Racial Differences in Pediatric Emergency Department Triage Scores

Triage Decisions Involving Pregnancy-Capable Patients: Educational Deficits and Emergency Nurses' Perceptions of Risk

BACKGROUND

In areas where obstetric services are not available, emergency departments often become the default for unplanned obstetric care, yet emergency nurses are not universally trained in the identification and treatment of obstetric emergencies. The purpose of this study was to explore emergency nurses' perception of acuity in the triage of pregnant or postpartum patients presenting to the emergency department with high-risk complaints and to identify facilitators and challenges to the accurate identification and treatment of these patients.

METHOD

A mixed-methods study was conducted using chart review data (N = 12,766) and focus group data (N = 39) from five emergency departments in the eastern United States.

RESULTS

In 86.5% of cases, pregnancy status was not documented. Ninety-four percent of pregnant patients with a systolic blood pressure over 140 mmHg were under-triaged. The overall theme of the qualitative data was acuity blindness, with identified barriers to assessment that included educational needs and triage processes and workflow issues.

CONCLUSION

There are significant knowledge deficits in the care of patients presenting with high-risk conditions associated with pregnancy. [J Contin Educ Nurs. 2021;52(1):21-29.].

First Nations emergency care in Alberta: descriptive results of a retrospective cohort study

Background

Worse health outcomes are consistently reported for First Nations people in Canada. Social, political and economic inequities as well as inequities in health care are major contributing factors to these health disparities. Emergency care is an important health services resource for First Nations people. First Nations partners, academic researchers, and health authority staff are collaborating to examine emergency care visit characteristics for First Nations and non-First Nations people in the province of Alberta.

Methods

We conducted a population-based retrospective cohort study examining all Alberta emergency care visits from April 1, 2012 to March 31, 2017 by linking administrative data. Patient demographics and emergency care visit characteristics for status First Nations persons in Alberta, and non-First Nations persons, are reported. Frequencies and percentages (%) describe patients and visits by categorical variables (e.g., Canadian Triage and Acuity Scale). Means, medians, standard deviations and interquartile ranges describe continuous variables (e.g., age).

Results

The dataset contains 11,686,288 emergency care visits by 3,024,491 unique persons. First Nations people make up 4% of the provincial population and 9.4% of provincial emergency visits. The population rate of emergency visits is nearly 3 times higher for First Nations persons than non-First Nations persons. First Nations women utilize emergency care more than non-First Nations women (54.2% of First Nations visits are by women compared to 50.9% of non-First Nations visits). More First Nations visits end in leaving without completing treatment (6.7% v. 3.6%).

Conclusions

Further research is needed on the impact of First Nations identity on emergency care drivers and outcomes, and on emergency care for First Nations women.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-021-06415-2.

Socioeconomic and Racial and/or Ethnic Disparities in Multisystem Inflammatory Syndrome

OBJECTIVES

To characterize the socioeconomic and racial and/or ethnic disparities impacting the diagnosis and outcomes of multisystem inflammatory syndrome in children (MIS-C).

METHODS

This multicenter retrospective case-control study was conducted at 3 academic centers from January 1 to September 1, 2020. Children with MIS-C were compared with 5 control groups: children with coronavirus disease 2019, children evaluated for MIS-C who did not meet case patient criteria, children hospitalized with febrile illness, children with Kawasaki disease, and children in Massachusetts based on US census data. Neighborhood socioeconomic status (SES) and social vulnerability index (SVI) were measured via a census-based scoring system. Multivariable logistic regression was used to examine associations between SES, SVI, race and ethnicity, and MIS-C diagnosis and clinical severity as outcomes.

RESULTS

Among 43 patients with MIS-C, 19 (44%) were Hispanic, 11 (26%) were Black, and 12 (28%) were white; 22 (51%) were in the lowest quartile SES, and 23 (53%) were in the highest quartile SVI. SES and SVI were similar between patients with MIS-C and coronavirus disease 2019. In multivariable analysis, lowest SES quartile (odds ratio 2.2 [95% confidence interval 1.1-4.4]), highest SVI quartile (odds ratio 2.8 [95% confidence interval 1.5-5.1]), and racial and/or ethnic minority background were associated with MIS-C diagnosis. Neither SES, SVI, race, nor ethnicity were associated with disease severity.

CONCLUSIONS

Lower SES or higher SVI, Hispanic ethnicity, and Black race independently increased risk for MIS-C. Additional studies are required to target interventions to improve health equity for children.

Examining black and white racial disparities in emergency department consultations by age and gender

BACKGROUND

While significant racial inequities in health outcomes exist in the United States, these inequities may also exist in healthcare processes, including the Emergency Department (ED). Additionally, gender has emerged in assessing racial healthcare disparity research. This study seeks to determine the association between race and the number and type of ED consultations given to patients presenting at a safety-net, academic hospital, which includes a level-one trauma center.

METHOD

Retrospective data was collected on the first 2000 patients who arrived at the ED from 1/1/2015-1/7/2015, with 532 patients being excluded. Of the eligible patients, 77% (74.6% adults and 80.7% pediatric patients) were black and 23% (25.4% adults and 19.3% pediatric patients) were white.

RESULTS

White and black adult patients receive similar numbers of ED consultations and remained after gender stratification. White pediatric males have a 91% higher incidence of receiving an ED consultation in comparison to their white counterparts. No difference was found between black and white adult patients when assessing the risk of receiving consultations. White adult females have a 260% higher risk of receiving both types of consultations than their black counterparts. Black and white pediatric patients had the same risk of receiving consultations, however, white pediatric males have a 194% higher risk of receiving a specialty consultation as compared to their white counterparts.

DISCUSSION

Future work should focus on both healthcare practice improvements, as well as explanatory and preventive research practices. Healthcare practice improvements can encompass development of appropriate racial bias trainings and institutionalization of conversations about race in medicine.

Improving ED Emergency Severity Index Acuity Assignment Using Machine Learning and Clinical Natural Language Processing

INTRODUCTION

Triage is critical to mitigating the effect of increased volume by determining patient acuity, need for resources, and establishing acuity-based patient prioritization. The purpose of this retrospective study was to determine whether historical EHR data can be used with clinical natural language processing and machine learning algorithms (KATE) to produce accurate ESI predictive models.

METHODS

The KATE triage model was developed using 166,175 patient encounters from two participating hospitals. The model was tested against a random sample of encounters that were correctly assigned an acuity by study clinicians using the Emergency Severity Index (ESI) standard as a guide.

RESULTS

At the study sites, KATE predicted accurate ESI acuity assignments 75.7% of the time compared with nurses (59.8%) and the average of individual study clinicians (75.3%). KATE's accuracy was 26.9% higher than the average nurse accuracy (P <.001). On the boundary between ESI 2 and ESI 3 acuity assignments, which relates to the risk of decompensation, KATE's accuracy was 93.2% higher, with 80% accuracy compared with triage nurses 41.4% accuracy (P <.001).

DISCUSSION

KATE provides a triage acuity assignment more accurate than the triage nurses in this study sample. KATE operates independently of contextual factors, unaffected by the external pressures that can cause under triage and may mitigate biases that can negatively affect triage accuracy. Future research should focus on the impact of KATE providing feedback to triage nurses in real time, on mortality and morbidity, ED throughput, resource optimization, and nursing outcomes.

Review article: Implicit bias towards Aboriginal and Torres Strait Islander patients within Australian emergency departments

Aboriginal and Torres Strait Islander peoples continue to suffer adverse experiences in healthcare, with inequitable care prevalent in emergency settings. Individual, institutional and systemic factors play a significant part in these persisting healthcare disparities, with biases remaining entrenched in healthcare institutions. This includes implicit racial bias which can result in stereotyping of racial minorities and premature diagnostic closure. Furthermore, it may contribute to distrust of medical professionals resulting in higher rates of leave events and hinder racial minorities from seeking care or following treatment recommendations. The aim of this review is to analyse the effect of implicit bias on patient outcomes in the ED in international literature and explore how these studies correlate to an Australian context.

A Racially Unbiased, Machine Learning Approach to Prediction of Mortality: Algorithm Development Study

Background

Racial disparities in health care are well documented in the United States. As machine learning methods become more common in health care settings, it is important to ensure that these methods do not contribute to racial disparities through biased predictions or differential accuracy across racial groups.

Objective

The goal of the research was to assess a machine learning algorithm intentionally developed to minimize bias in in-hospital mortality predictions between white and nonwhite patient groups.

Methods

Bias was minimized through preprocessing of algorithm training data. We performed a retrospective analysis of electronic health record data from patients admitted to the intensive care unit (ICU) at a large academic health center between 2001 and 2012, drawing data from the Medical Information Mart for Intensive Care–III database. Patients were included if they had at least 10 hours of available measurements after ICU admission, had at least one of every measurement used for model prediction, and had recorded race/ethnicity data. Bias was assessed through the equal opportunity difference. Model performance in terms of bias and accuracy was compared with the Modified Early Warning Score (MEWS), the Simplified Acute Physiology Score II (SAPS II), and the Acute Physiologic Assessment and Chronic Health Evaluation (APACHE).

Results

The machine learning algorithm was found to be more accurate than all comparators, with a higher sensitivity, specificity, and area under the receiver operating characteristic. The machine learning algorithm was found to be unbiased (equal opportunity difference 0.016, P=.20). APACHE was also found to be unbiased (equal opportunity difference 0.019, P=.11), while SAPS II and MEWS were found to have significant bias (equal opportunity difference 0.038, P=.006 and equal opportunity difference 0.074, P<.001, respectively).

Conclusions

This study indicates there may be significant racial bias in commonly used severity scoring systems and that machine learning algorithms may reduce bias while improving on the accuracy of these methods.

Combining Nonclinical Determinants of Health and Clinical Data for Research and Evaluation: Rapid Review

Background

Nonclinical determinants of health are of increasing importance to health care delivery and health policy. Concurrent with growing interest in better addressing patients’ nonmedical issues is the exponential growth in availability of data sources that provide insight into these nonclinical determinants of health.

Objective

This review aimed to characterize the state of the existing literature on the use of nonclinical health indicators in conjunction with clinical data sources.

Methods

We conducted a rapid review of articles and relevant agency publications published in English. Eligible studies described the effect of, the methods for, or the need for combining nonclinical data with clinical data and were published in the United States between January 2010 and April 2018. Additional reports were obtained by manual searching. Records were screened for inclusion in 2 rounds by 4 trained reviewers with interrater reliability checks. From each article, we abstracted the measures, data sources, and level of measurement (individual or aggregate) for each nonclinical determinant of health reported.

Results

A total of 178 articles were included in the review. The articles collectively reported on 744 different nonclinical determinants of health measures. Measures related to socioeconomic status and material conditions were most prevalent (included in 90% of articles), followed by the closely related domain of social circumstances (included in 25% of articles), reflecting the widespread availability and use of standard demographic measures such as household income, marital status, education, race, and ethnicity in public health surveillance. Measures related to health-related behaviors (eg, smoking, diet, tobacco, and substance abuse), the built environment (eg, transportation, sidewalks, and buildings), natural environment (eg, air quality and pollution), and health services and conditions (eg, provider of care supply, utilization, and disease prevalence) were less common, whereas measures related to public policies were rare. When combining nonclinical and clinical data, a majority of studies associated aggregate, area-level nonclinical measures with individual-level clinical data by matching geographical location.

Conclusions

A variety of nonclinical determinants of health measures have been widely but unevenly used in conjunction with clinical data to support population health research.

Racial/Ethnic Disparities in Longer-term Outcomes Among Emergency General Surgery Patients: The Unique Experience of Universally Insured Older Adults

OBJECTIVES

To determine whether racial/ethnic disparities in 30/90/180-day mortality, major morbidity, and unplanned readmissions exist among universally insured older adult (≥65 years) emergency general surgery patients; vary by diagnostic category; and can be explained by variations in geography, teaching status, age-cohort, and a hospital's percentage of minority patients.

SUMMARY OF BACKGROUND DATA

As the US population ages and discussions surrounding the optimal method of insurance provision increasingly enter into national debate, longer-term outcomes are of paramount concern. It remains unclear the extent to which insurance changes disparities throughout patients' postacute recovery period among older adults.

METHODS

Survival analysis of 2008 to 2014 Medicare data using risk-adjusted Cox proportional-hazards models.

RESULTS

A total of 6,779,649 older adults were included, of whom 82.8% identified as non-Hispanic white (NHW), 9.2% non-Hispanic black (NHB), 5.6% Hispanic, and 1.5% non-Hispanic Asian (NHA). Relative to NHW patients, each group of minority patients was significantly less likely to die [30-day NHB vs NHW hazard ratio (95% confidence interval): 0.88 (0.86-0.89)]. Differences became less apparent as outcomes approached 180 days [180-day NHB vs NHW: 1.00 (0.98-1.02)]. For major morbidity and unplanned readmission, differences among NHW, Hispanic, and NHA patients were comparable. NHB patients did consistently worse. Efforts to explain the occurrence found similar trends across diagnostic categories, but significant differences in disparities attributable to geography and the other included factors that combined accounted for up to 50% of readmission differences between racial/ethnic groups.

CONCLUSION

The study found an inversion of racial/ethnic mortality differences and mitigation of non-NHB morbidity/readmission differences among universally insured older adults that decreased with time. Persistent disparities among nonagenarian patients and hospitals managing a regionally large share of minority patients warrant particular concern.

Triage Performance in Emergency Medicine: A Systematic Review

STUDY OBJECTIVE

Rapid growth in emergency department (ED) triage literature has been accompanied by diversity in study design, methodology, and outcome assessment. We aim to synthesize existing ED triage literature by using a framework that enables performance comparisons and benchmarking across triage systems, with respect to clinical outcomes and reliability.

METHODS

PubMed, EMBASE, Scopus, and Web of Science were systematically searched for studies of adult ED triage systems through 2016. Studies evaluating triage systems with evidence of widespread adoption (Australian Triage Scale, Canadian Triage and Acuity Scale, Emergency Severity Index, Manchester Triage Scale, and South African Triage Scale) were cataloged and compared for performance in identifying patients at risk for mortality, critical illness and hospitalization, and interrater reliability. This study was performed and reported in adherence to Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines.

RESULTS

A total of 6,160 publications were identified, with 182 meeting eligibility criteria and 50 with sufficient data for inclusion in comparative analysis. The Canadian Triage and Acuity Scale (32 studies), Emergency Severity Index (43), and Manchester Triage Scale (38) were the most frequently studied triage scales, and all demonstrated similar performance. Most studies (6 of 8) reported high sensitivity (>90%) of triage scales for identifying patients with ED mortality as high acuity at triage. However, sensitivity was low (<80%) for identification of patients who had critical illness outcomes and those who died within days of the ED visit or during the index hospitalization. Sensitivity varied by critical illness and was lower for severe sepsis (36% to 74%), pulmonary embolism (54%), and non-ST-segment elevation myocardial infarction (44% to 85%) compared with ST-segment elevation myocardial infarction (56% to 92%) and general outcomes of ICU admission (58% to 100%) and lifesaving intervention (77% to 98%). Some proportion of hospitalized patients (3% to 45%) were triaged to low acuity (level 4 to 5) in all studies. Reliability measures (κ) were variable across evaluations, with only a minority (11 of 42) reporting κ above 0.8.

CONCLUSION

We found that a substantial proportion of ED patients who die postencounter or are critically ill are not designated as high acuity at triage. Opportunity to improve interrater reliability and triage performance in identifying patients at risk of adverse outcome exists.

The Impact of Health Equity Coaching on Patient's Perceptions of Cultural Competency and Communication in a Pediatric Emergency Department: An Intervention Design

Purpose

American Indian (AI) children experience significant disparities in health-care access. As a result, they are more likely to use the emergency department (ED) for nonemergent visits than white children. In a recent study, pediatric ED providers have shown an implicit bias for white children over AI children. To combat implicit bias in an ED setting, we created a protocol for training ED providers as health equity coaches.

Methods

The intervention took place during the fall of 2016 and was composed of 4 educational lectures, 6 to 8 hours of service learning in AI communities, and the participant's dissemination of what was learned through formal presentations and informal conversations with other ED staff. We measured the impact of this intervention on the intervention participants with a group interview at the completion of the intervention.

Results

The findings from the group interview provide feedback on what was learned during the intervention, how it impacted providers, and feedback on the structure of the intervention. Overall ED providers reported the intervention improved awareness of their implicit bias and ways to improve communication and care for AI patients. Additional institutional policy and procedural changes are necessary to effectively and sustainably address health disparities affecting AI populations.

Conclusions

The participating providers identified their lack of knowledge regarding AI cultures at the start of the intervention and it became clear that their knowledge, comfort, and relationships with AI communities increased as a result of this intervention.

Patient-level Factors and the Quality of Care Delivered in Pediatric Emergency Departments

OBJECTIVE

Quality of care delivered to adult patients in the emergency department (ED) is often associated with demographic and clinical factors such as a patient's race/ethnicity and insurance status. We sought to determine whether the quality of care delivered to children in the ED was associated with a variety of patient-level factors.

METHODS

This was a retrospective, observational cohort study. Pediatric patients (<18 years) who received care between January 2011 and December 2011 at one of 12 EDs participating in the Pediatric Emergency Care Applied Research Network (PECARN) were included. We analyzed demographic factors (including age, sex, and payment source) and clinical factors (including triage, chief complaint, and severity of illness). We measured quality of care using a previously validated implicit review instrument using chart review with a summary score that ranged from 5 to 35. We examined associations between demographic and clinical factors and quality of care using a hierarchical multivariable linear regression model with hospital site as a random effect.

RESULTS

In the multivariable model, among the 620 ED encounters reviewed, we did not find any association between patient age, sex, race/ethnicity, and payment source and the quality of care delivered. However, we did find that some chief complaint categories were significantly associated with lower than average quality of care, including fever (-0.65 points in quality, 95% confidence interval [CI] = -1.24 to -0.06) and upper respiratory symptoms (-0.68 points in quality, 95% CI = -1.30 to -0.07).

CONCLUSION

We found that quality of ED care delivered to children among a cohort of 12 EDs participating in the PECARN was high and did not differ by patient age, sex, race/ethnicity, and payment source, but did vary by the presenting chief complaint.

The Role of Bias by Emergency Department Providers in Care for American Indian Children

BACKGROUND

American Indian children have high rates of emergency department (ED) use and face potential discrimination in health care settings.

OBJECTIVE

Our goal was to assess both implicit and explicit racial bias and examine their relationship with clinical care.

RESEARCH DESIGN

We performed a cross-sectional survey of care providers at 5 hospitals in the Upper Midwest. Questions included American Indian stereotypes (explicit attitudes), clinical vignettes, and the Implicit Association Test. Two Implicit Association Tests were created to assess implicit bias toward the child or the parent/caregiver. Differences were assessed using linear and logistic regression models with a random effect for study site.

RESULTS

A total of 154 care providers completed the survey. Agreement with negative American Indian stereotypes was 22%-32%. Overall, 84% of providers had an implicit preference for non-Hispanic white adults or children. Older providers (50 y and above) had lower implicit bias than those middle aged (30-49 y) (P=0.01). American Indian children were seen as increasingly challenging (P=0.04) and parents/caregivers less compliant (P=0.002) as the proportion of American Indian children seen in the ED increased. Responses to the vignettes were not related to implicit or explicit bias.

CONCLUSIONS

The majority of ED care providers had an implicit preference for non-Hispanic white children or adults compared with those who were American Indian. Provider agreement with negative American Indian stereotypes differed by practice and respondents' characteristics. These findings require additional study to determine how these implicit and explicit biases influence health care or outcomes disparities.