures are easy to calculate and communicate. Quality of care was the most studied outcome. The EDWIN and NEDOCS had no studies with the outcome mortality. The ED length of stay had no studies with the outcome perception of care. ED crowding was often associated with worse outcomes: higher mortality in 45% of the studies, worse quality of care in 75%, and a worse perception of care in 100%. The ED occupancy, ED volume, and ED length of stay are easy to measure, calculate and communicate, are homogenous in their definition, and were the most studied measures.

Predicting inhospital admission at the emergency department: a systematic review

Background

ED crowding has potential detrimental consequences for both patient care and staff. Advancing disposition can reduce crowding. This may be achieved by using prediction models for admission. This systematic review aims to present an overview of prediction models for admission at the ED. Furthermore, we aimed to identify the best prediction tool based on its performance, validation, calibration and clinical usability.

Methods

We included observational studies published in Embase.com, Medline Ovid, Cochrane CENTRAL, Web of Science Core Collection or Google scholar, in which admission models were developed or validated in a general medical population in European EDs including the UK. We used the Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies (CHARMS) checklist to assess quality of model development. Model performance was presented as discrimination and calibration. The search was performed on 11 October 2020.

Results

In total, 18 539 articles were identified. We included 11 studies, describing 16 different models, comprising the development of 9 models and 12 external validations of 11 models. The risk of bias of the development studies was considered low to medium. Discrimination, as represented by the area under the curve ranged from 0.630 to 0.878. Calibration was assessed in seven models and was strong. The best performing models are the models of Lucke et al and Cameron et al. These models combine clinical applicability, by inclusion of readily available parameters, and appropriate discrimination, calibration and validation.

Conclusion

None of the models are yet implemented in EDs. Further research is needed to assess the applicability and implementation of the best performing models in the ED.

Systematic review registration number

PROSPERO CRD42017057975.

Exploring Potential Association Between Emergency Department Crowding Status and Patients' Length of Stay at a University Hospital in Saudi Arabia

Background

Emergency department (ED) crowding has been described as the most serious problem that endangers the reliability of healthcare system worldwide. The aim of this study was to explore the possible relationship of ED crowding status and length of stay in patient received care. In addition, association between LOS and other variables in relation to crowding status has been explored.

Methods

This is a retrospective cohort analysis study done by using dataset abstracted from Quadra Med Information System of patients visited emergency department of a tertiary university hospital at Eastern Province of Saudi Arabia during the period of January 1st, 2018 to December 30th, 2018. ED occupancy rates were used to define crowding status (as crowding and overcrowding), while the percentage of patient who spent in ED more than 6 hours was used to define the length of stay in ED.

Results

There were 53,309 crowded and 57,290 overcrowded presentations in ED. The median length ± interquartile range of the length of stay for low-crowded and high-crowded conditions were 211 ± 606 and 242 ± 659 minutes, respectively. There was a significant association between ED crowding status and length of stay (p < 0.05).

Conclusion

The increased patients' length of stay at ED was associated with crowding status of ED. Therefore, decision-makers at ministry of health should develop and implement measures and interventions to shed light on the causes of crowding, to reduce the crowding at ED, and resolve the problem steamed from such crowding for the purpose of shorten patients' length of stay at ED.

Emergency department crowding associated with increased 30-day mortality: a cohort study in Stockholm Region, Sweden, 2012 to 2016

OBJECTIVES

Emergency department (ED) crowding is a major problem across the world. Studies investigating the association between crowding and mortality are many, but the quality is inconsistent and there are very few large, high-quality multicenter studies that are properly designed to deal with confounding due to case mix. The aim of this study is to investigate the association between ED crowding and 30-day mortality.

METHODS

We conducted an observational cohort study at all 7 EDs in Stockholm Region, Sweden 2012-2016. The crowding exposure was defined as the mean hourly ED census during the shift that the exposed patient arrived, divided with the expected ED census for this shift. The expected ED census was estimated using a separate linear model for each hospital with year and shift as predictors. The exposure was categorized in 3 groups: reference (lowest 75% of observations), moderate (75%-95% of observations), and high (highest 5% of observations). Hazard ratios (HR) for all-cause mortality within 30 days were estimated with a Cox proportional hazards model. The model was adjusted for age, sex, triage priority, arrival hour, weekend, arrival mode, chief complaint, number of prior hospital admissions, and comorbidities.

RESULTS

884,228 patients who visited the ED 2,252,656 times were included in the analysis. The estimated HR (95% confidence interval) for death within 30-days was 1.00 (0.97-1.03) in crowding category 75%-95% and 1.08 (1.03-1.14) in the 95%-100% category.

CONCLUSIONS

In a large cohort study including 7 EDs in Stockholm Region, Sweden we identified a significant association between high levels of ED crowding and increased 30-day mortality.

Emergency Department Overcrowding: A Retrospective Spatial Analysis and the Geocoding of Accesses. A Pilot Study in Rome

The overcrowding of first aid facilities creates considerable hardship and problems which have repercussions on patients’ wellbeing, the time needed for a diagnosis, and on the quality of the assistance. The basic objective of this contribution, based on the data collected by the Hospital Policlinico Umberto I in Rome (Lazio region, Italy), is to carry out a territorial screening of the municipality using GIS applications and spatial analyses aimed at reducing—in terms of triage—code white (inappropriate) attendances, after having identified the areas of greatest provenance of improperly used emergency room access. Working in a GIS environment and using functions for geocoding, we have tested an experimental model aimed at giving a close-up geographical-sanitary look at the situation: recognizing the territorial sectors in Rome which contribute to amplifying the Policlinico Umberto I emergency room overcrowding; leading up to an improvement of the situation; promoting greater awareness and knowledge of the services available on the territory, a closer relationship between patient and regular doctor (general practitioner, GP) or Local Healthcare Unit and a more efficient functioning of the emergency room. In particular, we have elaborated a “source” map from which derive all the others and it is a dot map on which all the codes white have been geolocalized on a satellite image through geocoding. We have produced three sets made up of three digital cartographic elaborations each, constructed on the census sections, the census areas and the sub-municipal areas, according to data aggregation, for absolute and relative values, and using different templates. Finally, following the same methodology and steps, we elaborated another dot map about all the codes red to provide another kind of information and input for social utility. In the near future, this system could be tested on a platform that spatially analyzes the emergency department (ED) accesses in near-real-time in order to facilitate the identification of critical territorial issues and intervene in a shorter time to regulate the influx of patients to the ED.

Blood sampling during nurse triage reduces patient length of stay in the emergency department: A propensity score-weighted, population-based study

BACKGROUND

Increases in patients' length of stay (LOS) in the emergency department (ED) have led to overcrowding.

OBJECTIVES

In this study, the implementation of blood sampling during triage in lower priority level patients was assessed as a possible means to reduce LOS.

METHODS

A retrospective study was performed from January 2018 to January 2019. Lower priority level patients who required blood sampling for further diagnosis were considered. Patients who underwent blood sampling during triage evaluation were compared with those who underwent blood sampling after a physician's initial evaluation.

RESULTS

During the study period, 15,596 patients were enrolled. LOS was shorter in patients who underwent triage blood sampling, presenting a median value of 154 min in comparison with the 172 min recorded in the control group (p < 0.001). Using a propensity score-matching to control the two groups' differences, LOS remained lower in the triage-sampling group (151 vs. 175 min; p < 0.001). In the adjusted multivariate model, triage blood sampling was found to be an independent factor for a decrease in the LOS, with standardized coefficient β = 0.857 (0.822-0.894; p < 0.001).

CONCLUSIONS

Performing blood sampling during nurse triage can decrease LOS in ED and also reduce ED permanence after a physician's initial evaluation.

Patients who leave Emergency Department without being seen or during treatment in the Lazio Region (Central Italy): Determinants and short term outcomes

Background and Aims

Patients who leave Emergency Department before physician’s visit (LWBS) or during treatment (LDT) represent a useful indicator of the emergency care's quality. The profile of patients LWBS was described: they are generally males, young, with lower urgency triage allocation and longer waiting time. They have a greater risk of ED re-admission compared to discharged patients, but effect on hospitalization and mortality are more controversial. The aims of this study are to identify determinants and adverse short term outcomes for LWBS and LDT patients.

Methods

This is a retrospective cohort study that include all ED visits of LWBS, LDT and discharged patients in 2015 in the Lazio region, Central Italy. Determinants of LWBS or LDT were selected from gender, age, citizenship, residence area, triage category, chronic comorbidities, number of uncompleted ED visit in the previous year, mode of arrival in ED, time-band, day of the week, waiting time and ED crowding, using a multi-level logistic regression. A multivariate logistic regression was used to test if LWBS or LDT have a greater risk of short term adverse outcome compared to discharged patients.

Results

The cohort consists in 835,440 visits in ED, 86.8% subjects visited and discharged, 8.9% subjects are LWBS patients and 4.3% LDT. LWBS and LDT patients are mainly young, males, with a less severe triage, with long waiting times in ED. Moreover, ED crowding and leaving ED before physician’s visit in the previous year are risk factors of self-discharging. LWBS and LDT patients have a higher risk of readmission (LWBS: OR = 4.63, 95%CI 4.5–4.7; OR = 2.89, 95%CI 2.8–2.9; LDT: OR = 3.12, 95%CI 3–3.2; OR = 2.25, 95%CI2.2–2.3 for readmissions within 2 and 7 days respectively) and hospitalization (LWBS: OR = 3.65, 95%CI 3.4–3.9; OR = 2.25, 95%CI 2.1–2.4; LDT: OR = 3.96, 95%CI 3.6–4.3; OR = 2.62, 95%CI 2.4–2.8 for hospitalization within 2 and 7 days respectively). Furthermore, we find a mortality excess of risk for LWBS patients compared to the reference group (OR = 2.56, 95%CI1.6–4.2; OR = 1.7, 95%CI 1.3–2.2 within 2 and 7 days respectively).

Conclusions

Determinants of LWBS confirmed what already known, but LDT patients should be further investigated. There could be adverse health effects for people with LWBS and LDT behaviour. This could be an issue that the Regional Health System should deal with.