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Wang H, Sambamoorthi N, Robinson RD, Knowles H, Kirby JJ, Ho AF, Takami T, Sambamoorthi U. What explains differences in average wait time in the emergency department among different racial and ethnic populations: A linear decomposition approach. J Am Coll Emerg Physicians Open 2024; 5:e13293. [PMID: 39263368 PMCID: PMC11388625 DOI: 10.1002/emp2.13293] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Revised: 07/20/2024] [Accepted: 08/14/2024] [Indexed: 09/13/2024] Open
Abstract
Objective Non-Hispanic Black (NHB) and Hispanic/Latino (Hispanic) patients wait longer in the emergency department (ED) to see practitioners when compared with non-Hispanic White (NHW) patients. We investigate factors contributing to longer wait times for NHB and Hispanic patients using a linear decomposition approach. Methods This retrospective observational study included patients presenting to one tertiary hospital ED from 2019 to 2021. Median wait times among NHW, NHB, and Hispanic were calculated with multivariable linear regressions. The extent to which demographic, clinical, and hospital factors explained the differences in average wait time among the three groups were analyzed with Blinder‒Oaxaca post-linear decomposition model. Results There were 310,253 total patients including 34.7% of NHW, 34.7% of NHB, and 30.6% of Hispanic patients. The median wait time in NHW was 9 min (interquartile range [IQR] 4‒47 min), in NHB was 13 min (IQR 4‒59 min), and in Hispanic was 19 min (IQR 5‒78 min, p < 0.001). The top two contributors of average wait time difference were mode of arrival and triage acuity level. Post-linear decomposition analysis showed that 72.96% of the NHB‒NHW and 87.77% of the Hispanic‒NHW average wait time difference were explained by variables analyzed. Conclusion Compared to NHW patients, NHB and Hispanic patients typically experience longer ED wait times, primarily influenced by their mode of arrival and triaged acuity levels. Despite these recognized factors, there remains 12%‒27% unexplained factors at work, such as social determinants of health (including implicit bias and systemic racism) and many other unmeasured confounders, yet to be discovered.
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Affiliation(s)
- Hao Wang
- Department of Emergency Medicine John Peter Smith Health Network Fort Worth Texas USA
| | | | - Richard D Robinson
- Department of Emergency Medicine Baylor University Medical Center Dallas Texas USA
| | - Heidi Knowles
- Department of Emergency Medicine John Peter Smith Health Network Fort Worth Texas USA
| | - Jessica J Kirby
- Department of Emergency Medicine John Peter Smith Health Network Fort Worth Texas USA
| | - Amy F Ho
- Department of Emergency Medicine John Peter Smith Health Network Fort Worth Texas USA
| | - Trevor Takami
- Department of Emergency Medicine John Peter Smith Health Network Fort Worth Texas USA
| | - Usha Sambamoorthi
- University of North Texas Health Science Center Fort Worth Texas USA
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Lin P, Argon NT, Cheng Q, Evans CS, Linthicum B, Liu Y, Mehrotra A, Murphy L, Patel MD, Ziya S. Identifying Patient Subpopulations with Significant Race-Sex Differences in Emergency Department Disposition Decisions. Health Serv Insights 2024; 17:11786329241277724. [PMID: 39247491 PMCID: PMC11378179 DOI: 10.1177/11786329241277724] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2024] [Accepted: 08/08/2024] [Indexed: 09/10/2024] Open
Abstract
Background/objectives The race-sex differences in emergency department (ED) disposition decisions have been reported widely. Our objective is to identify demographic and clinical subgroups for which this difference is most pronounced, which will facilitate future targeted research on potential disparities and interventions. Methods We performed a retrospective analysis of 93 987 White and African-American adults assigned an Emergency Severity Index of 3 at 3 large EDs from January 2019 to February 2020. Using random forests, we identified the Elixhauser comorbidity score, age, and insurance status as important variables to divide data into subpopulations. Logistic regression models were then fitted to test race-sex differences within each subpopulation while controlling for other patient characteristics and ED conditions. Results In each subpopulation, African-American women were less likely to be admitted than White men with odds ratios as low as 0.304 (95% confidence interval (CI): [0.229, 0.404]). African-American men had smaller admission odds compared to White men in subpopulations of 41+ years of age or with very low/high Elixhauser scores, odds ratios being as low as 0.652 (CI: [0.590, 0.747]). White women were less likely to be admitted than White men in subpopulations of 18 to 40 or 41 to 64 years of age, with low Elixhauser scores, or with Self-Pay or Medicaid insurance status with odds ratios as low as 0.574 (CI: [0.421, 0.784]). Conclusions While differences in likelihood of admission were lessened by younger age for African-American men, and by older age, higher Elixhauser score, and Medicare or Commercial insurance for White women, they persisted in all subgroups for African-American women. In general, patients of age 64 years or younger, with low comorbidity scores, or with Medicaid or no insurance appeared most prone to potential disparities in admissions.
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Affiliation(s)
- Peter Lin
- Department of Statistics and Operations Research, University of North Carolina, Chapel Hill, NC, USA
| | - Nilay T Argon
- Department of Statistics and Operations Research, University of North Carolina, Chapel Hill, NC, USA
| | - Qian Cheng
- Department of Statistics and Operations Research, University of North Carolina, Chapel Hill, NC, USA
| | - Christopher S Evans
- Information Services, ECU Health, Greenville, NC, USA
- Department of Emergency Medicine, East Carolina University, Greenville, NC, USA
| | - Benjamin Linthicum
- Department of Emergency Medicine, University of North Carolina, Chapel Hill, NC, USA
| | - Yufeng Liu
- Department of Statistics and Operations Research, University of North Carolina, Chapel Hill, NC, USA
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
- Department of Biostatistics, University of North Carolina, Chapel Hill, NC, USA
- Carolina Center for Genome Sciences, University of North Carolina, Chapel Hill, NC, USA
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC, USA
| | - Abhishek Mehrotra
- Department of Emergency Medicine, University of North Carolina, Chapel Hill, NC, USA
| | - Laura Murphy
- Department of Emergency Medicine, University of North Carolina, Chapel Hill, NC, USA
| | - Mehul D Patel
- Department of Emergency Medicine, University of North Carolina, Chapel Hill, NC, USA
| | - Serhan Ziya
- Department of Statistics and Operations Research, University of North Carolina, Chapel Hill, NC, USA
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Coffey EK, Walker RM, Nicholson P, Gillespie BM. Prioritising patients for semi-urgent surgery: A scoping review. J Clin Nurs 2024; 33:2509-2524. [PMID: 38334175 DOI: 10.1111/jocn.17056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Revised: 11/16/2023] [Accepted: 01/23/2024] [Indexed: 02/10/2024]
Abstract
BACKGROUND Semi-urgent surgery where surgical intervention is required within 48 h of admission and the patient is medically stable is vulnerable to scheduling delays. Given the challenges in accessing health care, there is a need for a detailed understanding of the factors that impact decisions on scheduling semi-urgent surgeries. AIM To identify and describe the organisational, departmental and contextual factors that determine healthcare professionals' prioritising patients for semi-urgent surgeries. METHODS We used the Joanna Briggs Institute guidance for scoping reviews and the Preferred Reporting Items for Systematic Reviews and Meta-Analysis extension for scoping reviews (PRISMA-ScR) checklist. Four online databases were used: EBSCO Academic Search Complete, EBSCO Cumulative Index to Nursing and Allied Health Literature, OVID Embase and EBSCO Medline. Articles were eligible for inclusion if they published in English and focussed on the scheduling of patients for surgery were included. Data were extracted by one author and checked by another and analysed descriptively. Findings were synthesises using the Patterns, Advances, Gaps, Evidence for practice and Research recommendations framework. RESULTS Twelve articles published between 1999 and 2022 were included. The Patterns, Advances, Gaps, Evidence for practice and Research recommendations framework highlighted themes of emergency surgery scheduling and its impact on operating room utilisation. Gaps in the management of operating room utilisation and the incorporation of semi-urgent surgeries into operating schedules were also identified. Finally, the lack of consensus on the definition of semi-urgent surgery and the parameters used to assign surgical acuity to patients was evident. CONCLUSIONS This scoping review identified patterns in the scheduling methods, and involvement of key decision makers. Yet there is limited evidence about how key decision makers reach consensus on prioritising patients for semi-urgent surgery and its impact on patient experience. PATIENT OR PUBLIC CONTRIBUTION No Patient or Public Contribution.
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Affiliation(s)
- Elyse K Coffey
- School of Nursing and Midwifery, Deakin University, Geelong, Victoria, Australia
- School of Nursing and Midwifery, Menzies Health Institute Queensland, Griffith University, Southport, Queensland, Australia
| | - Rachel M Walker
- School of Nursing and Midwifery, Menzies Health Institute Queensland, Griffith University, Southport, Queensland, Australia
- Division of Surgery, Princess Alexandra Hospital, Woolloongabba, Queensland, Australia
- National Health and Medical Research Council Centre of Research Excellence in Wiser Wound Care, Menzies Health Institute Queensland, Griffith University, Southport, Queensland, Australia
| | - Patricia Nicholson
- School of Nursing and Midwifery, Deakin University, Geelong, Victoria, Australia
- Centre for Quality and Patient Safety Research, Institute for Health Transformation, Deakin University, Geelong, Victoria, Australia
| | - Brigid M Gillespie
- School of Nursing and Midwifery, Menzies Health Institute Queensland, Griffith University, Southport, Queensland, Australia
- National Health and Medical Research Council Centre of Research Excellence in Wiser Wound Care, Menzies Health Institute Queensland, Griffith University, Southport, Queensland, Australia
- Gold Coast University Hospital, Gold Coast Health Nursing and Midwifery Education and Research Unit, Gold Coast, Queensland, Australia
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Patel MD, Lin P, Cheng Q, Argon NT, Evans CS, Linthicum B, Liu Y, Mehrotra A, Murphy L, Ziya S. Patient sex, racial and ethnic disparities in emergency department triage: A multi-site retrospective study. Am J Emerg Med 2024; 76:29-35. [PMID: 37980725 PMCID: PMC11270534 DOI: 10.1016/j.ajem.2023.11.008] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Revised: 10/30/2023] [Accepted: 11/07/2023] [Indexed: 11/21/2023] Open
Abstract
OBJECTIVES There is limited evidence on sex, racial, and ethnic disparities in Emergency Department (ED) triage across diverse settings. We evaluated differences in the assignment of Emergency Severity Index (ESI) by patient sex and race/ethnicity, accounting for age, clinical factors, and ED operating conditions. METHODS We conducted a multi-site retrospective study of adult patients presenting to high-volume EDs from January 2019-February 2020. Patient-level data were obtained and analyzed from three EDs (academic, metropolitan community, and rural community) affiliated with a large health system in the Southeastern United States. For the study outcome, ESI levels were grouped into three categories: 1-2 (highest acuity), 3, and 4-5 (lowest acuity). Multinomial logistic regression was used to compare ESI categories by patient race/ethnicity and sex jointly (referent = White males), adjusted for patient age, insurance status, ED arrival mode, chief complaint category, comorbidity score, time of day, day of week, and average ED wait time. RESULTS We identified 186,840 eligible ED visits with 56,417 from the academic ED, 69,698 from the metropolitan community ED, and 60,725 from the rural community ED. Patient cohorts between EDs varied by patient age, race/ethnicity, and insurance status. The majority of patients were assigned ESI 3 in the academic and metropolitan community EDs (61% and 62%, respectively) whereas 47% were assigned ESI 3 in the rural community ED. In adjusted analyses, White females were less likely to be assigned ESI 1-2 compared to White males although both groups were roughly comparable in the assignment of ESI 4-5. Non-White and Hispanic females were generally least likely to be assigned ESI 1-2 in all EDs. Interactions between ED wait time and race/ethnicity-sex were not statistically significant. CONCLUSIONS This retrospective study of adult ED patients revealed sex and race/ethnicity-based differences in ESI assignment, after accounting for age, clinical factors, and ED operating conditions. These disparities persisted across three different large EDs, highlighting the need for ongoing research to address inequities in ED triage decision-making and associated patient-centered outcomes.
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Affiliation(s)
- Mehul D Patel
- Department of Emergency Medicine, University of North Carolina at Chapel Hill, NC, USA.
| | - Peter Lin
- Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, NC, USA
| | - Qian Cheng
- Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, NC, USA
| | - Nilay T Argon
- Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, NC, USA
| | - Christopher S Evans
- Information Services, ECU Health, Greenville, NC, USA; Department of Emergency Medicine, East Carolina University, Greenville, NC, USA
| | - Benjamin Linthicum
- Department of Emergency Medicine, University of North Carolina at Chapel Hill, NC, USA
| | - Yufeng Liu
- Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, NC, USA; Department of Genetics, Department of Biostatistics, University of North Carolina at Chapel Hill, NC, USA
| | - Abhi Mehrotra
- Department of Emergency Medicine, University of North Carolina at Chapel Hill, NC, USA
| | - Laura Murphy
- Department of Emergency Medicine, University of North Carolina at Chapel Hill, NC, USA
| | - Serhan Ziya
- Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, NC, USA
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