Description and Analysis of Emergency Department Demands, Constraints and Consequences

Emergency medicine has developed rapidly over the last 50 years with notable successes in developing purpose-built units, training programmes and postgraduate examinations with consequent improvements in the morbidity and mortality outcomes for millions of patients.

However, these departments, systems and processes have developed in a rather piecemeal manner; seldom have single departments, let alone whole systems been built, resourced and managed in an optimal manner. For the few that have, the inevitable increase in attendances and admissions plus advancements in medical science have ensured that even they have become increasingly challenged.

Comparison of the emergency care systems of various countries have been published and the conclusions disseminated widely. Hence it is recognised that the system of emergency care in North America, Australasia, the UK and Ireland is substantially different from that in many mainland European countries. Such comparisons are of value but seldom lead to system changes.   

Surprisingly we are often blind to the significant differences within our own systems. In England there are over 180 Emergency Departments operating within 130 hospitals or groups. The scope to better analyse variation between these departments is considerable, yet until recently has not been systematically undertaken. Moreover, such analysis can illuminate key constraints and opportunities, which are more likely to resonate with patients and staff than international comparisons. Such intra-system variations are also more likely to drive improvements by highlighting unwarranted variation. 

In determining how best to use metrics to analyse performance of emergency departments and illuminate comparisons it is essential to avoiding both simplistic reduction and meaningless complexity. 

Work undertaken by a number of national bodies in England has identified over 1,000 potential metrics of which 40 appear to be the most discriminatory. For the purposes of this article these metrics are subdivided into four key domains; Demand, Capacity, Flow and Outcomes. Importantly this is not a standardisation methodology. Indeed, inherent in the analysis is a recognition that often there are good reasons for variations in both demand and outcomes. 

ED Demand 

To properly appreciate the performance of an emergency department (ED) it is essential to recognise the variation of demand between ‘apparently’ similar departments. Four metrics in particular are edifying. 

a. Attendance rate 

b. Proportion of attendances over 75 years 

c. Deprivation profile of attendances 

d. Conversion rate of attendances to admissions 

Whilst these are not independent variables they are sufficiently discriminatory for our purpose. 

From our data we now know that the attendance rate varies from 16 to 42 per cent of the catchment population per year. This reflects both geographical challenges e.g. distance travelled as well as the availability (or otherwise) of other urgent care services e.g. primary care and treatment centres. 

The proportion of patients attending who are aged over 75 varies from 16 to 43 per cent. For many, but not all hospitals, the need to reflect this case load by providing frailty and geriatric services is self-evident yet the data shows the provision of such services is patchy and not obviously aligned always with demand. 

Deprivation levels (as measured by the proportion of the catchment population that are in the 20 per cent of the population that is most deprived) varies from less than one per cent to almost 80 per cent. Both the nature of illness/injury and the linkages to social care/public health that are determined by such variation are also self-evident. 

Finally, the proportion of attendances to an ED that require an admission varies from 13 to 44 per cent. This will require fundamentally different resource configurations both of estate and manpower to effectively manage such variation. 

Thus, by examining only four variables we are already much better informed of the range of challenges each ED must face. If we are to have a debate around ED performance, we must recognise the very different demands placed upon them even within a single country, region or even city. 

ED Capacity

Whereas ED demand is largely without the control of the department or its associated hospital, ED capacity is most obviously not. It is this issue that demonstrates such a high degree of unwarranted variation ie; variation for which there can be no proportionate justification. 

Data shows that in England, on average, 1,250 admitted patients must be accommodated for every emergency department majors/ resuscitation bay. As such, each of these clinical spaces must manage between three and four admitted patients per day and depending on the conversion rate at least twice as many non-admitted patients also. Simple arithmetic shows that in order to accommodate these patients the average ‘time in bay’ must be less than three hours. 

Remarkably however these numbers and calculations apply only to the statistical mean. Half of all departments will have to manage more patients per bay and in some cases twice as many! 

Some departments are simply too physically small to be fit for purpose.

Flow, Exit Block and Implicit Harms

Flow is key to ED performance. The timely assessment, treatment and disposition of each patient is important to both the patient and the healthcare system. Delays and bottlenecks impair experience and outcomes, yet are seen all too often in many EDs in most healthcare systems. 

The Four Hour Standard was introduced in the UK in 2004 specifically to provide a key driver to timely flow in the ED. It has achieved notable success and without such a metric, performance and outcomes in the ED would be much worse. 

However, two valid criticisms of the Four Hour Standard are of genuine concern. Firstly, it applies to all patients including those with minor illness and injury. This can paradoxically encourage systems to ensure large numbers of patients with minor conditions are managed quickly to offset delays for fewer, more seriously ill patients. Secondly, the standard is binary, anything under 240 mins is a success and over is a failure. 

The first criticism is most easily dealt with by referencing the Admitted Patient Breach Rate (APBR) separately — this records the proportion of patients who require admission that breach the Four Hour Standard. As such it refocuses attention on the more seriously ill and injured. 

Avoiding the binary nature of the Four Hour Stand is also relatively straightforward using a derived metric — the Aggregated Patient Delay (APD). 

This metric summates the accumulated delay beyond four hours from time of arrival for all ED patients requiring admission. It is then expressed as ‘hours delay per hundred admitted patients’. A worked example of how this would apply to three different EDs highlights how this metric extends the clinical relevance of any ED time standard (Fig.1). 

However, these new metrics are most powerful when plotted as a function of each other. Charting the Admitted Patient Breach Rate vs Aggregated Patient Delay for each ED in England produces a visual and contextual insight into the flow delays experienced by patients. 

Those patients attending hospitals whose performance is plotted within the top right quadrant are evidently at much greater risk of delay-associated morbidity and mortality than those in the bottom left quadrant. Importantly these metrics are not binary but continuous variables. They resonate with clinicians and managers because they reflect the ‘lived-experience’ of both staff and patients. Because there is no cut-off threshold every patient counts; as does every hour of delay. Every system can credibly aspire to improve both their relative and absolute position on the APD/APBR chart. 

Numerous studies from North America, Australasia and the UK have shown morbidity and mortality consequences of overcrowding in the ED and Exit Block related delays. Hitherto we have lacked a methodology to differentiate performance of various EDs and hospitals in a manner that was reliably proportionate to these harms. This methodology, focusing on patients requiring admission, directly addresses this deficit and importantly can also be applied to any ED in any country. 

The use of nationally and locally collected data can provide valuable insights into the demand and capacity profiles of an emergency department. Such data when systematically analysed using clinically referenced benchmarks can better inform redesign, reconfiguration and investment decisions.

Figure 1

However, these new metrics are most powerful when plotted as a function of each other. Charting the Admitted Patient Breach Rate vs Aggregated Patient Delay for each ED in England produces a visual and contextual insight into the flow delays experienced by patients.

Those patients attending hospitals whose performance is plotted within the top right quadrant are evidently at much greater risk of delay-associated morbidity and mortality than those in the bottom left quadrant.

Importantly these metrics are not binary but continuous variables. They resonate with clinicians and managers because they reflect the ‘lived-experience’ of both staff and patients. Because there is no cut-off threshold every patient counts; as does every hour of delay. Every system can credibly aspire to improve both their relative and absolute position on the APD/APBR chart.

Numerous studies from North America, Australasia and the UK have shown morbidity and mortality consequences of overcrowding in the ED and Exit Block related delays. Hitherto we have lacked a methodology to differentiate performance of various EDs and hospitals in a manner that was reliably proportionate to these harms. This methodology, focusing on patients requiring admission, directly addresses this deficit and importantly can also be applied to any ED in any country.

The use of nationally and locally collected data can provide valuable insights into the demand and capacity profiles of an emergency department. Such data when systematically analysed using clinically referenced benchmarks can better inform redesign, reconfiguration and investment decisions.