Emergency room overcrowding occurs when the demand for critical emergency care exceeds supply and poses a serious threat to safe patient care.

here Dr. Colin Dewar, Specialist in emergency medicine at University Hospitals Sussex NHS Trust, breaks down the main causes along with possible solutions.

What are the top causes of emergency room overcrowding (ED)?
Each emergency room is unique and crowding is a complex problem, but there is a helpful framework to categorize the three overarching causes of crowding.

First, as the population increases, so does the number of visitors to the ED. This rush has also been fueled by public health campaigns that focus on time-sensitive conditions such as heart attacks. In the UK, we have also seen a significant increase in ED visits after COVID. Input causes for ED crowing are therefore largely socio-economic.

There are then causes of crowding that are found once a patient has entered the emergency room. Bottlenecks arise from the fact that plants are often not equipped for the increased demand due to insufficient staffing or spatial arrangement. Many other factors can reduce patient flow resulting in overcrowding, e.g. other patients.

Finally, a reduced output of the ED can lead to overfill; this is more commonly referred to as the “exit block”. A shortage of inpatient beds in relation to demand can lead to a longer stay of the admitted patients in the emergency room. The exit block is often seen as the main contributing factor. Because of this, ED crowing is a hospital-wide problem and this must be taken into account when attempting to resolve it.

How does this affect patient care?
Overcrowding in the emergency room is the greatest threat to safe patient care in acute situations in industrialized countries. It affects patient care in terms of the quality of care they receive and this naturally affects patient outcomes.

ED crowing has been shown to be associated with higher staff workloads, delayed patient assessment, higher treatment costs, more frequent discharges of patients with high-risk clinical characteristics, poor infection prevention and control measures, and lower patient satisfaction, all of which are also associated with the likelihood of increasing reduce the patient’s compliance with their follow-up care plan.

This leads to lower patient outcomes, particularly in the form of high readmission rates, extended hospital stays, increased work stoppages, a higher frequency of medication errors and adverse events, and increased morbidity and mortality.

It is demoralizing for employees because they cannot provide the level of care they want when emergency rooms are constantly operated with needs that exceed both physical and human resources and capacities.

How has the pandemic affected this problem?
During the pandemic, attempts were made to keep patients out of the hospital whenever possible. This lowered admission rates for ED, but as the world normalized a bit there has been a significant spike in UK ED participation in the post-pandemic period and the challenge has come again.

The overcrowding has been compounded by the need to give patients adequate space to ensure safe care in the context of the pandemic.

It has shown the need for solutions that can be implemented in the short to medium term, as demand will only continue to increase, as it has in the last 20 years. And the main pressures that ED faces is the need for ED leaders to be actively involved in developing solutions to crowding. Emergency room corridors crowded with patients on carts and chairs should not be an accepted part of 21st century healthcare.

Where, if at all, is this problem currently being technically addressed?
While the implications for patient care are well known, previous solutions have been patchy and inconsistent.
In terms of technology, tools that allow superficial measurements of crowding to aid decision-making are such as: NEDOCS and ICMED For example, scores are available to emergency medicine executives, although their limitations and inadequacies are widely recognized.

Otherwise, the initiatives tend to focus on improving access to primary care and general practitioners as well as on alternative care models. All of them have their shortcomings. The Royal College of Emergency Medicine has consistently argued that the proportion of patients with poor visual acuity (who could be treated in alternative health care facilities) does not exceed 15% clinics or the increasing access to these clinics is likely to be limited.

Britain has also introduced goals such as all ED patients must be treated within 4 hours. This has increased the resources available for emergency doctors, but has not been able to keep up with the increasing demand from year to year.

Overall, this is an area where technological innovations need to be explored.

Can artificial intelligence and machine learning (AI / ML) help solve the problem?
I believe that only large data sets with AI / ML technology applied will be able to unlock the proactive modeling needed to tackle the overcrowding problem. KI / ML offers the promise of transforming the provision of acute services from the current reactive system to a proactive model.

To do this, we need a testable predictive tool for both emergency room needs and inpatient admission. This would be the first step in building a system that optimizes the resources available to meet the expected pressures, with a consequent reduction in ED crowding and the damage it causes.
Such a solution would transform care in emergency rooms and go a long way in ensuring safe and timely patient care while minimizing clinician burnout.

What role will technology play in this area in the future?
In the future, I see the advent of really advanced digital health technologies will also play a role in providing extremely rich, previously inaccessible information about patients’ physiological health (vital signs, etc.) in real time, as well as their exact location in the hospital. This could one day also supply ML-driven crowding models with this type of data, which could permanently change our understanding of what constitutes high-quality hospital care management.

ED crowding is therefore an issue in the healthcare landscape where the urgent need for change meets enormous potential for innovation. Therefore, now is the time to form an international consortium to capitalize on this convergence.

You work with electronRx, what are you doing in this area?
ElectronRx is a deep tech startup based in Cambridge, United Kingdom. They have an expert team of interdisciplinary scientists and engineers who develop a range of novel technologies to revolutionize patient engagement and support clinical decision-making, and take a consistently data-driven approach to the way we deliver health care and treatment of diseases to improve, to change.

With electronRx we are building an international consortium of emergency medicine executives who all work together passionately to overcome the long-standing, internationally recognized obstacle to high-quality patient care, ED crowding.

Our project aims to use their AI / ML skills to extract the value that lies dormant in a plethora of previously inaccessible healthcare insights across the hospital. Our goal is to create a holistic, AI-driven solution that delivers actionable insights with measurable results to fight ED crowing once and for all.