Towards a common lexicon for equity, diversity, and inclusion work in academic medicine.

Differential rewarding of work and experience has been a longtime feature of academic medicine, resulting in a series of academic disparities. These disparities have been collectively called a cultural or minority "tax," and, when considered beyond academic medicine, exist across all departments, colleges, and schools of institutions of higher learning-from health sciences to disciplines located on university campuses outside of medicine and health. A shared language can provide opportunities for those who champion this work to pool resources for larger impacts across the institution. This article aims to catalog the terms used across academic medicine disciplines to establish a common language describing the inequities experienced by Black, Latinx, American Indian/Alaska Native and Native Hawaiian/Other Pacific Islander, Women, and other underrepresented people as well as queer, disabled, and other historically marginalized or excluded groups. These ideas are specific to academic medicine in the United States, although many can be used in academic medicine in other countries. The terms were selected by a team of experts in equity, diversity, and inclusion, (EDI) who are considered national thought leaders in EDI and collectively have over 100 years of scholarship and experience in this area.

Developing an Inclusive and Welcoming LGBTQ Clinic.

People who identify as lesbian, gay, bisexual, transgender, queer, and questioning (LGBTQ) are underserved and face barriers to knowledgeable health care. Most health systems are ill prepared to provide care that addresses the needs of the LGBTQ community. Basic steps to developing an LGBTQ welcoming health care program are presented. It can be adapted to diverse health care models, from obstetrics and gynecology and other primary care services whether public or private and to hospitals and specialty clinics. This LGBTQ inclusive health care model was developed in collaboration with the LGBTQ community, a multidisciplinary team of health care providers, and professionals of Law and Information Technology.

Promoting Equity In Clinical Decision Making: Dismantling Race-Based Medicine.

As the use of artificial intelligence has spread rapidly throughout the US health care system, concerns have been raised about racial and ethnic biases built into the algorithms that often guide clinical decision making. Race-based medicine, which relies on algorithms that use race as a proxy for biological differences, has led to treatment patterns that are inappropriate, unjust, and harmful to minoritized racial and ethnic groups. These patterns have contributed to persistent disparities in health and health care. To reduce these disparities, we recommend a race-aware approach to clinical decision support that considers social and environmental factors such as structural racism and social determinants of health. Recent policy changes in medical specialty societies and innovations in algorithm development represent progress on the path to dismantling race-based medicine. Success will require continued commitment and sustained efforts among stakeholders in the health care, research, and technology sectors. Increasing the diversity of clinical trial populations, broadening the focus of precision medicine, improving education about the complex factors shaping health outcomes, and developing new guidelines and policies to enable culturally responsive care are important next steps.

The CTSA Diversity, Equity, Inclusion, and Accessibility (DEIA) Task Force's recommendations for the CTSA program consortium.

The Clinical and Translational Science Award (CTSA) Program recognizes that advancing diversity, equity, inclusion, and accessibility (DEIA) requires moving beyond statements of commitment to transformative actions. In 2021, the CTSA Program created a Task Force (TF) to initiate work in support of structural and transformational initiatives that advance DEIA for the consortium and its individual hubs. We describe the process of forming the expertise-driven (DEIA) TF and our activities to date. We 1) developed and adopted the DEIA Learning Systems Framework to guide our approach; 2) defined a set of recommendations across four focus areas (Institutional; Programmatic; Community-Centered; and Social, Cultural, Environmental); and 3) designed and disseminated a survey to capture the CTSA Program's baseline demographic, community, infrastructural, and leadership diversity. The CTSA Consortium also elevated the TF to a standing Committee to extend our understanding, development, and implementation of DEIA approaches to translational and clinical science. These initial steps provide a foundation for collectively fostering environment that support DEIA across the research continuum.

Future Doctors From Underrepresented in Medicine Communities at the University of Utah.

Background and Objectives: Future Doctors (FD), a high school pathway program, was developed to address the lack of compositional diversity in the health professions at our health sciences campus. Methods: We obtained, analyzed, and compared data on FD student demographic and educational achievement at undergraduate and graduate programs at the University of Utah and graduate programs at other institutions to non-FD students. We followed students from high school to graduate school. Results: We analyzed data from 1,897 FD participants (2014-2019). FD participants were 71% women, with 50.3% identifying as students of color. Ninety-eight students matriculated in graduate school, with 75 (76%) remaining at University of Utah and 45 (46%) attending health sciences graduate programs. Conclusions: FD student cohorts are more diverse than those in the University of Utah undergraduate and graduate programs, contributing to the diversity of those programs. More research is needed to ensure that graduate school gains are evidenced in all underrepresented groups.

Guiding Principles to Address the Impact of Algorithm Bias on Racial and Ethnic Disparities in Health and Health Care.

Importance: Health care algorithms are used for diagnosis, treatment, prognosis, risk stratification, and allocation of resources. Bias in the development and use of algorithms can lead to worse outcomes for racial and ethnic minoritized groups and other historically marginalized populations such as individuals with lower income. Objective: To provide a conceptual framework and guiding principles for mitigating and preventing bias in health care algorithms to promote health and health care equity. Evidence Review: The Agency for Healthcare Research and Quality and the National Institute for Minority Health and Health Disparities convened a diverse panel of experts to review evidence, hear from stakeholders, and receive community feedback. Findings: The panel developed a conceptual framework to apply guiding principles across an algorithm's life cycle, centering health and health care equity for patients and communities as the goal, within the wider context of structural racism and discrimination. Multiple stakeholders can mitigate and prevent bias at each phase of the algorithm life cycle, including problem formulation (phase 1); data selection, assessment, and management (phase 2); algorithm development, training, and validation (phase 3); deployment and integration of algorithms in intended settings (phase 4); and algorithm monitoring, maintenance, updating, or deimplementation (phase 5). Five principles should guide these efforts: (1) promote health and health care equity during all phases of the health care algorithm life cycle; (2) ensure health care algorithms and their use are transparent and explainable; (3) authentically engage patients and communities during all phases of the health care algorithm life cycle and earn trustworthiness; (4) explicitly identify health care algorithmic fairness issues and trade-offs; and (5) establish accountability for equity and fairness in outcomes from health care algorithms. Conclusions and Relevance: Multiple stakeholders must partner to create systems, processes, regulations, incentives, standards, and policies to mitigate and prevent algorithmic bias. Reforms should implement guiding principles that support promotion of health and health care equity in all phases of the algorithm life cycle as well as transparency and explainability, authentic community engagement and ethical partnerships, explicit identification of fairness issues and trade-offs, and accountability for equity and fairness.

Electronic Health Record-Integrated Clinical Decision Support for Clinicians Serving Populations Facing Health Care Disparities: Literature Review.

OBJECTIVES: To review current studies about designing and implementing clinician-facing clinical decision support (CDS) integrated or interoperable with an electronic health record (EHR) to improve health care for populations facing disparities. METHODS: We searched PubMed to identify studies published between January 1, 2011 and October 22, 2021 about clinician-facing CDS integrated or interoperable with an EHR. We screened abstracts and titles and extracted study data from articles using a protocol developed by team consensus. Extracted data included patient population characteristics, clinical specialty, setting, EHR, clinical problem, CDS type, reported user-centered design, implementation strategies, and outcomes. RESULTS: There were 28 studies (36 articles) included. Most studies were performed at safety net institutions (14 studies) or Indian Health Service sites (6 studies). CDS tools were implemented in primary care outpatient settings in 24 studies (86%) for screening or treatment. CDS included point-of-care alerts (93%), order facilitators (46%), workflow support (39%), relevant information display (36%), expert systems (11%), and medication dosing support (7%). Successful outcomes were reported in 19 of 26 studies that reported outcomes (73%). User-centered design was reported during CDS planning (39%), development (32%), and implementation phase (25%). Most frequent implementation strategies were education (89%) and consensus facilitation (50%). CONCLUSIONS: CDS tools may improve health equity and outcomes for patients who face disparities. The present review underscores the need for high-quality analyses of CDS-associated health outcomes, reporting of user-centered design and implementation strategies used in low-resource settings, and methods to disseminate CDS created to improve health equity.

Establishing a multidisciplinary initiative for interoperable electronic health record innovations at an academic medical center.

OBJECTIVE: To establish an enterprise initiative for improving health and health care through interoperable electronic health record (EHR) innovations. MATERIALS AND METHODS: We developed a unifying mission and vision, established multidisciplinary governance, and formulated a strategic plan. Key elements of our strategy include establishing a world-class team; creating shared infrastructure to support individual innovations; developing and implementing innovations with high anticipated impact and a clear path to adoption; incorporating best practices such as the use of Fast Healthcare Interoperability Resources (FHIR) and related interoperability standards; and maximizing synergies across research and operations and with partner organizations. RESULTS: University of Utah Health launched the ReImagine EHR initiative in 2016. Supportive infrastructure developed by the initiative include various FHIR-related tooling and a systematic evaluation framework. More than 10 EHR-integrated digital innovations have been implemented to support preventive care, shared decision-making, chronic disease management, and acute clinical care. Initial evaluations of these innovations have demonstrated positive impact on user satisfaction, provider efficiency, and compliance with evidence-based guidelines. Return on investment has included improvements in care; over $35 million in external grant funding; commercial opportunities; and increased ability to adapt to a changing healthcare landscape. DISCUSSION: Key lessons learned include the value of investing in digital innovation initiatives leveraging FHIR; the importance of supportive infrastructure for accelerating innovation; and the critical role of user-centered design, implementation science, and evaluation. CONCLUSION: EHR-integrated digital innovation initiatives can be key assets for enhancing the EHR user experience, improving patient care, and reducing provider burnout.

Using Electronic Clinical Quality Measures (eCQMs) to Perform a Venous Thromboembolism Prophylaxis Rapid Cycle Quality Improvement Initiative.

BACKGROUND: At one institution, a clinical decision support (CDS) alert for venous thromboembolism (VTE) prophylaxis burdened providers but was considered vital to patient safety. Electronic clinical quality measures (eCQMs) incentivized the translation of quality measures into data elements within the electronic health record (EHR) and facilitated hospitalwide performance monitoring during CDS improvement. The aim was to reduce VTE alerts by 50% without compromising eCQM performance. METHODS: This quality improvement initiative was performed at a tertiary care academic medical center using an integrated EHR. Alert firings were revised in three rounds over a four-week transition period while monitoring VTE eCQM performance weekly. Postimplementation data were recorded for 12 weeks. Primary outcomes were VTE alerts per 100 admissions and VTE eCQM performance. Secondary outcomes were alert effectiveness (desired responses/patients), alert efficiency (desired responses/alerts), and dwell time (time between alert firing and provider addressing the alert). RESULTS: Alerts decreased from 157 to 74 per 100 admissions, a 52.9% reduction (p < 0.001). There was no change in eCQM compliance or the percentage of inpatients excluded from the VTE eCQM. Provider dwell time across the hospital dropped between 2.9 and 7.2 hours per day. After the interventions, alert effectiveness increased (66.1% to 73.3%; p < 0.001), but alert efficiency decreased (17.5% to 16.2%; p = 0.007) due to an increase in providers delaying definitive responses. CONCLUSION: Altering VTE alert criteria did not affect compliance with providing VTE prophylaxis to patients while reducing alert burden by more than 50%. Using preexisting quality data like eCQMs can facilitate near-time patient safety monitoring during quality improvement projects.

Activation and Utilization of an Electronic Health Record Patient Portal at an Academic Medical Center-Impact of Patient Demographics and Geographic Location.

The advent of the online electronic health record patient portal has provided an efficient and practical means for patients to become more involved in their health care. In this report, we analyze how demographic variables such as age, gender, race, and geographic location affect patient portal activation and usage at the University of Iowa Hospitals and Clinics, the sole academic medical center in the state of Iowa, a predominantly rural state. Our primary end points were activation of the patient portal (MyChart, Epic, Inc) and access of outpatient laboratory and radiology results, among the most commonly accessed and popular features of the patient portal. We thus analyzed data from 536 378 patients to determine rates of patient portal activation and data from 219 671 patient encounters to determine the frequency at which patients access their online diagnostic test results. Higher rates of patient portal activation and usage were associated with female gender, Caucasians/non-underrepresented minorities, geographic location in closer proximity to the medical center (Iowa City and neighboring cities/suburbs), and nonelderly adults. For underrepresented minority and rural patients, opportunities for improvement exist for both activation and more robust use of online patient portal accounts. Overall, these data highlight existing disparities with online patient portal usage and provide a base on which further studies and interventions can help to improve utilization of these systems.

Preferred Names, Preferred Pronouns, and Gender Identity in the Electronic Medical Record and Laboratory Information System: Is Pathology Ready?

BACKGROUND: Electronic medical records (EMRs) and laboratory information systems (LISs) commonly utilize patient identifiers such as legal name, sex, medical record number, and date of birth. There have been recommendations from some EMR working groups (e.g., the World Professional Association for Transgender Health) to include preferred name, pronoun preference, assigned sex at birth, and gender identity in the EMR. These practices are currently uncommon in the United States. There has been little published on the potential impact of these changes on pathology and LISs. METHODS: We review the available literature and guidelines on the use of preferred name and gender identity on pathology, including data on changes in laboratory testing following gender transition treatments. We also describe pathology and clinical laboratory challenges in the implementation of preferred name at our institution. RESULTS: Preferred name, pronoun preference, and gender identity have the most immediate impact on the areas of pathology with direct patient contact such as phlebotomy and transfusion medicine, both in terms of interaction with patients and policies for patient identification. Gender identity affects the regulation and policies within transfusion medicine including blood donor risk assessment and eligibility. There are limited studies on the impact of gender transition treatments on laboratory tests, but multiple studies have demonstrated complex changes in chemistry and hematology tests. A broader challenge is that, even as EMRs add functionality, pathology computer systems (e.g., LIS, middleware, reference laboratory, and outreach interfaces) may not have functionality to store or display preferred name and gender identity. CONCLUSIONS: Implementation of preferred name, pronoun preference, and gender identity presents multiple challenges and opportunities for pathology.

Variation in Results Release and Patient Portal Access to Diagnostic Test Results at an Academic Medical Center.

BACKGROUND: Electronic health records (EHRs) are commonplace in industrialized countries. Many hospitals are granting their patients access to their medical information through online patient portals. In this report, we describe a retrospective analysis of patient access to diagnostic test results released through the patient portal (MyChart; Epic, Inc.) at a state academic medical center. METHODS: We analyzed 6 months of data for anatomic pathology, clinical laboratory, and radiology test results to evaluate variations in results release (automated vs. manual) and subsequent patient access to the institutional patient portal. During this period, diagnostic test results were released for all patient encounters including inpatient units, outpatient clinics, and the emergency department. RESULTS: Manual results release by providers before automated release time occurred most commonly in the outpatient setting. The highest rates of access of diagnostic test results occurred for outpatients (about 30% overall view rate), females (two times or more compared to males in nearly every age bracket), and 20-45-year-old. Access rates of diagnostic tests in the emergency department or inpatient units were <10% across all populations. Access of diagnostic test results was very low for 12-17-year-old, likely influenced by institutional policies limiting parental proxy access within this pediatric age range. Approximately 20% of outpatient laboratory results were viewed by patients within 8 h of release from the EHR to the patient portal and 10% within 2 h of release. CONCLUSIONS: Patient accessing of diagnostic test results were generally higher for females, outpatients, and 20-45-year-old. Approximately, 20% of outpatient results were viewed quickly by patients after release to the EHR.

Diagnosis, antiretroviral therapy, and emergence of resistance to antiretroviral agents in HIV-2 infection: a review.

Human immunodeficiency virus type 1 (HIV-1) and type 2 (HIV-2) are the causative agents of AIDS. HIV-2 is prevalent at moderate to high rates in West African countries, such as Senegal, Guinea, Gambia, and Cape Verde. Diagnosis of HIV-2 is made with a positive HIV-1/HIV-2 ELISA or simple/rapid assay, followed by one or two confirmatory tests specific for HIV-2. Following CD(4)(+)T cell counts, HIV-2 viral burden and clinical signs and symptoms of immunodeficiency are beneficial in monitoring HIV-2 disease progression. Although non-nucleoside reverse transcriptase inhibitors are ineffective in treating HIV-2, nucleoside reverse transcriptase inhibitors and protease inhibitors can be effective in dual and triple antiretroviral regimens. Their use can decrease HIV-2 viral load, increase CD(4)(+)T cell counts and improve AIDS-related symptoms. HIV-2 resistance to various nucleoside reverse transcriptase inhibitors and protease inhibitors, including zidovudine, lamivudine, ritonivir and indinavir, has been identified in some HIV-2 infected patients on antiretroviral therapy. The knowledge of HIV-2 peculiarities, when compared to HIV-1, is crucial to helping diagnose and guide the clinician in the choice of the initial antiretroviral regimen and for monitoring therapy success.

Diagnosis, antiretroviral therapy, and emergence of resistance to antiretroviral agents in HIV-2 infection: a review

Human immunodeficiency virus type 1 (HIV-1) and type 2 (HIV-2) are the causative agents of AIDS. HIV-2 is prevalent at moderate to high rates in West African countries, such as Senegal, Guinea, Gambia, and Cape Verde. Diagnosis of HIV-2 is made with a positive HIV-1/HIV-2 ELISA or simple/rapid assay, followed by one or two confirmatory tests specific for HIV-2. Following CD4+ T cell counts, HIV-2 viral burden and clinical signs and symptoms of immunodeficiency are beneficial in monitoring HIV-2 disease progression. Although non-nucleoside reverse transcriptase inhibitors are ineffective in treating HIV-2, nucleoside reverse transcriptase inhibitors and protease inhibitors can be effective in dual and triple antiretroviral regimens. Their use can decrease HIV-2 viral load, increase CD4+ T cell counts and improve AIDS-related symptoms. HIV-2 resistance to various nucleoside reverse transcriptase inhibitors and protease inhibitors, including zidovudine, lamivudine, ritonavir and indinavir, has been identified in some HIV-2 infected patients on antiretroviral therapy. The knowledge of HIV-2 peculiarities, when compared to HIV-1, is crucial to helping diagnose and guide the clinician in the choice of the initial antiretroviral regimen and for monitoring therapy success