Racial disparities in ED triage assessments and wait times

Racial disparities in ED triage assessments and wait times Jordan Bleth, James Beal PhD, Abe Sahmoun PhD June 2, 2017 Outline Background Purpose Methods Results Discussion Limitations Future areas of study Conclusions Acknowledgements References 1

Background Eliminating health care disparities is an important policy goal of HealthyPeople 2020 1 Access to health services encompasses four components: coverage, services, timeliness, and workforce. Timeliness is critical in the ED Prolonged ED wait times associated with 2,3 : Delayed diagnosis and treatment Extended pain and suffering Reduced patient satisfaction More patients leaving before being seen by a provider Overcrowding and prolonged ED wait times have been increasing 4,5,6 Between 1995-2010, yearly visits to the ED grew by 34%, while the number of hospital EDs declined by 11% 7 Background Other contributing factors 1,2,3,8 : aging population with greater health care needs shortages of nurses and other clinical personnel relative lack of inpatient and intensive care unit beds insufficient primary care network Proposed/implemented solutions 5 : optimizing triage systems and lab/radiologic processing times increasing availability of primary care, urgent care, advice lines improving insurance coverage transferring ED patients awaiting inpatient placement to hallway beds on the inpatient floor developing observation units implementing early inpatient discharge processes 2

Background Several studies have shown that minorities experience longer wait times & are assigned less urgent triage levels when presenting with similar conditions 2,6,7,9,10,13 Could be related to many variables at the level of the patient or the hospital 9,10 According to an analysis of NHAMCS in 2008 11 : average wait time for black patients was 69.2 minutes, vs. 53.3 minutes for non-black patients black patients were more likely to present with an illness with the lowest triage level (category 5) than non-black patients Purpose Determine if the racial disparity in ED wait times and triage levels persists, using data from the 2011 NHAMCS Race (Black, White, Other) Average ED wait time Triage level Study the association between race and several other patient and hospital characteristics 3

Methods Based on framework used in Qiao, WP 2015 Study Type Retrospective cross-sectional analysis Study Population Adults presenting to the ED with chest pain, abdominal pain, or back pain the three most common presenting chief complaints Inclusion Criteria Men and women, ages 18 and older Chest pain (ICD-9 code 786.5), abdominal pain (789.0), or back pain (724.5) Exclusion Criteria patient visits with missing variables Methods Variables Primary outcome variables: Triage level (1-5) Average wait time Primary independent variable: Race (Black, White, Other) Patient-level variables: Age Sex Payment method (private insurance, Medicare, Medicaid/CHIP) Season of visit Pain rating Hospital-level variables: Hospital ownership type (for-profit, government, nonprofit) Census region of the US (Northeast, West, South, Midwest) Metropolitan statistical area (urban vs. nonurban) Teaching status (patients seen by a resident physician) 4

Methods Exploratory data analysis was performed using summary statistics and bivariate comparisons (Chi-square tests and LSMeans, all significance tests were two-sided, P-value < 0.05 for significance) Survey data were analyzed using the sampled visit weight that is the product of the corresponding sampling fractions at each stage in the sample design SAS v.9.4 (SAS Institute, Cary, NC) was used to analyze the data in a manner that accounts for the NHAMCS s complex sample survey design Sampling errors were determined using the appropriate survey procedure following the guidance of the NHAMCS documentation, which takes into account the clustered nature of the sample. This study was approved by the University of North Dakota Institutional Review Board. Results Sample size: 3341 731 (21.9%) Black 2454 (73.5%) White 156 (4.7%) Other Asian, Native Hawaiian or Other Pacific Islander, American Indian or Alaska Native Association between race & sex, source of payment, teaching status, region, and triage level No association between race & age, season, hospital ownership, urban location, pain scale, and wait time 5

Table 1. Patient and hospital characteristics by race (% [95% confidence interval]) Black (n = 731, 21.9%) White (n = 2454, 73.5%) Other (n = 156, 4.7%) P value Age (y) 44.6 (42.2-47.0) 46.0 (44.7-47.3) 44.4 (39.3-49.5) 0.931 Sex 0.001 Female 66.1 (62.2-70.0) 57.0 (53.4-60.5) 61.2 (50.3-72.0) Season 0.931 Winter 20.8 (12.9-28.8) 21.8 (15.8-27.8) 23.6 (10.8-36.5) Spring 27.7 (14.1-41.4) 25.9 (18.3-33.4) 14.1 (5.2-22.9) Summer 25.4 (15.1-35.8) 27.0 (19.6-34.4) 33.5 (17.1-50.0) Fall 26.0 (14.6-37.4) 25.4 (18.2-32.5) 28.7 (13.9-43.5) Source of payment 0.013 Private insurance 28.3 (20.8-35.7) 34.4 (30.7-38.1) 25.6 (17.2-33.9) Medicare 22.8 (17.6-28.0) 24.2 (21.1-27.4) 14.4 (7.1-21.7) Medicaid or CHIP 27.0 (20.8-33.3) 19.5 (16.3-22.8) 35.9 (26.0-45.8) Other 21.9 (17.9-25.9) 21.8 (18.7-24.9) 24.1 (11.4-36.9) Teaching status 0.002 Teaching hospital 13.4 (9.3-17.5) 9.4 (6.6-12.3) 19.2 (9.8-28.6) Hospital ownership 0.742 For-profit 11.0 (0.48-21.4) 10.7 (3.8-17.5) 12.4 (1.4-23.3) Government 20.2 (12.1-28.4) 14.7 (9.5-20.0) 15.4 (5.1-25.6) Non-profit 68.8 (56.3-81.3) 74.6 (66.7-82.4) 72.3 (58.8-85.7) Table 1. Patient and hospital characteristics by race (% [95% CI]), continued Black (n = 731, 21.9%) White (n = 2454, 73.5%) Other (n = 156, 4.7%) P value Region <0.001 Northeast 10.2 (5.5-14.9) 15.4 (11.4-19.5) 18.2 (2.7-33.7) West 5.3 (2.8-7.7) 21.4 (14.4-28.4) 40.3 (21.6-58.9) South 66.3 (56.5-76.1) 38.3 (31.5-45.0) 18.2 (5.8-30.6) Midwest 18.3 (11.2-25.4) 25.0 (19.3-30.5) 23.3 (9.5-37.2) Urban vs. rural 0.365 Urban 91.0 (81.4-100.0) 86.0 (77.8-94.2) 95.1 (88.4-100.0) Pain scale 0.077 Mild 6.9 (4.5-9.2) 7.5 (6.1-8.9) 13.3 (6.5-20.5) Moderate 19.0 (14.7-23.3) 24.2 (21.6-26.8) 26.1 (15.1-37.2) Severe 67.7 (62.7-72.8) 60.9 (58.0-63.7) 52.8 (41.6-64.0) Triage level 0.034 (1) Immediate 0.35 (0.0-0.9) 1.0 (0.1-1.8) 5.9 (0.0-13.2) (2) 1-14 minutes 12.1 (8.1-16.1) 16.7 (13.9-19.5) 10.4 (4.5-16.4) (3) 15-60 minutes 53.7 (47.0-60.4) 53.3 (48.7-57.9) 57.0 (45.2-68.7) (4) >1 to 2 h 26.4 (21.9-31.0) 23.0 (19.5-26.6) 20.8 (10.4-31.1) (5) >2 to 24 h 5.5 (2.3-8.7) 3.7 (2.3-5.0) 1.0 (0.0-2.2) Mean wait time (min) 67.0 (44.8-89.2) 50.1 (44.1-56.0) 49.5 (36.9-62.0) 0.293 Median wait time (min) 31.9 (13.1-80.2) 26.3 (12.6-56.8) 32.5 (10.8-56.2) 6

Discussion Results indicate there is NO association between race and increased wait times Differs from many previous studies, including Qiao WP, 2015 May suggest racial disparities are improving Provider bias decreasing Socioeconomic factors changing (household income, education, residential segregation) Race/ethnicity-specific factors (patient preferences, communication patterns, language barriers, literacy) May suggest more efficient ED throughput, improved staffing, etc. May be related to ED utilization patterns Black patients less likely than patients in the Other group to visit Teaching hospitals, which take longer Consider including ED Volume as a variable perhaps more of this cohort visited lower-volume EDs Discussion Higher proportion of black patients presented with illnesses rated at a lower triage level Similar to previous studies, including Qiao WP, 2015 May be related to reduced access to/coverage of primary care services, given that black patients were less likely to use private insurance May be related to bias/subjective variables in triage process Race/gender of triage nurse Subjective variables such as look of the patient, different descriptors for symptoms, patient s behavior at triage desk Taken together with no significant increase in wait times, this is unexpected generally expect lower acuity illnesses to wait longer in triage 7

Discussion Black patients more likely to visit hospitals in the South Similar to Qiao WP, 2015 Fact that disparity in wait times has ostensibly improved indicates that efforts and resources directed here have helped Black patients less likely to use private insurance as a source of payment Similar to Qiao WP, 2015 An important consideration for reducing health disparities Black patients more likely to be female than male Similar to Qiao QP, 2015 Compared to males, black females may simply be more willing to seek care in the ED Limitations Sample size of some variables too small (<30 cases) to be reliable Payment method, hospital ownership, region, triage level Limited to top 3 chief complaints for sake of homogenous sample, which significantly reduced sample size Limited to adults age 18 or older for sake of homogenous sample, which significantly reduced sample size Did not account for ED volume in study design, a variable which could potentially cause differences in wait times between races Measurement errors inherent in NHAMCS, which could have affected the data Facilities may register patients/log time points differently Requirements for triage assignment can vary between institutions, may not be reliable as a proxy for illness severity 8

Future Studies Include all ages and chief complaints for larger sample size which is more representative of US population Include ED volume in analysis Include other ethnicities in analysis Hispanic patients make up large portion of ED patients, prior studies have demonstrated longer wait times for Hispanics vs. white patients 2 No option yet in NHAMCS for recording people of multiple races/ethnicities More studies are needed to explore racial disparities in triage assessments Conclusions Racial disparities amongst ED patients exist for: Triage assessment Sex Payment method Teaching status of hospital Region Importantly, there was no racial disparity in wait times. The fact that there is no longer a significant difference found between ED wait times for different racial groups may indicate improvement as a result of directed efforts, although it may also be a consequence of study design. Further studies are needed to continue trending ED wait times over time as a measure of how access to quality care is improving. 9

Acknowledgements Thank you to Dr. James Beal and Dr. Abe Sahmoun of UNDSMHS for your guidance and analysis of data. References 1. Office of Disease Prevention and Health Promotion. Access to Health Services. Healthy People 2020. Available at: http://www.healthypeople.gov/2020/topics-ob- jectives/topic/access-to- Health-Services. [Accessed Date (5/15/2017)]. 2. James CA, Bourgeois FT, Shannon MW. Association of race/ethnicity with emergency department wait times. Pediatrics. 2005 Mar;115(3):e310-5. 3. Wilper AP1, Woolhandler S, Lasser KE, et al. Waits to see an emergency department physician: U.S. trends and predictors, 1997-2004. Health Aff (Millwood). 2008 Mar-Apr;27(2):w84-95. 4. Schrader CD, Lewis LM. Racial disparity in emergency department triage. J Emerg Med. 2013 Feb;44(2):511-8. 5. Hsia RY, Tabas JA. Emergency care: the increasing weight of increasing waits. Arch Intern Med. 2009 Nov 9;169(20):1836-8. 6. Sonnenfeld N, Pitts SR, Schappert SM, et al. Emergency department volume and racial and ethnic differences in waiting times in the United States. Med Care. 2012 Apr;50(4):335-41. 7. Center for Disease Control and Prevention. 2010 NHAMCS: Emergency Department Summary Tables. Ambulatory Health Care Data. Available at: https://www.cdc.gov/nchs/data/ahcd/nhamcs_emergency/2010_ed_web_table s.pdf. [Accessed Date (5/15/2017)]. 10

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