Administration & Operations

Implicit Bias and ED Overcrowding: Is There a Connection?

Overcrowding in the emergency department can be a significant barrier to delivering efficient and high-quality care, but the impact on delivering equitable health care is less commonly discussed. Literature demonstrates a connection between overcrowding and increased length of stay, mortality, and higher cost per admission.1

Overcrowding negatively impacts clinical decision-making by increasing miscommunication, delaying recognition and treatment, and increasing physician cognitive load.2,3 A large contributor to overcrowding is inefficient hospital throughput, especially in hospitals operating at greater than 100% capacity resulting in patients boarding in the ED. An overwhelmed primary health care system also contributes to an increasing number of patients relying on the ED as their sole access to the health care system. EDs are challenged to meet the needs of increasingly complex and diverse patients while managing higher patient volumes within the confines of limited hospital throughput and bed availability.

Like many other specialties, emergency medicine has discrepancies in care outcomes in marginalized populations in comparison to the general population.4-6 However, emergency medicine is unique from other specialties in the high number of decisions made each shift based on limited patient information, while also subject to frequent work-flow interruptions and time constraints. Clinical decisions are made without a long-term doctor-patient relationship and are based on initial impression that can be influenced by extraneous factors. Physician fatigue and cognitive stress, which are exacerbated by the overcrowded conditions of the ED, may amplify internal bias held by providers and have an increased role in clinical decision-making.3,7,8 These biases include subconscious attitudes and perpetuating generalizations/stereotypes of marginalized patients (ethnic/racial/linguistic minorities, those with poor social support, those with substance abuse or psychiatric disorders, ED “frequent flyers,” etc.). This is important to consider because EDs serve as safety nets for vulnerable populations, providing access to care independent of income, insurance, gender, race, or ethnicity.5 The effects of overcrowding can influence biases from the time of ED triage, during ED provider evaluation, and throughout hospitalization.

Patient bias may begin in the prehospital setting or in ED triage and can be perpetuated by the patient’s location in the ED. It is standard of care that patients are triaged based on acuity and resource utilization. Thus, under normal circumstances without ED boarding, one could easily presume that a patient placed in the hallway is lower acuity, leading to a lower provider suspicion of acute pathology in comparison to a patient placed in a regular treatment room. For example, one could easily imagine the discrepant assessment and work up for a hallway patient triaged as “somnolent and intoxicated” in comparison to that of a patient who enters a critical care area for the same chief complaint.

However, with increasing ED volumes and overcrowding, this may be a dangerous mindset, as many of our hallways are now considered to be normal treatment areas and are filled with patients with varying levels of acuity. The triage provider is also making patient care decisions with even less information and time than the patient’s main ED provider, and these decisions can be influenced by prehospital personnel, patient behavior, appearance, and ability to express severity of illness. Multiple factors make patients susceptible to inaccurate triage and more likely to end up placed in an ostensibly lower acuity area of the ED. Patients who face language barriers may be unable to communicate illness severity or have their primary complaints misunderstood, leading to inappropriate initial assessment. Patients with history of high ED utilization may have their medical concerns minimized, making them susceptible to limited clinical assessment and the potential to miss acute pathology. Thus, patient location in the ED in addition to inherent patient factors of vulnerability may lead to suboptimal care.

ED overcrowding can contribute to implicit bias during ED provider evaluation, especially if the patient has characteristics that are prone to stereotyping. One such factor is the stigma associated with mental illness. Patients with mental health disorders experience societal stigma, suboptimal social interaction and limited vocational opportunities.9 Many of them limit health care interactions due to their own self-stigma and fear of experiencing further negative interaction.10 Due to these stigmas, mental health illness is often linked to homelessness and substance abuse. These patients have many risk factors for acute pathology and may be subjected to inaccurate assessment due to increased provider bias during the ED evaluation. Implicit biases may include attributing distress to mental illness instead of an acute medical process. Patients with mental health problems often require increased face to face provider time due to complicated social situations and, unfortunately, may receive a cursory evaluation due to the inability or aversion to dedicating large amounts of time in a busy emergency department.9 All these factors can set these patients up for suboptimal health care, especially within the time-pressured environment of the ED.  

One of the most studied factors contributing to provider bias within health care is patient ethnicity. Previous research has shown that provider bias due to ethnicity has altered health care decisions in management of thrombolysis, chest pain, and treatment of acute pain.6,11,12 This implicit bias has been shown to be promoted by the heavy cognitive stressors and time pressures of the ED environment.13,14 ED overcrowding may also increase provider reliance on heuristics and promote implicit stereotypes.15 In a study investigating ED provider ethnicity bias pre- and post-shift, it was found that ED overcrowding and higher patient volumes caused a greater pro-white implicit bias.5 In contrast, when cognitive burdens are reduced providers are more likely to individualize patients and employ strategies that reduce unconscious bias.16,17 As a result, reduced ED overcrowding can promote more equitable health care decisions for patients.

Implicit biases during ED evaluation can negatively impact not only the ED evaluation but the entire hospitalization. Under conditions of heavy workload and time constraint, unconscious bias may play an even greater role in the rapid decision-making and disposition planning by ED providers.17 It has also been reported that patient generalizations affect not only immediate treatment decisions, but also decisions of further specialist involvement and procedural intervention.11,18,19 If these first patient-provider interactions are compromised by implicit biases, they will contribute to suboptimal downstream health care decisions. Unfortunately, ED overcrowding can promote these biases and may contribute to increased health care disparities in vulnerable patient populations.

The ED is the safety net for many vulnerable populations. Recognition of possible implicit biases and cognitive stressors that may promote these biases will assist providers in more accurately assessing at-risk patients and reduce health care disparities. Strategies to address ED overcrowding, hospital throughput, and provider fatigue can also reduce the extraneous stressors that can increase reliance on heuristics and patient stereotyping. Greater education in mental health disorders may also promote an improved interaction between providers and these patients -- leading to improved access to emergency care. By becoming aware of what specific stressors can augment these biases and which patient characteristics increase vulnerability, ED providers can implement decision-making that is less influenced by unconscious bias and help improve the care of the marginalized patient.

References

1. Kavanagh K, Shields D, Staunton P. 40 ED crowding: the acceptability of dysfunction. Emerg Med J. 2017;34(12):A887-a888.
2. Derlet RW, Richards JR. Overcrowding in the nation’s emergency departments: Complex causes and disturbing effects. Ann Emerg Med. 2000;35(1):63-68.
3. Laxmisan A, Hakimzada F, Sayan OR, Green RA, Zhang J, Patel VL. The multitasking clinician: decision-making and cognitive demand during and after team handoffs in emergency care. Int J Med Inform. 2007;76(11-12):801-811.
4. Richardson LD, Babcock Irvin C, Tamayo-Sarver JH. Racial and ethnic disparities in the clinical practice of emergency medicine. Acad Emerg Med. 2003;10(11) 1184-1188.
5. Johnson TJ, Hickey RW, Switzer GE, et al. The Impact of Cognitive Stressors in the Emergency Department on Physician Implicit Racial Bias. Acad Emerg Med. 2016;23(3):297-305.
6. Sabin JA, Rivara FP, Greenwald AG. Physician implicit attitudes and stereotypes about race and quality of medical care. Med Care. 2008;46(7):678-885.
7. Kovacs G, Croskerry P. Clinical decision-making: an emergency medicine perspective. Acad Emerg Med. 1999;6(9):947-952.
8. Croskerry P, Sinclair D. Emergency medicine: A practice prone to error? CJEM. 2001; 3(4):271-276.
9. Peris TS, Teachman BA, Nosek BA. Implicit and explicit stigma of mental illness: links to clinical care. J Nerv Ment Dis. 2008;196(10):752-760.
10. Corrigan PW, Watson AC. Understanding the impact of stigma on people with mental illness. World Psychiatry. 2002;1(1):16-20.
11. Green AR, Carney DR, Pallin DJ, Ngo LH, Raymond KL, Iezzoni LI, Banaji MR. Implicit bias among physicians and its prediction of thrombolysis decisions for black and white patients. J Gen Intern Med. 2007;22(9):1231-1238.
12. Stepanikova I. Racial-ethnic biases, time pressure, and medical decisions. J Health Soc Behav. 2012;53(3):329-343.
13. Muroff JR, Jackson JS, Mowbray CT, Himle JA. The influence of gender, patient volume and time on clinical diagnostic decision-making in psychiatric emergency services. Gen Hosp Psychiatry. 2007;29(6):481-488.
14. Wigboldus DHJ, Sherman JW, Franzese HL, van Knippenberg A. Capacity and Comprehension: Spontaneous Stereotyping Under Cognitive Load. Social Cognition. 2004;22(3):292-309.
15. Burgess DJ. Are providers more likely to contribute to health care disparities under high levels of cognitive load? How features of the health care setting may lead to biases in medical decision-making. Med Decis Making. 2010;30(2):246-257.
16. Yi‐Wen C, Wegener DT, Petty RE, Hsiao CC. The Flexible Correction Model: Bias Correction Guided by Naïve Theories of Bias. Soc Pers Soc Comp. 2014;8(6):275-286.
17. Blanchard JC, Haywood YC, Scott C. Racial and ethnic disparities in health: an emergency medicine perspective. Acad Emerg Med. 2003;10(11):1289-1293.
18. Schulman KA, Berlin JA, Harless W, et al. The effect of race and sex on physicians' recommendations for cardiac catheterization. N Engl J Med. 1999;340(8):618-626.
19. Kerman HM, Smith SR, Smith KC, et al. Disparities in total knee replacement: Population losses in quality-adjusted life years due to differential offer, acceptance, and complication rates for Black Americans. Arthritis Care Res (Hoboken). 2018;70(9):1326-1334.

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