Patient Race or Ethnicity and the Use of Diagnostic Imaging: A Systematic Review

Radiology Utilization in an Academic Center Partnership With a Federally Qualified Health Center: A Cross-Sectional Study

OBJECTIVE

Federally qualified health centers (FQHCs) serve medically underserved populations. In 2013, UW Health, the health system of the University of Wisconsin, partnered with Access Community Health Centers (ACHC), the FQHC network in Madison, Wisconsin, to provide on-site outpatient imaging. This study characterized radiography utilization associated with the UW Health-ACHC partnership compared with other UW Health outpatient imaging sites.

METHODS

We included health record data from January 2013 to December 2022 on all outpatient radiographs completed at UW Health sites. We compared characteristics between patients ever seen at ACHC clinics with patients seen only at non-ACHC UW Health clinics using χ2 and t tests. Logistic regression was used to assess factors associated with imaging utilization at ACHC.

RESULTS

Over the study period, 4% (23,794 of 650,685) of imaging encounters occurred at ACHC and 4% (10,986 of 246,104) of patients used ACHC facilities at least once. ACHC clinic patients were younger (41 versus 42) and more often female (55% versus 53%), Black or African American (22% versus 5%), Hispanic or Latino (34% versus 4%), with Medicaid (33% versus 9%), uninsured (18% versus 4%), and living in metropolitan areas (98% versus 88%) with higher Social Deprivation Index scores (53 versus 31) (P < .001). In multivariable analyses, patients from racial or ethnic minority groups, without commercial insurance, residing in a metropolitan area, and with a non-English primary language were more likely to ever use ACHC radiography services (P < .001).

DISCUSSION

FQHCs represent trusted, community health centers serving medically underserved populations. Partnerships between academic institutions and FQHCs can increase geographic imaging access among these groups.

Racial and Ethnic Disparities in Screening Mammography During COVID-19 in the Upper Midwest

OBJECTIVE

Studies conducted prior to COVID-19 suggested that racial and ethnic disparities in mammographic screening have reduced over time. COVID-19 has had devastating effects on racial and ethnic minority populations, resulting in delays in preventive screening. Our purpose was to determine if racial and ethnic minority groups were less likely to receive mammographic screening during the COVID-19 pandemic.

METHODS

Retrospective cross-sectional study was conducted in a multisite academic medical center in the Upper Midwest to evaluate screening disparities during the COVID-19 pandemic. Participants included 50- to 74-year-old female individuals (June 2021 to May 2022). Additional control group was included for pre-COVID-19 case-control comparison (June 2018 to May 2019). Unadjusted and adjusted logistic regression analyses estimated the association between screening and race and ethnicity including interaction terms to assess temporal interactions associated with COVID-19. Study was deemed exempt from institutional review board review.

RESULTS

In all, 37,509 eligible female patients were included. Of them, 73.8% of eligible patients received a mammogram within the last 2 years (White 74.7%, Black 57.6%, Asian 67.0%, American Indian 60.1%, Hispanic 64.2%). In our adjusted analyses, Black (P < .001), Asian (P = .003), and American Indian patients (P = .001) were less likely to receive screening. Hispanic patients were comparably likely to receive screening (P = .338). Non-English-preferred languages, uninsured or Medicaid, and living in rural areas were associated with decreased screening (P < .001). In all, 36,768 eligible female patients were included for pre-COVID-19 comparison. Compared with the pre-COVID-19 time period, COVID-19 was associated with increased screening disparities (P < .001) for Black and Hispanic women (P < .001).

CONCLUSION

The COVID-19 pandemic was associated with increased racial and ethnic screening disparities. Targeted outreach efforts are required to ensure equitable access to mammographic screening for medically underserved patient populations.

Six Steps to Improving Health Equity Using Quality Improvement and Patient Safety Tools

Health equity is a foundational principle for providing high-quality care. The COVID-19 pandemic has increased the urgency of health systems and regulatory agencies to address longstanding health disparities. Imaging disparities have been documented in the imaging literature for decades, but there is paucity of published interventions to successfully reduce disparities in imaging. Quality and safety approaches can be successfully employed to catalyze and rigorously evaluate interventions to reduce imaging disparities. Emerging from the Toyota Production System, the lean management framework focuses on continuous quality improvement to improve efficiency and reduce waste. Lean approaches have been successfully adopted by quality and safety experts in health care for problem-solving and process improvement. This article provides readers with step-by-step guidance on how to address health equity issues by adapting selected lean tools for quality improvement and patient safety. Core steps include (a) problem identification, (b) team building, (c) creation of a data infrastructure, (d) problem analysis, (e) development and testing of solutions, and (f) change management strategies to help organizations sustain successful health equity initiatives. Readers can use these six core steps to catalyze data-driven quality improvement initiatives to reduce imaging disparities within their health systems.

Artificial intelligence: Applications in cardio-oncology and potential impact on racial disparities

Numerous cancer therapies have detrimental cardiovascular effects on cancer survivors. Cardiovascular toxicity can span the course of cancer treatment and is influenced by several factors. To mitigate these risks, cardio-oncology has evolved, with an emphasis on prevention and treatment of cardiovascular complications resulting from the presence of cancer and cancer therapy. Artificial intelligence (AI) holds multifaceted potential to enhance cardio-oncologic outcomes. AI algorithms are currently utilizing clinical data input to identify patients at risk for cardiac complications. Additional application opportunities for AI in cardio-oncology involve multimodal cardiovascular imaging, where algorithms can also utilize imaging input to generate predictive risk profiles for cancer patients. The impact of AI extends to digital health tools, playing a pivotal role in the development of digital platforms and wearable technologies. Multidisciplinary teams have been formed to implement and evaluate the efficacy of these technologies, assessing AI-driven clinical decision support tools. Other avenues similarly support practical application of AI in clinical practice, such as incorporation into electronic health records (EHRs) to detect patients at risk for cardiovascular diseases. While these AI applications may help improve preventive measures and facilitate tailored treatment to patients, they are also capable of perpetuating and exacerbating healthcare disparities, if trained on limited, homogenous datasets. However, if trained and operated appropriately, AI holds substantial promise in positively influencing clinical practice in cardio-oncology. In this review, we explore the impact of AI on cardio-oncology care, particularly regarding predicting cardiotoxicity from cancer treatments, while addressing racial and ethnic biases in algorithmic implementation.

Medical imaging utilization in migrants compared with nonmigrants in a universal healthcare system: A population-based matched cohort study

BACKGROUND

Medical imaging is an integral part of healthcare. Globalization has resulted in increased mobilization of migrants to new host nations. The association between migration status and utilization of medical imaging is unknown.

METHODS AND FINDINGS

A retrospective population-based matched cohort study was conducted in Ontario, Canada from April 1, 1995 to December 31, 2016. A total of 1,848,222 migrants were matched 1:1 to nonmigrants in the year of migration on age, sex, and geography. Utilization of computed tomography (CT), magnetic resonance imaging (MRI), radiography, and ultrasonography was determined. Rate differences per 1,000 person-years comparing migrants to nonmigrants were calculated. Relative rates were calculated using a recurrent event framework, adjusting for age, sex, and time-varying socioeconomic status, comorbidity score, and access to a primary care provider. Estimates were stratified by migration age: children and adolescents (≤19 years), young adults (20 to 39), adults (40 to 59), and older adults (≥60). Utilization rates of CT, MRI, and radiography were lower for migrants across all age groups compared with Ontario nonmigrants. Increasing age at migration was associated with larger differences in utilization rates. Older adult migrants had the largest gap in imaging utilization. The longer the time since migration, the larger the gap in medical imaging use. In multivariable analysis, the relative rate of imaging was approximately 20% to 30% lower for migrants: ranging from 0.77 to 0.88 for CT and 0.72 to 0.80 for MRI imaging across age groups. Radiography relative rates ranged from 0.84 to 0.90. All migrant age groups, except older adults, had higher rates of ultrasonography. The indication for imaging was not captured, thus it was not possible to determine if the imaging was necessary.

CONCLUSIONS

Migrants utilized less CT, MRI, and radiography but more ultrasonography. Older adult migrants used the least amount of imaging compared with nonmigrants. Future research should evaluate whether lower utilization is due to barriers in healthcare access or health-seeking behaviors within a universal healthcare system.

Fostering Patient-Centered Equitable Care in Radiology: AJR Expert Panel Narrative Review

Patient-centered care (PCC) and equity are two of the six core domains of quality health care, according to the Institute of Medicine. Exceptional imaging care requires radiology practices to provide patient-centered (i.e., respectful and responsive to individual patient preferences, needs, and values) and equitable (i.e., does not vary in quality on the basis of gender, ethnicity, geographic location, or socioeconomic status) care. Specific barriers that prevent the delivery of patient-centered equitable care include information gaps, breaches of trust, organizational medical culture, and financial incentives. Information gaps limit practitioners in understanding the lived experience of patients. Breaches of trust prevent patients from seeking needed medical care. Organizational medical cultures may not be centered around patient experiences. Financial incentives can impede practitioners' ability to spend the time and resources required to meet patient goals and needs. Intentional approaches that integrate core principles in both PCC and health equity are required to deliver high-quality patient-centered imaging care for diverse patient populations. The purpose of this AJR Expert Panel Narrative Review is to review the origins of the PCC movement in radiology, characterize connections between the PCC and health equity movements, and describe concrete examples of ways to foster patient-centered equitable care in radiology.

Health services utilization by fibromyalgia patients from two ethnic groups

AIM

The cost to the healthcare system of management and treatment for fibromyalgia patients is high. The aims of the study were to identify and compare factors associated with the use of healthcare services among fibromyalgia patients in southern Israel from two ethnic groups.

METHODS

A cross-sectional study of patients insured in the southern district of the Clalit Healthcare Services in Israel in 2019-2020. The data were collected from the central computerized system. Multivariable regression models were developed for healthcare services utilization.

RESULTS

During the study period, 7686 members were diagnosed with fibromyalgia. The median for specialist consultations was 47 and for imaging tests was eight. About 47% made emergency room visits and 25% were hospitalized. The median of imaging tests was significantly higher in Jewish patients than in Arab patients (8 vs. 6; p = .000). In contrast, a significantly higher rate of Arab patients visited the Emergency Room at least once (51.6% vs. 46.75%; p = .000) and they had a higher median number or Emergency Room visits (2 vs. 1; p = .003), compared with Jewish patients. In the Arab group there was a strong effect coefficient for another localized pain syndrome with specialist consultations (odds ratio [OR] 1.699; 95% confidence interval [CI] 1.266-2.241) and imaging tests (OR 2.511; 95% CI 1.496-4.146).

CONCLUSIONS

The utilization rate of healthcare services is high among fibromyalgia patients. The factors associated with high healthcare utilization are different in the two ethnic groups. Future studies could show if interventions designed to address modifiable factors could reduce the overutilization of healthcare services.

AI pitfalls and what not to do: mitigating bias in AI

Various forms of artificial intelligence (AI) applications are being deployed and used in many healthcare systems. As the use of these applications increases, we are learning the failures of these models and how they can perpetuate bias. With these new lessons, we need to prioritize bias evaluation and mitigation for radiology applications; all the while not ignoring the impact of changes in the larger enterprise AI deployment which may have downstream impact on performance of AI models. In this paper, we provide an updated review of known pitfalls causing AI bias and discuss strategies for mitigating these biases within the context of AI deployment in the larger healthcare enterprise. We describe these pitfalls by framing them in the larger AI lifecycle from problem definition, data set selection and curation, model training and deployment emphasizing that bias exists across a spectrum and is a sequela of a combination of both human and machine factors.

Practical Approaches to Advancing Health Equity in Radiology, From the AJR Special Series on DEI

Despite significant advances in health care, many patients from medically under-served populations are impacted by existing health care disparities. Radiologists are uniquely positioned to decrease health disparities and advance health equity efforts in their practices. However, literature on practical tools for advancing radiology health equity efforts applicable to a wide variety of patient populations and care settings is lacking. Therefore, this article seeks to equip radiologists with an evidence-based and practical knowledge tool kit of health equity strategies, presented in terms of four pillars of research, clinical care, education, and innovation. For each pillar, equity efforts across diverse patient populations and radiology practice settings are examined through the lens of existing barriers, current best practices, and future directions, incorporating practical examples relevant to a spectrum of patient populations. Health equity efforts provide an opportune window to transform radiology through personalized care delivery that is responsive to diverse patient needs. Guided by compassion and empathy as core principles of health equity, the four pillars provide a helpful framework to advance health equity efforts as a step toward social justice in health.

Racial and ethnic differences in the use of lumbar imaging, opioid analgesics and spinal surgery for low back pain: A systematic review and meta-analysis

BACKGROUND AND OBJECTIVE

There is a substantial gap between evidence and clinical care for low back pain (LBP) worldwide despite recommendations of best practice specified in clinical practice guidelines. The aim of this systematic review was to identify disparities associated with race or ethnicity in the use of lumbar imaging, opioid analgesics, and spinal surgery in people with LBP.

DATABASES AND DATA TREATMENT

We included observational studies which compared the use of lumbar imaging, opioid analgesics, and spinal surgery for the management of non-serious LBP between people from different racial/ethnic populations. We searched in MEDLINE, EMBASE and CINAHL from January 2000 to June 2021. Risk of bias of included studies was appraised in six domains. For each type of care, we pooled data stratified by race and ethnicity using random effects models.

RESULTS

We identified 13 eligible studies; all conducted in the United States. Hispanic/Latino (OR 0.69, 95%CI 0.49-0.96) and Black/African American (OR 0.59, 95%CI 0.46-0.75) people with LBP were less likely to be prescribed opioid analgesics than White people. Black/African Americans were less likely to undergo or be recommended spinal surgery for LBP (OR 0.47, 95%CI 0.33-0.67) than White people. There was a lack of high certainty evidence on racial/ethnic disparities in the use of lumbar imaging.

CONCLUSION

This review reveals lower rate of the use of guideline-discordant care, especially opioid prescription and spinal surgery, in racial/ethnic minority populations with LBP in the United States. Future studies in other countries evaluating care equity for LBP are warranted. PROSPERO Registration ID: CRD42021260668.

SIGNIFICANCE

This systematic review and meta-analysis revealed that people with low back pain from the minority racial/ethnic backgrounds were less likely to be prescribed opioid analgesics and undergo spinal surgery than the majority counterparts. Strategic interventions to improve the access to, and the value of, clinical care for minority populations with low back pain are warranted.

Healthcare Disparities and Upper Gastrointestinal Bleeding: Exploring the Linkages

Introduction Upper gastrointestinal bleeding (UGIB) refers to blood loss from a gastrointestinal (GI) source proximal or above the ligament of Treitz. Health equity means giving everyone an equal chance to achieve optimal health by addressing injustices, overcoming barriers, and eliminating health disparities. Healthcare providers must analyze racial and ethnic disparities in UGIB management to ensure all patients receive equal care. Identifying risk factors in specific populations leads to tailored interventions that improve outcomes. Our study aims to examine trends and identify disparities in upper gastrointestinal bleeding across races and ethnicities to promote health equity. Methods Retrospective data on upper gastrointestinal bleeding from June 2009 to June 2022 were collected and categorized into five groups based on race. The baseline characteristics of each group were matched to ensure equitable comparison. A joinpoint regression model was used to compare incidence trends, identifying potential healthcare disparities for different racial/ethnic groups over time. Patients aged 18-75 who suffered from upper gastrointestinal bleeding at Nassau University Medical Center in New York from 2010 to 2021 were selected, excluding those with incomplete baseline comorbidity information. Results This study examined 5103 cases of upper gastrointestinal bleeding, with 41.9% female. The cohort was diverse, with 29.4% African American, 15.6% Hispanic, 45.3% White, 6.8% Asian, and 2.9% of other races. Data were split into two groups; 49.9% occurred between 2009 and 2015 and 50.1% between 2016 and 2022. Findings showed increased UGIB among Hispanics and decreased bleeding among Asians during 2016-2021 compared to 2009-2015. However, no significant difference was found for African Americans, Whites, and other races. In addition, Hispanics had a rise in the annual percentage change (APC) rate, whereas Asians had a decrease. Conclusion Our study examined trends in upper gastrointestinal bleeding and potential healthcare disparities across races and ethnicities. Our findings highlight an increased incidence of UGIB in Hispanics and a decreased incidence in Asians. Additionally, we identified a significant increase in the annual percentage change rate in Hispanics and a decrease in Asians over time. Our study underscores the importance of identifying and addressing disparities in UGIB management to promote health equity. Future research can build on these findings to develop tailored interventions that improve patient outcomes.

A Framework for Developing Health Equity Initiatives in Radiology

PURPOSE

In recent years, radiology departments have increasingly recognized the extent of health care disparities related to imaging and image-guided interventions. The goal of this article is to provide a framework for developing a health equity initiative in radiology and to articulate key defining factors.

METHODS

This article leverages the experience of three academic radiology departments and explores key principles that emerged when observing the experiences of these departments that have begun to engage in health equity-focused work.

RESULTS

A four-component framework is described for a health equity initiative in radiology consisting of (1) environmental scan and blueprint, (2) design and implementation, (3) initiative evaluation, and (4) community engagement. Key facilitators include a comprehensive environmental scan, early stakeholder engagement and consensus building, implementation science design thinking, and multitiered community engagement.

CONCLUSIONS

All radiology organizations should strive to develop, pilot, and evaluate novel initiatives that promote equitable access to high-quality imaging services. Establishing systems for high-quality data collection is critical to success. An implementation science approach provides a robust framework for developing and testing novel health equity initiatives in radiology. Community engagement is critical at all stages of the health equity initiative time line.

Practical, epistemic and normative implications of algorithmic bias in healthcare artificial intelligence: a qualitative study of multidisciplinary expert perspectives

BACKGROUND

There is a growing concern about artificial intelligence (AI) applications in healthcare that can disadvantage already under-represented and marginalised groups (eg, based on gender or race).

OBJECTIVES

Our objectives are to canvas the range of strategies stakeholders endorse in attempting to mitigate algorithmic bias, and to consider the ethical question of responsibility for algorithmic bias.

METHODOLOGY

The study involves in-depth, semistructured interviews with healthcare workers, screening programme managers, consumer health representatives, regulators, data scientists and developers.

RESULTS

Findings reveal considerable divergent views on three key issues. First, views on whether bias is a problem in healthcare AI varied, with most participants agreeing bias is a problem (which we call the bias-critical view), a small number believing the opposite (the bias-denial view), and some arguing that the benefits of AI outweigh any harms or wrongs arising from the bias problem (the bias-apologist view). Second, there was a disagreement on the strategies to mitigate bias, and who is responsible for such strategies. Finally, there were divergent views on whether to include or exclude sociocultural identifiers (eg, race, ethnicity or gender-diverse identities) in the development of AI as a way to mitigate bias.

CONCLUSION/SIGNIFICANCE

Based on the views of participants, we set out responses that stakeholders might pursue, including greater interdisciplinary collaboration, tailored stakeholder engagement activities, empirical studies to understand algorithmic bias and strategies to modify dominant approaches in AI development such as the use of participatory methods, and increased diversity and inclusion in research teams and research participant recruitment and selection.

How We Got Here: The Legacy of Anti-Black Discrimination in Radiology

Current disparities in the access to diagnostic imaging for Black patients and the underrepresentation of Black physicians in radiology, relative to their representation in the general U.S. population, reflect contemporary consequences of historical anti-Black discrimination. These disparities have existed within the field of radiology and professional medical organizations since their inception. Explicit and implicit racism against Black patients and physicians was institutional policy in the early 20th century when radiology was being developed as a clinical medical field. Early radiology organizations also embraced this structural discrimination, creating strong barriers to professional Black radiologist involvement. Nevertheless, there were numerous pioneering Black radiologists who advanced scholarship, patient care, and diversity within medicine and radiology during the early 20th century. This work remains important in the present day, as race-based health care disparities persist and continue to decrease the quality of radiology-delivered patient care. There are also structural barriers within radiology affecting workforce diversity that negatively impact marginalized groups. Multiple opportunities exist today for antiracism work to improve quality of care and to apply standards of social justice and health equity to the field of radiology. An initial step is to expand education on the disparities in access to imaging and health care among Black patients. Institutional interventions include implementing community-based outreach and applying antibias methodology in artificial intelligence algorithms, while systemic interventions include identifying national race-based quality measures and ensuring imaging guidelines properly address the unique cancer risks in the Black patient population. These approaches reflect some of the strategies that may mutually serve to address health care disparities in radiology. ^© RSNA, 2023 See the invited commentary by Scott in this issue. Quiz questions for this article are available in the supplemental material.

Relationship between Race and Access to Newer Mammographic Technology in Women with Medicare Insurance

Background Racial disparities in breast cancer mortality have been reported. Mammographic technology has undergone two major technology transitions since 2000: first, the transition from screen-film mammography (SFM) to full-field digital mammography (FFDM) and second, the transition to digital breast tomosynthesis (DBT). Purpose To examine the relationship between use of newer mammographic technology and race in women receiving mammography services. Materials and Methods This was a multiyear (January 2005 to December 2020) retrospective study of women aged 40-89 years with Medicare fee-for-service insurance who underwent mammography. Data were obtained using a 5% research identifiable sample of all Medicare fee-for-service beneficiaries. Within-institution and comparable-institution use of mammographic technology between Black women or women of other races and White women were assessed with multivariable logistic and linear regression, respectively, adjusted for age, race, Charlson comorbidity index, per capita income, urbanicity, and institutional capability. Results Between 2005 and 2020, there were 4 028 696 institutional mammography claims for women (mean age, 72 years ± 8 [SD]). Within an institution, the odds ratio (OR) of Black women receiving digital mammography rather than SFM in 2005 was 0.80 (95% CI: 0.70, 0.91; P < .001) when compared with White women; these differences remained until 2009. Compared with White women, the use of DBT within an institution was less likely for Black women from 2015 to 2020 (OR, 0.84; 95% CI: 0.81, 0.87; P < .001). Across institutions, there were racial differences in digital mammography use, which followed a U-shaped pattern, and the differences peaked at 3.8 percentage points less for Black compared with White women (95% CI: -6.1, -1.6; P = .001) in 2011 and then decreased to 1.2 percentage points less (95% CI: -2.2, -0.2; P = .02) in 2016. Conclusion In the Medicare population, Black women had less access to new mammographic imaging technology compared with White women for both the transition from screen-film mammography to digital mammography and then for the transition to digital breast tomosynthesis. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Lee and Lawson in this issue.

Lost to Follow-Up: A Nationwide Analysis of Patients With Transient Ischemic Attack Discharged From Emergency Departments With Incomplete Imaging

PURPOSE

Imaging guidelines for transient ischemic attack (TIA) recommend that patients undergo urgent brain and neurovascular imaging within 48 hours of symptom onset. Prior research suggests that most patients with TIA discharged from the emergency department (ED) do not complete recommended TIA imaging workup during their ED encounters. The purpose of this study was to determine the nationwide percentage of patients with TIA discharged from EDs with incomplete imaging workup who complete recommended imaging after discharge.

METHODS

Patients discharged from EDs with the diagnosis of TIA were identified from the Medicare 5% sample for 2017 and 2018 using International Classification of Diseases, tenth rev, Clinical Modification codes. Imaging performed was identified using Current Procedural Terminology codes. Incomplete imaging workup was defined as a TIA encounter without cross-sectional brain, brain-vascular, and neck-vascular imaging performed within the subsequent 30 days of the initial ED encounter. Patient- and hospital-level factors associated with incomplete TIA imaging were analyzed in a multivariable logistic regression.

RESULTS

In total, 6,346 consecutive TIA encounters were analyzed; 3,804 patients (59.9%) had complete TIA imaging workup during their ED encounters. Of the 2,542 patients discharged from EDs with incomplete imaging, 761 (29.9%) completed imaging during the subsequent 30 days after ED discharge. Among patients with TIA imaging workup completed after ED discharge, the median time to completion was 5 days. For patients discharged from EDs with incomplete imaging, the odds of incomplete TIA imaging at 30 days after discharge were highest for black (odds ratio, 1.84; 95% confidence interval, 1.27-2.66) and older (≥85 years of age; odds ratio, 2.41; 95% confidence interval, 1.78-3.26) patients. Reference values were age cohort 65 to 69 years; male gender; white race; no co-occurring diagnoses of hypertension, hyperlipidemia, or diabetes mellitus; household income > $63,029; hospital in the Northeast region; urban hospital location; hospital size > 400 beds; academically affiliated hospital; and facility with access to MRI.

CONCLUSIONS

Most patients discharged from EDs with incomplete TIA imaging workup do not complete recommended imaging within 30 days after discharge.