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

A study of "left against medical advice" emergency department patients: an optimized explainable artificial intelligence framework

The issue of left against medical advice (LAMA) patients is common in today's emergency departments (EDs). This issue represents a medico-legal risk and may result in potential readmission, mortality, or revenue loss. Thus, understanding the factors that cause patients to "leave against medical advice" is vital to mitigate and potentially eliminate these adverse outcomes. This paper proposes a framework for studying the factors that affect LAMA in EDs. The framework integrates machine learning, metaheuristic optimization, and model interpretation techniques. Metaheuristic optimization is used for hyperparameter optimization-one of the main challenges of machine learning model development. Adaptive tabu simulated annealing (ATSA) metaheuristic algorithm is utilized for optimizing the parameters of extreme gradient boosting (XGB). The optimized XGB models are used to predict the LAMA outcomes for patients under treatment in ED. The designed algorithms are trained and tested using four data groups which are created using feature selection. The model with the best predictive performance is then interpreted using the SHaply Additive exPlanations (SHAP) method. The results show that best model has an area under the curve (AUC) and sensitivity of 76% and 82%, respectively. The best model was explained using SHAP method.

Interventions to improve emergency department throughput and care delivery indicators: A systematic review and meta-analysis

BACKGROUND

Emergency department (ED) crowding has repercussions on acute care, contributing to prolonged wait times, length of stay, and left without being seen (LWBS). These indicators are regarded as systemic shortcomings, reflecting a failure to provide equitable and accessible acute care. The objective was to evaluate the effectiveness of interventions aimed at improving ED care delivery indicators.

METHODS

This was a systematic review and meta-analysis of randomized controlled trials (RCTs) assessing ED interventions aimed at reducing key metrics of time to provider (TTP), time to disposition (TTD), and LWBS. We excluded disease-specific trials (e.g., stroke). We used Cochrane's revised tool to assess the risk of bias and Grading of Recommendations, Assessment, Development, and Evaluations to rate the quality of evidence. The meta-analysis was performed using a random-effects model and Cochrane Q test for heterogeneity. Data were summarized as means (±SD) for continuous variables and risk ratios (RR) with 95% confidence intervals (CIs).

RESULTS

We searched MEDLINE, EMBASE, and other major databases. A total of 1850 references were scanned and 20 RCTs were selected for inclusion. The trials reported at least one of the three outcomes of TTD, TTP, or LWBS. Most interventions focused on triage liaison physician and point-of-care (POC) testing. Others included upfront expedited workup (ordering tests before full evaluation by a provider), scribes, triage kiosks, and sending notifications to consultants or residents. POC testing decreased TTD by an average of 5-96 min (high heterogeneity) but slightly increased TTP by a mean difference of 2 min (95% CI 0.6-4 min). Utilizing a triage liaison physician reduced TTD by 28 min (95% CI 19-37 min; moderate-quality evidence) and was more effective in reducing LWBS than routine triage (RR 0.76, 95% CI 0.66-0.88; moderate quality).

CONCLUSIONS

Operational strategies such as POC testing and triage liaison physicians could mitigate the impact of ED crowding and appear to be effective. The current evidence supports these strategies when tailored to the appropriate practice environment.

Leaving emergency departments without completing treatment among First Nations and non-First Nations patients in Alberta: a mixed-methods study

BACKGROUND

Our previous research showed that, in Alberta, Canada, a higher proportion of visits to emergency departments and urgent care centres by First Nations patients ended in the patient leaving without being seen or against medical advice, compared with visits by non-First Nations patients. We sought to analyze whether these differences persisted after controlling for patient demographic and visit characteristics, and to explore reasons for leaving care.

METHODS

We conducted a mixed-methods study, including a population-based retrospective cohort study for the period of April 2012 to March 2017 using provincial administrative data. We used multivariable logistic regression models to control for demographics, visit characteristics, and facility types. We evaluated models for subgroups of visits with pre-selected illnesses. We also conducted qualitative, in-person sharing circles, a focus group, and 1-on-1 telephone interviews with health directors, emergency care providers, and First Nations patients from 2019 to 2022, during which we reviewed the quantitative results of the cohort study and asked participants to comment on them. We descriptively categorized qualitative data related to reasons that First Nations patients leave care.

RESULTS

Our quantitative analysis included 11 686 287 emergency department visits, of which 1 099 424 (9.4%) were by First Nations patients. Visits by First Nations patients were more likely to end with them leaving without being seen or against medical advice than those by non-First Nations patients (odds ratio 1.96, 95% confidence interval 1.94-1.98). Factors such as diagnosis, visit acuity, geography, or patient demographics other than First Nations status did not explain this finding. First Nations status was associated with greater odds of leaving without being seen or against medical advice in 9 of 10 disease categories or specific diagnoses. In our qualitative analysis, 64 participants discussed First Nations patients' experiences of racism, stereotyping, communication issues, transportation barriers, long waits, and being made to wait longer than others as reasons for leaving.

INTERPRETATION

Emergency department visits by First Nations patients were more likely to end with them leaving without being seen or against medical advice than those by non-First Nations patients. As leaving early may delay needed care or interfere with continuity of care, providers and departments should work with local First Nations to develop and adopt strategies to retain First Nations patients in care.

Utilization of the Disaster Medical Assistance Team (DMAT) in an Inner-City Emergency Department During the COVID-19 Pandemic

OBJECTIVE

To evaluate the effect of the Disaster Medical Assistance Team (DMAT) in an inner-city emergency department during the coronavirus disease (COVID-19) pandemic.

METHODS

Data were abstracted from individual emergency department encounters over 6 weeks. The study compared left without being seen (LWBS) percentage, door-to-provider, and door-to-disposition times for 2 weeks before, during, and after the DMAT.

RESULTS

The LWBS percentages for the 2 weeks before and after the DMAT were 16.2% and 11.6%, respectively. The LWBS percentage during the DMAT was 8.1%. Door-to-disposition times for the 2 weeks before and after the DMAT were 7.36 hours and 8.53 hours, respectively. The door-to-disposition during the DMAT was 7.33 hours. Door-to-disposition was statistically significant during the 2 weeks of the DMAT compared to the 2 weeks after the DMAT (7.33 vs 8.53, P < 0.05) but not statistically significant when compared to the period before the DMAT (7.36 vs 7.33, P = 1.00). Door-to-provider time was the longest during the DMAT (122.5 minutes [2.04 hours]) when compared to the time frame before the DMAT (114.54 minutes [1.91 hours]) and after the DMAT (102.84 minutes [1.71 hours]).

CONCLUSION

The DMAT had the most positive impact on LWBS percentages. The DMAT showed no improvement in door-to-provider times in the study and only in door-to-disposition times when comparing the time the DMAT was present to after the DMAT departed.

Machine learning in clinical practice: Evaluation of an artificial intelligence tool after implementation

OBJECTIVE

Artificial intelligence (AI) has gradually found its way into healthcare, and its future integration into clinical practice is inevitable. In the present study, we evaluate the accuracy of a novel AI algorithm designed to predict admission based on a triage note after clinical implementation. This is the first of such studies to investigate real-time AI performance in the emergency setting.

METHODS

The novel AI algorithm that predicts admission using a triage note was translated into clinical practice and integrated within St Vincent's Hospital Melbourne's electronic emergency patient management system. The data were collected from 1 January 2021 to 17 August 2022 to evaluate the diagnostic accuracy of the AI system after implementation.

RESULTS

A total of 77 125 ED presentations were included. The live AI algorithm has a sensitivity of 73.1% (95% confidence interval 72.5-73.8), specificity of 74.3% (73.9-74.7), positive predictive value of 50% (49.6-50.4) and negative predictive value of 88.7% (88.5-89) with a total accuracy of 74% (73.7-74.3). The accuracy of the system was at the lowest for admission to psychiatric units (34%) and at the highest for gastroenterology and medical admission (84% and 80%, respectively).

CONCLUSION

Our study showed the diagnostic evaluation of a real-time AI clinical decision-support tool became less accurate than the original. Although real-time sensitivity and specificity of the AI tool was still acceptable as a decision-support tool in the ED, we propose that continuous training and evaluation of AI-enabled clinical support tools in healthcare are conducted to ensure consistent accuracy and performance to prevent inadvertent consequences.

The effect of having a physician in the triage area on the rate of patients leaving without being seen: A quality improvement initiative at King Fahad Specialist hospital

OBJECTIVES

To evaluate the effect of the presence of a physician in the triage area on the number of patients who leave without being seen (LWBS) and some of the factors affecting emergency department (ED) crowding.

METHODS

This was a pre-post study carried out at King Fahad Specialist Hospital, Dammam, Saudi Arabia. The 3-month study, consisting of 7826 patients, was split into pre-physician and post-physician periods. Variables compared across these periods were the number of LWBS patients, length of hospital stay, time to physician, and time to disposition decision. Statistical analysis was carried out using R version 4.3.0.

RESULTS

Our results showed that the presence of a triage physician significantly decreased the number of LWBS patients (p<0.001) and the time taken to encounter an ED physician (p<0.001). However, it did not have any significant impact on the length of hospital stay (p=0.5) or time to disposition decision (p=0.9).

CONCLUSION

The appointment of a triage physician has streamlined patient flow and decreased LWBS rates in the ED, demonstrating the need for more thorough research in this area.

Impact of the COVID-19 pandemic on visits to the hospital emergency service in two hospitals in Spain, from March 14, 2020 to June 21, 2020

This study will describe trends in the use of emergency departments before and after the Spanish State of Alarm, especially in pathologies not directly related to this infection. A cross-sectional study was conducted of all visits to the emergency departments in two third-level hospitals in two Spanish communities during the Spanish State of Alarm, compared with the same period of the previous year. The variables collected included the day of the week, the time of the visit, the duration of the visit, the final destination of the patients (home, admission to a conventional hospitalization ward, admission to the intensive care unit, and death), and the diagnosis at discharge according to the International Classification of Diseases 10th Revision. During the Spanish State of Alarm period, an overall decrease in care demand of 48% was observed, which reached 69.5% in pediatric emergency departments. We also saw a drop of between 20 and 30% in time-dependent pathologies (heart attack, stroke, sepsis, poisoning). The decrease in overall attendance in the emergency departments and absence of serious pathologies, such as time-dependent diseases, observed during the Spanish State of Alarm compared to the previous year highlights the need to strengthen the messages addressed to the population to encourage them to seek care without delay in case of alarming symptoms and reduce the high morbidity and mortality rate if the diagnosis is delayed.

Characteristics of First Nations patients who take their own leave from an inner-city emergency department, 2016-2020

OBJECTIVE

Using a strength-based framework, we aimed to describe and compare First Nations patients who completed care in an ED to those who took their own leave.

METHODS

Routinely collected adult patient data from a metropolitan ED collected over a 5-year period were analysed.

RESULTS

A total of 6446 presentations of First Nations patients occurred from 2016 to 2020, constituting 3% of ED presentations. Of these, 5589 (87%) patients waited to be seen and 857 (13%) took their own leave. Among patients who took their own leave, 624 (73%) left not seen and 233 (27%) left at own risk after starting treatment. Patients who were assigned a triage category of 4-5 were significantly more likely to take their own leave (adjusted odds ratio [OR] 3.17, 95% confidence interval [CI] 2.67-3.77, P < 0.001). Patients were significantly less likely to take their own leave if they were >60 years (adjusted OR 0.69, 95% CI 1.01-1.36, P = 0.014) and had private health insurance (adjusted OR 0.61, 95% CI 0.45-0.84, P < 0.001). Patients were more likely to leave if they were women (adjusted OR 1.17, 95% CI 1.01-1.36, P = 0.04), had an unknown housing status (adjusted OR 1.76, 95% CI 1.44-2.15, P < 0.001), were homeless (adjusted OR 1.50, 95% CI 1.22-1.93, P < 0.001) or had a safety alert (adjusted OR 1.60, 95% CI 1.35-1.90, P < 0.001).

CONCLUSION

A lower triage category is a strong predictor of First Nations patients taking their own leave. It has been documented that First Nations patients are under-triaged. One proposed intervention in the metropolitan setting is to introduce practices which expediate the care of First Nations patients. Further qualitative studies with First Nations patients should be undertaken to determine successful approaches to create equitable access to emergency healthcare for this population.

A new approach for emergency department performance positioning: The quality-efficiency matrix

BACKGROUND

The crowding of emergency departments (EDs) is one of the major poor-quality factors for patients. Because of this, measuring ED performance in Healthcare Systems is a difficult but an important task needed to enhance quality and efficiency.

PURPOSE

(i) Development of a tool to observe and evaluate performance measurement, analysing two critical variables (quality and efficiency), verifying the change in performance due to the implementation of a new organizational model; (ii) the implementation of the tool in two EDs with comparable annual volumes of activity in the Italian context.

METHODS

A literature review on ED performance was conducted in order to identify acknowledged performance measurements used in this context that can be used in the development of a tool for the evaluation of EDs' performance. The goal is to have a matrix that is easily understood and that shows a simple relationship between quality and efficiency. This was possible by setting up a method that translates the ED annual performance data (in this case the data related to year 2018) into a graph with benchmarking purposes, also including an actual situation (AS-IS) view as compared to a TO-BE situation (i.e., before and after an organizational change occurred).

RESULTS

Two real EDs were compared and their results depicted; they can be easily related with each other to benchmark healthcare organisations. More precisely, a comparison can be used for two main tasks: - identifying different strategic areas and observing the positioning of a health organization at any given moment in time, seeing where it stands among its competitors in a matrix; - knowing how to best allocate available resources and where to divert investment. Results show that the tool depicts the situation of EDs, with a clear indication of how performance increases or decreases in the case of AS-IS and TO-BE evaluation, and also offers a quick understanding of the benchmarked EDs' situations.

PRACTICE IMPLICATIONS

The results can be shown on a graph that summarises the performance change for the AS-IS versus TO-BE conditions. This can be a useful tool for the ED and for the hospital decision makers, as it allows for an observation of performance by analysing two critical variables: the quality and the efficiency of the service provided. The former represents customer satisfaction, which in this work is the combination of two factors (i.e., appropriateness of assigning the triage code and patient satisfaction), and the latter represents the ED's efficiency in providing emergency care. The tool also helps the organizational changes to be easily evaluated.

Patients who leave the Emergency Department without being seen. Has COVID-19 affected this phenomenon?

BACKGROUND AND AIM

Patients who present to an Emergency Department (ED) and leave without being seen by a physician represent a safety concern because they may become severely ill and experience adverse events as a result of lacking or delayed ED treatment. Prior to the COVID-19 outbreak, the increasing number of patients accessing care through the ED in Italy and throughout the world has had implications for health policies.

METHODS

A retrospective cohort study that included all ED visits from 1st January 2013 to 31st December 2018 in the Perugia University Hospital has been carried out.

RESULTS

During the 5 years investigated 26,344 out of 300,372 (8.77%) patients who attended the ED left the triage area before being seen with an average of 439 patients per month. The same phenomenon has been analysed from February to October 2020. During these 9 months there were a total of 1,824 out of 30,990 (5.88%) patients who left the ED without being seen with an average of 202 per month. The latter value is one third lower than the one related to the period investigated prior to the COVID-19 outbreak.

CONCLUSIONS

Such investigation could help to differentiate actual essential demand from non-essential demand within the ED, which could inform quality-improvement policies. Several strategies could be implemented to lower the proportion of patients who leave the department without being seen. Reorganising the activities in the ED with different paths should be implemented with the aim of reducing waiting times and in turn patients' satisfaction.

Reduction of the emergency activity, during the Covid 19 Italian lockdown, what's the lesson to learn?

The COVID 19 pandemic was declared on the 9^th of March 2020. The health crisis affected the whole world with a very high and unexpected number of infected people. The situation forced the declaration of lockdown and a worldwide health system reorganization. Surprisingly, the social distancing laws caused a reduction of urgent hospital activities not COVID 19 related. The aim of this manuscript is to analyze the reasons why fewer emergencies were described during the 2020 Italian lockdown. The Data reporting urgent Emergency Room (ER) activity, during the first three weeks of the Italian lockdown (Group 1), were analyzed and compared with the same period in 2019 (Group 2). During the study period in 2020, there was a 46,5% reduction in ER activity compared to that in 2019. Nevertheless, the hospitalization rate was higher in the 2020 then in 2019 (p<0.05). The present data showed that almost half of the basic ER activity araised from mild health problems that could be followed by territorial health services. The strengthening of territorial medical services would allow hospitals to handle critical situations more easily and to focus activity by reducing the waiting list.

Implementation of a Multifactorial Strategy Including Direct Bedding Is Associated With a Rapid and Sustained Reduction in Left Without Being Seen

Objective

Improve left without being seen (LWBS) in our high volume, tertiary care trauma center. Prior to intervention, our LWBS rate was 4.4%. Including a direct bedding strategy, we successfully reduced our LWBS to <1%.

Design and method

We utilized a retrospective before and after model. We hired a clinical documentation specialist and tracked several metrics. These included daily census, admission rates, and door to provider, door to room, average boarding, and door to disposition times. Data were collected and disseminated daily. Reports were shared at organization quality meetings. Simultaneously, we implemented the direct bedding initiative in conjunction with quick registration. To accommodate higher numbers of patients and expediate movement to care spaces, all patient spaces were clearly designated and labeled.

Results

Direct bedding began in September 2015 and our LWBS was 4.4%. One-year post-intervention, our LWBS was <2%. Within four years, it was <0.5%. The LWBS rate for each year, 2016 to 2019, was significantly lower than the control period (p < 0.01) (2015 up to September). Improvement was also seen in door-to-provider time and with patient experience scores.

Conclusion

Our multifactorial approach was associated with a profound and sustained reduction in LWBS over a short time period.

Development and validation of a scoring system for mortality prediction and application of standardized W statistics to assess the performance of emergency departments

Background

In-hospital mortality and short-term mortality are indicators that are commonly used to evaluate the outcome of emergency department (ED) treatment. Although several scoring systems and machine learning-based approaches have been suggested to grade the severity of the condition of ED patients, methods for comparing severity-adjusted mortality in general ED patients between different systems have yet to be developed. The aim of the present study was to develop a scoring system to predict mortality in ED patients using data collected at the initial evaluation and to validate the usefulness of the scoring system for comparing severity-adjusted mortality between institutions with different severity distributions.

Methods

The study was based on the registry of the National Emergency Department Information System, which is maintained by the National Emergency Medical Center of the Republic of Korea. Data from 2016 were used to construct the prediction model, and data from 2017 were used for validation. Logistic regression was used to build the mortality prediction model. Receiver operating characteristic curves were used to evaluate the performance of the prediction model. We calculated the standardized W statistic and its 95% confidence intervals using the newly developed mortality prediction model.

Results

The area under the receiver operating characteristic curve of the developed scoring system for the prediction of mortality was 0.883 (95% confidence interval [CI]: 0.882–0.884). The Ws score calculated from the 2016 dataset was 0.000 (95% CI: − 0.021 – 0.021). The Ws score calculated from the 2017 dataset was 0.049 (95% CI: 0.030–0.069).

Conclusions

The scoring system developed in the present study utilizing the parameters gathered in initial ED evaluations has acceptable performance for the prediction of in-hospital mortality. Standardized W statistics based on this scoring system can be used to compare the performance of an ED with the reference data or with the performance of other institutions.

First Nations emergency care in Alberta: descriptive results of a retrospective cohort study

Background

Worse health outcomes are consistently reported for First Nations people in Canada. Social, political and economic inequities as well as inequities in health care are major contributing factors to these health disparities. Emergency care is an important health services resource for First Nations people. First Nations partners, academic researchers, and health authority staff are collaborating to examine emergency care visit characteristics for First Nations and non-First Nations people in the province of Alberta.

Methods

We conducted a population-based retrospective cohort study examining all Alberta emergency care visits from April 1, 2012 to March 31, 2017 by linking administrative data. Patient demographics and emergency care visit characteristics for status First Nations persons in Alberta, and non-First Nations persons, are reported. Frequencies and percentages (%) describe patients and visits by categorical variables (e.g., Canadian Triage and Acuity Scale). Means, medians, standard deviations and interquartile ranges describe continuous variables (e.g., age).

Results

The dataset contains 11,686,288 emergency care visits by 3,024,491 unique persons. First Nations people make up 4% of the provincial population and 9.4% of provincial emergency visits. The population rate of emergency visits is nearly 3 times higher for First Nations persons than non-First Nations persons. First Nations women utilize emergency care more than non-First Nations women (54.2% of First Nations visits are by women compared to 50.9% of non-First Nations visits). More First Nations visits end in leaving without completing treatment (6.7% v. 3.6%).

Conclusions

Further research is needed on the impact of First Nations identity on emergency care drivers and outcomes, and on emergency care for First Nations women.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-021-06415-2.

Patients Who Leave the Emergency Department Before Treatment Completion: A Retrospective Cohort Study

BACKGROUND

Patients leaving the emergency department (ED) before treatment completion (LBTC) is a common universal occurrence. We hypothesized that the characteristics of the Israeli health care system, as well as its policy, intended to reduce the burden of nonurgent ED visits, may have an impact on factors associated with LBTC.

OBJECTIVES

The purpose of this study was to explore factors associated with LBTC in the Israeli context.

METHODS

This was a retrospective cohort study of patients who visited the ED in a major hospital located in northern-central Israel during 2016-2019. Characteristics of 130 randomly sampled LBTC patients and of 130 non-LBTC patients that constituted the control group, were compared. Odds ratios (OR) are presented.

RESULTS

A low-acuity triage score (OR 8.18, p < 0.01) and a longer length of stay (OR 1.15, p < 0.01) were found to be risk factors for LBTC, and female gender (OR 0.40, p < 0.01) was found to be a protective factor. In contrast, age and nationality were not found as risk factors. Significant differences were found between the two groups with regard to the main presenting complaint. However, both groups had similar rates of presentations with a psychiatric condition. Approximately half of the LBTC patients presented at times when primary clinics were active.

CONCLUSIONS

These findings reflect the strengths of the Israeli health care system. Despite the policy intended to reduce the burden of nonurgent ED visits, there are possible shortcomings in the system that should be addressed.

Pilot assessment of an on-demand telehealth 'left without being seen' follow-up programme

INTRODUCTION

On-demand telehealth can have a high rate of patients requesting visits and dropping off without being seen by a provider, especially during the COVID-19 pandemic.

METHODS

On-demand telehealth requests made to a large healthcare system in the USA between 15 March 2020 and 31 May 2020 were included for analysis with a focus on patients who were defined as left without being seen (LWBS). As part of a pilot program a registered nurse attempted to call LWBS patients within 24 hours of their telehealth request and asked if they were ok, if they sought care for their original visit reason, what that care was, or if they still needed guidance. This information and patient demographics were analyzed.

RESULTS

During the study period there were 21,610 completed on-demand telehealth visits and 1852 patients for whom there were LWBS attempted follow-ups. Most patients LWBS for a reason that originated from the patient and not associated with the provider or telehealth platform. The mean wait time for LWBS patients was 12.4 min compared to patients waiting 15.1 min before engaging with a provider to complete a visit. Of the 1852 total LWBS patients in the follow-up programme, 819 (44.2%) were successfully contacted with a follow-up phone call. Most of these patients (63.2%) already completed or planned to complete a telehealth visit, 13.6% indicated they no longer needed to see a provider, and 12.8% planned or already completed an in-person visit. Only 2.2% went to an emergency department.

DISCUSSION

Results suggest patients can effectively self-manage their care needs.

Characteristics of Aboriginal and Torres Strait Islander peoples attending Australian emergency departments

OBJECTIVE

Aboriginal and Torres Strait Islander patients are overrepresented in Australian EDs. The present study aimed to assess their characteristics in utilising ED services at a national level.

METHODS

This exploratory, quantitative study used 2016-2017 de-identified data from the National Non-admitted Patient Emergency Department Care Database to assess the proportions (with 95% confidence interval) of Indigenous and non-Indigenous Australians across various aspects of ED presentations, including mode of arrival, triage scale, diagnosis information, episode end status and ED length of stay. Episode level ED data were compared by Indigenous status and geographical remoteness of EDs.

RESULTS

Of 7.4 million presentations, 6.58% were Indigenous presentations, with over two-thirds occurring in regional and remote EDs. Indigenous patients were more likely than non-Indigenous patients to arrive to EDs by ambulance and police/correctional services vehicle across all remoteness areas. Additionally, they were more likely to present with respiratory system illness, illness of the skin/subcutaneous tissue/breast and mental/behavioural disorders. Indigenous Australians were more likely to leave EDs before being seen or care complete (odds ratio 1.73, 95% confidence interval 1.71-1.74), and this was observed for patients classified across all levels of triage scale.

CONCLUSIONS

This is the first national study looking at the characteristics of and reasons for presenting to Australian EDs for Indigenous and non-Indigenous patients. Our findings provide important insight into the potential factors affecting Indigenous patient care, and an impetus for ongoing research and advocacy work to improve the quality of emergency care provided to Indigenous Australians.

Implementation and validation of a new method to model voluntary departures from emergency departments. Running Title: Modeling Voluntary departures from emergency departments

In the literature, several organizational solutions have been proposed for determining the probability of voluntary patient discharge from the emergency department. Here, the issue of self-discharge is analyzed by Markov theory-based modeling, an innovative approach diffusely applied in the healthcare field in recent years. The aim of this work is to propose a new method for calculating the rate of voluntary discharge by defining a generic model to describe the process of first aid using a "behavioral" Markov chain model, a new approach that takes into account the satisfaction of the patient. The proposed model is then implemented in MATLAB and validated with a real case study from the hospital "A. Cardarelli" of Naples. It is found that most of the risk of self-discharge occurs during the wait time before the patient is seen and during the wait time for the final report; usually, once the analysis is requested, the patient, although not very satisfied, is willing to wait longer for the results. The model allows the description of the first aid process from the perspective of the patient. The presented model is generic and can be adapted to each hospital facility by changing only the transition probabilities between states.