The Study of Emergency Room Overcrowding, Lengthy Wait Times, and the Effect on Patients

Definition of Terms

Emergency department. Medical facility focused on the treatment of acute medical or trauma-related emergencies. The ED is generally based within a centrally located hospital environment or other health care facility, and patients are granted the freedom to arrive independently or through the utilization of an emergency medical service such as an ambulance. All conditions, no matter the severity, are at least accepted into the facility for treatment or diversion to specialized facilities. The broad range of issues that present within the ED require medical personnel with a broad range of medical expertise.

Patient flow. In this context patient flow refers to the movement of patients into and out of an ED, and is similar to product streams in industrial production facilities. The specifics of patient flow into and out of an ED, of course, differ in large ways and the build-up of patients prior to entrance into the ED can be attributed downstream patient flow issues such as low admittance availability, low staffing, and case complexity.

The customers’ voice. In the US healthcare system, it is a responsibility of ED’s to treat acute emergencies to the best of their ability. The customer’s voice is embodied in this duty, as the situations ED patients present in preclude a true ability to express their personal rights.

Overcrowding. The influx of patients to an ED coupled to a decreased patient flow. Patient flow may be affected by downstream issues such as low admittance availability, low staffing, and case complexity. Overcrowding in this context is directly correlated to increased ED patient wait times which is assumed to be inversely proportional to the patient’s health.

Waiting times. The amount of time spent in a pre-care situation prior to entrance into ED treatment.

Synergy effect. The positive effect on production streams, in this case, patient flow, as a result of increasing communication between working units and decreasing waste.

Mixed-methodology research. The application of research findings, theoretical frameworks, and anecdotes across a variety of platforms and subjects in order to focus research questions on one specific variable or field of study.

Variables. Individual units of interest within a research consideration. Variables may be present or absent, changing or immoveable, authentic or inferred.

Acuteness. A measure of objective timeliness in which the presence of some activity or state is of immediate concern. In this context, acuteness refers to medical or trauma-related emergencies within patients in an ED.

Performance Measurement. Scales and grades of output by working units within an ED, independent or dependent on patient flow.

Plan-Do-Study-Act (PDSA) process. The progression of the implementation of quality management tools as they relate to healthcare systems and specifically ED’s.

Staff resistance. The inability to accept quality management changes in the processes and structures of an ED. In this context, it is a result of the complex requirements already placed on ED staff, and an assumption of the study places the burden of staff resistance on top-down leadership within a quality management focus.

Service quality. The measurement of ED perception by ED patients that encompasses waiting time, treatment, level of care, and subjective standards of expectation.

Significance of the Study

It has widely been accepted that the growing trend of increased waiting times in Emergency Departments (ED) throughout developed countries is derogatory to both patients and healthcare systems alike. What is not accepted, however, is the proper mechanisms that should be applied to ED’s across the United States of America (US). In a 2014 report by the American College of Emergency Physicians (ACEP), ED’s across the country were given a dismal rating with a primary concern for ED crowding and the build-up of patients waiting to be admitted to the hospital. The state of Michigan received one of the lowest positions, ranking 46 of the 50 US states (Hirshon et al., 2013). The National Quality Forum, a US-based medical forum, couples yearly rates of patients who leave an ED without being seen to the length of total stays within an ED to consider a true measure of quality and efficiency (Guttman, Schull, Vermeulen, & Sturkel, 2011). There are gaps in the understanding of those measures, however, and the significance of this study rests in its focus on identifying quality management tools to implement within ED’s in order to decrease the gaps of knowledge.

In order to determine the ability of this study to identify quality management tools that should be implemented it is necessary to understand the current state of ED’s in the US. Hirshon et al. (2014) cite 4% of US doctors comprise the working force of US ED’s while handling approximately 28% of acute care cases. Compounding this is the 11% drop in ED’s between 1995 and 2010, and a continued trend of an increased patient volume seeking primary care services (Hirshon et al., 2014). Such a decrease in the number of ED’s means a significant increase in the expectations and workloads of functional ED’s.

The demographics of an ED’s service area play into the reasons for the growing waiting line. In Illinois hospitals, it was found that larger ED’s had longer wait times. The ten Illinois ED’s with the longest wait times were some of the largest, and they were based in the dense urban population of Chicago (Wang, 2013). The ten Illinois ED’s with the shortest waiting times were located in wealthier suburban areas, which balanced the Illinois average ED waiting time to 260 minutes, slightly below the 274-minute national average (Wang, 2013). This is not a great surprise. Wealthier areas tend to support less dense populations, higher tax revenue, and the insurance-provision of more expensive private hospitals. Within Chicago, the “safety net” and educational hospitals had the largest ED’s and the longest waiting times. The University of Chicago Medical Center, the University of Illinois Hospital, the Northwestern Memorial Hospital, and a host of Cook County Health and Hospital System locations posted waiting times of over 6.5 hours (Wang, 2013). While it is easy to understand the economic demographics at play with these raw numbers, it is not easy to understand why health systems in such close proximity can have such widely varying waiting times.

Recent debates in this country centered on access to health insurance may speak to the discrepancies seen between suburban and urban Chicago. As previously detailed in the ACEP report, 4% of US doctors are handling a growing majority of primary care issues. Their report also states that this 4% handles nearly 66.7% of uninsured patients who seek treatment, warning “as more Americans become insured under the Affordable Care Act, many for the first time, Emergency Departments are likely to play a more pivotal role and to become more stressed” (Hirshon et al., 2014, p. 16). So, not only is the load of uninsured patients stacking up within ED’s for the primary care they need, ED’s will remain their main primary care option when they receive federally-subsidized insurance.

Even with Accountable Care Organizations, ED primary care as a last resort is a common practice in densely populated and largely poor urban areas. Houston, a city with the highest proportion of uninsured patients in the nation and thus the city with the highest number of uninsured primary care cases within ED’s, has a growing problem that long ED waiting times indicate. A recent study suggested that demographic categories like race, geographic location, and economic circumstances are the underlying problem, and insurance status is just one aspect (Begley, Behan, & Seo, 2010). The main issue in Houston, indicated by the rising ED waiting times, is a lack of access to primary care facilities. Indeed, primary care-related ED use by Houston’s uninsured residents was found to be much lower in geographic areas that were saturated with primary care facilities (Begley et al., 2010). Either way, ED’s in Houston have become the go-to location for primary care, a problem that will be compounded with the Affordable Care Act which will grant millions of Americans a reprieve from the issues of being uninsured but will keep them in their usual spot; waiting in line at the ED.

Quality management and quality assurance within ED’s have shown a strong correlation to an increased level of healthcare delivery and a decreased amount of time patients spend waiting for treatment. Quality management, however, is a process. It must take place over time with a number of industry-specific considerations. The principles of quality management were first applied to industrial assembly line processes, and thus its application to ED’s will garner a different approach. The ED is a staple of developed countries’ healthcare systems, with the provision of high-quality acute care a seemingly inherent right (Francis, Spies, & Kerner, 2008). While the semantics of humanism can be debatable, the core values of ED’s in the US affirm this right with a focus on ensuring positive outcomes in cases of acute emergencies. The need to decrease waiting times may seem secondary to those core values, but growing evidence supports decreasing the waiting line. Providing assurance on the status of acute emergencies is more than simply a nice gesture, it can impact the healing process (Oberklaid, Barnett, Jarman, & Sewell, 1991).

The complexities of the ED make the identification of specific quality management parameters difficult, and the significance of studies like this lies in the definition of those parameters. Decreasing ED waiting times is beneficial, but it must not come at the cost of decreasing some other valuable standard of care. The strength of applying quality management practices to ED’s is threefold. First, it offers a strong system of management by which organized groups of team members can rely on. Second, it offers a clerical system by which efficiencies can be plotted, understood, or scrapped. Third, it measures the allocation of resources which will continue to be a major rate-limiting step in the progression of quality management. Oberklaid et al. (1991) cite three quality assurance developments within ED’s that will decrease waiting times and increase the quality of emergency care: structural approaches such as practitioner educational training, evaluations of outcomes in health delivery, and documenting the process of delivering healthcare to assess outcomes. Identifying such parameters is a necessary component in the effort to decrease the time spent waiting in the ED line.

While it is necessary to implement quality management parameters, they cannot be set in place without a firm understanding of the factors affecting care provision in the complex environment of the ED. It is generally understood that as patient volume increases so too does the workload for front line staff like physicians, nurses, physician assistants, technicians, respiratory aids, and other supplementary staff. The uneven character of the workload compounds care provision. These front line staff must have the technical expertise to handle flu-like respiratory symptoms in a two-month-old infant, a cardiac arrest in a seventy-five-year-old woman, and a compound fracture in a young teenager. Such a broad array of cases requires a ubiquitous top-down focus on efficiency as new tasks generally decrease productivity. This issue is further compounded when inexperienced or junior members are the primary staff, or when experienced staff is stretched beyond their capable limits (Oberklaid et al., 1991). ED’s must remain open at all hours and in all conditions, and thus any changes in staffing are likely to result in significant changes in the expectations of care provision.

Streamlining the process of ED care is difficult, but quality management techniques have been shown to do just that. In an assessment of changes implemented within their ED, Goralnick, Walls, and Kosowsky (2013) made an analogy to the Toyota Production System’s Andon Cord. The Andon Cord is a quality-control method used by Toyota to identify problems with the production stream so that analysts, managers, and production line workers alike can focus efforts on solving the problem. Any team member can notify another of a process problem, and management can act more efficiently to quell the issue. Prior to implementing the Andon Cord-like streamlined ED process, Goralnick et al. (2013) revealed a 65 minute wait time with patient satisfaction resting between the 6th and 40th percentiles. Within five years they were able to decrease the wait time to 22 minutes, and patient satisfaction rested between the 90th and 99th percentiles despite 50% staffing numbers (Goralnick et al., 2013). The approach they took to decrease ED waiting time and increase patient satisfaction included identifying important key stakeholders in care provision and tasking them with an immovable and high bar for success. Analysts worked with staff subdivided into pods to conduct live walkthroughs, change pathways to service provision, and adopt a strategy of placing any patient in any bed when space permitted (Goralnick et al., 2013). This process of quality management streamlined the process of ED service provision and significantly decreased the ED waiting times.

Such streamlining measures are the focus of lean production techniques. Lean production techniques focus on decreasing waste while products “flow smoothly, continuously, and without errors from one step to another” (Holden, 2011, p. 265). In the ED the products are the patients, and the elimination of waste is directly correlated to a maximal value to the patients. Holden (2011) identified other principles of lean production techniques that could be applied within ED’s including a decrease in the production (patient care) stream, decrease in the stock inventories, worker empowerment, immediate identification of problems, solving such problems at their source in an effort to decrease multiplicity, and continuous improvement (p. 266). In ED’s these factors will take on different identities, however, it is important to detail common applications of lean production techniques. Specific changes to ED processes can include an increased speed of assessment by physicians and nurse by using a more standardized charting technique, eliminating policies that are outdated, combining steps within the process of care provision, admissions of patients to any area of the hospital that has capacity, and a more standardized medication storage and labeling process. ED systems can also undergo changes. Goralnick et al. (2013) found that despite their incredible decrease in ED waiting time, the primary bottleneck that maintained any waiting time at all was the initial triage process. They were able to identify this by compiling accurate data for benchmarking within units of their ED. Other system changes that can be implemented include better educational training when time permits, better communication tools, better teamwork throughout departments, and certain specialties assigned to match peak patient volumes (Holden, 2011).

Quality management is an important factor, but gaps in the understanding of its application exist. An understanding of risk within the ED is a primary component of proper quality management and a major factor in decreasing resource losses. The ED is a complex and dangerous environment. The stressors of the work, coupled to the time requirements, affect ED physicians in terms of malpractice. Risk committees can be formed to provide structure to physicians who do not specialize in the litigation process of malpractice. Other factors aid in such risk committees or risk analysts in decreasing the overall burden of risk. Well documented charts, better orientation for new and junior physicians, and increased standards of group participation not only increase the quality of the professional environment, but such measures can have extraordinary effects on the quality of healthcare provision (ACEP Medical Legal Committee, 2011).

Benchmarking, the process of creating comparative analysis between similar organizations or units within an organization, is also an important factor in decreasing the gaps of knowledge as they apply to decreasing the waiting times of ED patients. Francis et al. (2008) cite the use of disease-specific markers as a valuable measure of effective ED care. Benchmarks must target better quality in terms of reducing errors and streamlining medical procedures. The core values of quality assurance include supervision, interdisciplinary communication, and individual self-control mechanisms (Francis et al., 2008). These core values should remain a top priority for analysts, supervisors, and team members at all times. A cohort study from Ontario showed why these factors of quality assurance should remain a top priority. Patients presenting with acute emergencies during periods of long waiting times were much more likely to leave without being seen and had an increased risk of death for up to seven days following ED presentation (Guttmann et al., 2011). So too, patients who were seen during the same time and were discharged showed similar susceptibility to medical risk and death (Guttmann et al, 2011). This reveals that a singular focus on decreasing ED waiting times can be harmful if other quality management techniques are not considered.

The increasing burden of primary care provision in ED’s in the US is a growing problem, and the changing landscape of the US healthcare system will likely produce more gaps in knowledge. In their 2014 report on the current state of ED’s in the US, Hirshon et al. (2014) underlined the importance of understanding and preparing for the effects of the Affordable Care Act. While the Affordable Care Act will provide a cheaper option for health insurance for millions of Americans, it is likely that the ED will remain the first option for primary care-related issues. In order to combat this potential problem, Hirshon et al. (2014) provide recommendations for ED’s across the US. Supporting programs that facilitate a quicker transition to more focused and pertinent care are likely to benefit ED waiting times. This will likely mean the lobbying for increased primary care facilities linked to ED’s or linked to geographic locations that show large ED burdens. Hirshon et al. (2014) also state that more time should be devoted to funding disaster preparedness programs, increase investment in information technologies, increase funding for graduate medical education programs that focus specifically on emergency care, and the implementation of better drug monitoring systems.

It is evident that quality management tools like streamlining patient care, increasing the quality of orientation and educational practices, and focusing resources more efficiently will decrease ED waiting times. Dr. Elaine Rabin of the Mount Sinai School of Medicine agrees but sees limitations. “We do a pretty good job of focusing the resources on the sickest people, but there’s only so far that can go,” she says (Wang, 2013, p. 1). The significance of studies like this rests in identifying how far the efforts of Dr. Rabin and other ED practitioners can go by highlighting important gaps in knowledge and quality management practices.

Assumptions and Limitations

The assumptions of this study are largely shared by the literature previously discussed. Increased waiting times in ED’s throughout the US have a derogatory effect on the healthcare system as a whole and on individual patient health. While there does exist some debate over the applicability of rights and responsibilities of governing bodies to provide, at face-value, high-quality emergency care for its citizens, it is a self-evident truth that healthcare practitioners are tasked with providing the highest quality care they can provide. It is an assumption of this study that such providers benefit from decreasing ED waiting times. This will play into the quality management tools explored. The streamlining of patient care techniques and processes benefits from a decreased burden elsewhere in the system. It is an assumption that quality management tools can be applied to the US healthcare system.

The limitations of this study are defined by a number of geographic, economic, and situational parameters. In regards to the US healthcare system, recent changes to the accessibility of health insurance stated in the Affordable Care Act will increase the number of American citizens who have health insurance. It has been debated whether or not the high number of uninsured citizens is a primary factor in the lengthy ED waiting times in the US healthcare system, and changes implemented by the Affordable Care Act may produce significant changes in the practical applications of findings of this study (Begley et al., 2010). Another limitation rests in the application of quality management tools within a healthcare setting. A number of studies have shown improvements to ED waiting times, however, sample sizes are low and claims are largely subjective in nature (Goralnick et al., 2013).

Scope of the Study

The extent of this study rests on the identification of trends, factors, and specific measurements of ED overcrowding and excessive waiting times. The general hypothesis states that the persistent problem of ED overcrowding and excessive waiting times will affect the quality of care for the patients and by the practitioners. Qualitative and quantitative measures will be explored in order to identify gaps in the knowledge of literature devoted to measuring the effects of increased waiting time in ED’s throughout the US.

Qualitative measures will rely heavily on the assumptions previously stated and explored in past literature. Identification of gaps in knowledge within that literature is an important aspect of defining what qualitative measures matter. It is widely accepted that increased waiting times are derogatory to both health care systems and the patients they serve. What is not accepted are the specific measures that should be put in place to combat the problem. The implementation of quality management strategies has shown practical application, but they remain largely theoretical strategies that many ED staff refuses to accept as tactile practices for increasing hospital care.

Quantitative measures will rely on the development of an overcrowding and lengthy wait time measure for retrospective ED data. Such a measure will provide a better quantification of the effect that ED waiting time has on the health of patients. In their look at Ontario, Canada ED’s, Guttman et al. (2011) found that while ED waiting time affects patient health in a negative way, so too does speedy discharge from the ED. A measure of the effect of waiting times on the outcome of a patient’s care may speak to gaps in the knowledge of studies like this.

Theoretical Framework

The primary area of interest is the quality management of healthcare systems, specifically the ED’s within the US healthcare system. The specific area of interest is the ED waiting room, and the parameters that affect its overcrowding and the subsequent waiting time for patients experiencing acute health emergencies. An objective assumption can be made in acute emergency situations that a patient’s health will be inversely proportionate to the amount of time the patient waits to receive medical care. Numerous studies have shown correlations between increased waiting time and decreased care, but it is also known that overcrowded US ED’s are filled with patients who require treatments and therapies linked to primary care (Begley et al., 2010).

The primary research questions revolve around the broad effects of increased waiting room times on healthcare systems, and specifically within the ED itself. If increased ED overcrowding and increased ED waiting times negatively affects the health of patients experiencing an acute medical emergency, it is an assumption of this study that the ED as a whole will be negatively affected. The primary research questions of this study will investigate the problems that arise when such a burden occurs, but they will not focus on the specific properties of the medical emergencies discussed.

It is not known how the Affordable Care Act and the increased number of American citizens with health insurance will affect ED waiting times. It is also unknown whether or not ED staff can effectively implement quality management measures, but many studies have shown the applicability of lean production techniques and quality management measures to healthcare settings (Holden, 2011). The purpose of this study is to explore the applicability of those measures to ED’s, and whether or not they will affect the rising length of waiting time ED patients experiences.

Short Summary

Long ED waiting times are inversely proportional to the health of patients experiencing acute medical emergencies. The makeup of ED waiting rooms expands numerous demographic definitions, but it is evident that densely populated urban areas experience significantly longer ED waiting times, and large ED’s experience longer waiting times. One major issue affecting the overcrowding of ED’s within the US healthcare system includes a lack of accessible and affordable primary care facilities. It is evident that a small fraction of US medical doctors practices emergency medicine, all the while carrying the burden of the large majority of uninsured patients and patients in need of primary care services.

The application of quality management tools to healthcare settings has shown positive gains, and there is room to explore whether these tools can decrease ED waiting times. Some limitations exist in that the complex requirements asked of ED staff preclude their ability to apply ongoing quality control measures. Studies are cited that have shown success, however, they are subjective and isolated. The success of quality management within the ED may, then, be reliant on top-down leadership focused on structural changes instead of process changes. Such structural changes may include a better drug organization and tracking mechanism, a more standardized charting process, physical reorganization of ED stations, and a focus on the triage process that is a common bottleneck for ED’s across the US.

References

ACEP Medical Legal Committee. (2013). A risk management program for emergency medicine; basic components and considerations. Irving, TX: American College of Emergency Physicians.

Begley, C., Behan, P., & Seo, M. (2010). Who uses hospital emergency rooms?: Evidence from Houston/Harris county Texas. Journal of Health Care for the Poor and Underserved, 21(2), 606-616.

Francis, R. C., Spies, C. D., & Kerner, T. (2008). Quality management and benchmarking in emergency medicine. Current Opinion in Anaesthesiology, 21(2), 233-239.

Goralnick, E., Walls, R. M., & Kosowsky, J. M. (2013, September 26). How we revolutionized our emergency department. Harvard Business Review. Retrieved from http://blogs.hbr.org/2013/09/how-we-revolutionized-our-emergency-department/

Guttmann, A., Schull, M. J., Vermeulen, M. J., & Stukel, T. A. (2011). Association between waiting times and short term mortality and hospital admission after departure from emergency department: Population based cohort study from Ontario, Canada. British Medical Journal, 342(jun01 1), d2983-d2983.

Hirshon, J. M., Alson, R. L., Blunk, D., Brosnan, D. P., Epstein, S. K., Gardner, A. F, … Kivela, P.D. (2014). America's emergency care environment: A state-by-state report card. Irving, TX: American College of Emergency Physicians.

Holden, R. J. (2011). Lean thinking in emergency departments: A critical review. Annals of Emergency Medicine, 57(3), 265-278.

Oberklaid, F., Barnett, P., Jarman, F., & Sewell, J. (1991). Quality assurance in the emergency room. Archives of Disease in Childhood, 66(9), 1093-1098.

Wang, A. (2013, May 13). Emergency room waiting game. Crain's Chicago Business. Retrieved from http://www.chicagobusiness.com/article/20130511/ISSUE01/305119981/emergency-room-waiting-game#