Effect of bioprosthetic leaflet anisotropy on stent dynamics of Transcatheter Aortic Valve Replacement devices.

The assessment of stent fatigue in Transcatheter Aortic Valve Replacement (TAVR) systems is critical for the design of next-generation devices, both in vitro and in vivo. The mechanical properties of the bioprosthetic heart valves (BHVs) have a significant impact on the fatigue life of the metallic stent and thus must be taken into consideration when evaluating new TAVR device designs. This study aims to investigate the relationship between BHV anisotropic behaviour and the asymmetric deflections of the stent frame observed during in vitro testing. An explicit dynamics finite element model of the nitinol stent with attached bioprosthetic valve leaflets was developed to evaluate the deflections of the TAVR device under haemodynamic loading. Our results demonstrate that pericardium behaviour plays a dominant role in determining stent frame deflection. The anisotropic behaviour of the leaflets, resulting from collagen fibre orientation, affects the extent of deflection encountered by each commissure of the frame. This leads to asymmetric variation in frame deflection that can influence the overall fatigue life of the nitinol stent. This study highlights the importance of considering both the flexible nature of the metallic stent as well as the leaflet anisotropic behaviour in the design and fatigue assessment of TAVR systems.

Opportunities for psychologists to advance health equity: Using liberation psychology to identify key lessons from 17 years of praxis.

Health and health care inequities persist because the efforts to eliminate them have ignored structural racism, typically using a power neutral approach to diagnose and solve the problem. Critical theory can address many of the conceptual weaknesses of current approaches, help identify how racism operates in health care, and open the door for more effective individual employee and organizational actions to advance health equity. We apply Martín-Baró's (1996) liberation psychology to lessons we learned through implementing a transdisciplinary national health and health care equity program. The program, which began in 2005, conducts equity-focused health services interventions and research, using the best available evidence to assist health and health care policymakers, payers, community-based organizations, care delivery organizations, and patients to transform and align their activities in order to advance health equity. It serves as a rare model to explore how misconceptions resulting from racist structures can hinder progress, even when everyone involved is highly motivated to address health and health care inequities. Liberation psychology guides our interpretation of the lessons learned and recommendations for the field of psychology. Psychologists advancing equity in health and health care should integrate liberation psychology and other critical theories into their own work. In addition, partnerships with other disciplines and communities outside of academia and professional health services are key to success. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Advancing health equity through partnerships of state Medicaid agencies, Medicaid managed care organizations, and health care delivery organizations.

Background: Reducing health inequities in marginalized populations, including people with Medicaid insurance, requires care transformation to address medical and social needs that is supported and incentivized by tailored payment methods. Collaboration across health care stakeholders is essential to overcome health system fragmentation and implement sustainable reform in the United States (U.S.). This paper explores how multi-stakeholder teams operationalized the Roadmap to Advance Health Equity model during early stages of their journey to (a) build cultures of equity and (b) integrate health equity into care transformation and payment reform initiatives. Methods: Advancing Health Equity: Leading Care, Payment, and Systems Transformation is a national program in the U.S. funded by the Robert Wood Johnson Foundation that brings together multi-stakeholder teams to design and implement initiatives to advance health equity. Each team consisted of representatives from state Medicaid agencies, Medicaid managed care organizations, and health care delivery organizations in seven U.S. states. Between June and September 2021, semi-structured interviews were conducted with representatives (n = 23) from all seven teams about experiences implementing the Roadmap to Advance Health Equity model with technical assistance from Advancing Health Equity. Results: Facilitators of building cultures of equity included (1) build upon preexisting intra-organizational cultures of equity, (2) recruit and promote diverse staff and build an inclusive culture, and (3) train staff on health equity and anti-racism. Teams faced challenges building inter-organizational cultures of equity. Facilitators of identifying a health equity focus area and its root causes included (1) use data to identify a health equity focus and (2) overcome stakeholder assumptions about inequities. Facilitators of implementing care transformation and payment reform included (1) partner with Medicaid members and individual providers and (2) support and incentivize equitable care and outcomes with payment. Facilitators of sustainability planning included (1) identify evidence of improved health equity focus and (2) maintain relationships among stakeholders. Teams faced challenges determining the role of the state Medicaid agency. Conclusions: Multi-stakeholder teams shared practical strategies for implementing the Roadmap to Advance Health Equity that can inform future efforts to build intra- and inter-organizational cultures of equity and integrate health equity into care delivery and payment systems.

Sparse spatially clustered coefficient model via adaptive regularization.

Large spatial datasets with many spatial covariates have become ubiquitous in many fields in recent years. A question of interest is to identify which covariates are likely to influence a spatial response, and whether and how the effects of these covariates vary across space, including potential abrupt changes from region to region. To solve this question, a new efficient regularized spatially clustered coefficient (RSCC) regression approach is proposed, which could achieve variable selection and identify latent spatially heterogeneous covariate effects with clustered patterns simultaneously. By carefully designing the regularization term of RSCC as a chain graph guided fusion penalty plus a group lasso penalty, the RSCC model is computationally efficient for large spatial datasets while still achieving the theoretical guarantees for estimation. RSCC also adopts the idea of adaptive learning to allow for adaptive weights and adaptive graphs in its regularization terms and further improves the estimation performance. RSCC is applied to study the acceptance of COVID-19 vaccines using county-level data in the United States and discover the determinants of vaccination acceptance with varying effects across counties, revealing important within-state and across-state spatially clustered patterns of covariates effects.

Developing Standards for Cultural Competency Training for Health Care Providers to Care for Lesbian, Gay, Bisexual, Transgender, Queer, Intersex, and Asexual Persons: Consensus Recommendations from a National Panel.

Purpose: Lesbian, gay, bisexual, transgender, queer, intersex, and/or asexual and other sexual and gender diverse persons (LGBTQIA+ or SGD persons) experience barriers to equitable health care. The purpose of this article is to describe a collaborative process that resulted in core cultural competency recommendations addressing training for those who provide health care and/or social services to LGBTQIA+ patients. Methods: In 2018 and 2019, Whitman-Walker Health, a Federally Qualified Community Health Center in Washington, DC, and the National LGBT Cancer Network purposively selected leaders of community clinics and community-based organizations, cultural competency trainers, and clinicians and researchers with expertise in SGD health with diverse lived experiences to develop consensus-based cultural competency recommendations. Recommendations were developed through a synthesis of peer-reviewed studies, publicly accessible curricula, and evaluations of SGD cultural competency trainings; two in-person convenings; and iterative feedback from diverse stakeholders. Results: Five anchoring recommendations emerged: (1) know your audience; (2) develop and fine-tune the curriculum; (3) employ both adult and transformational learning theories; (4) choose multiple effective trainers; and (5) evaluate impact of training. These recommendations promote an ongoing process of individual and organizational improvement and a stance of humility rather than competence to be mastered. Conclusion: By setting core cultural competency standards for all persons involved in health care and social services, these recommendations complement existing clinical competency recommendations to advance SGD health equity.

Critical Theory, Culture Change, and Achieving Health Equity in Health Care Settings.

Achieving optimal health for all requires confronting the complex legacies of colonialism and white supremacy embedded in all institutions, including health care institutions. As a result, health care organizations committed to health equity must build the capacity of their staff to recognize the contemporary manifestations of these legacies within the organization and to act to eliminate them. In a culture of equity, all employees-individually and collectively-identify and reflect on the organizational dynamics that reproduce health inequities and engage in activities to transform them. The authors describe 5 interconnected change strategies that their medical center uses to build a culture of equity. First, the medical center deliberately grounds diversity, equity, and inclusion efforts (DEI) in critical theory, aiming to illuminate social structures through critical analysis of power relations. Second, its training goes beyond cultural competency and humility to include critical consciousness, which includes the ability to critically analyze conditions in the organizational and broader societal contexts that produce health inequities and act to transform them. Third, it works to strengthen relationships so they can be change vehicles. Fourth, it empowers an implementation team that models a culture of equity. Finally, it aligns equity-focused culture transformation with equity-focused operations transformation to support transformative praxis. These 5 strategies are not a panacea. However, emerging processes and outcomes at the medical center indicate that they may reduce the likelihood of ahistorical and power-blind approaches to equity initiatives and provide employees with some of the critical missing knowledge and skills they need to address the root causes of health inequity.

Framework for Integrating Equity Into Machine Learning Models: A Case Study.

Predictive analytic models leveraging machine learning methods increasingly have become vital to health care organizations hoping to improve clinical outcomes and the efficiency of care delivery for all patients. Unfortunately, predictive models could harm populations that have experienced interpersonal, institutional, and structural biases. Models learn from historically collected data that could be biased. In addition, bias impacts a model's development, application, and interpretation. We present a strategy to evaluate for and mitigate biases in machine learning models that potentially could create harm. We recommend analyzing for disparities between less and more socially advantaged populations across model performance metrics (eg, accuracy, positive predictive value), patient outcomes, and resource allocation and then identify root causes of the disparities (eg, biased data, interpretation) and brainstorm solutions to address the disparities. This strategy follows the lifecycle of machine learning models in health care, namely, identifying the clinical problem, model design, data collection, model training, model validation, model deployment, and monitoring after deployment. To illustrate this approach, we use a hypothetical case of a health system developing and deploying a machine learning model to predict the risk of mortality in 6 months for patients admitted to the hospital to target a hospital's delivery of palliative care services to those with the highest mortality risk. The core ethical concepts of equity and transparency guide our proposed framework to help ensure the safe and effective use of predictive algorithms in health care to help everyone achieve their best possible health.

Development, implementation, and use of an "equity lens" integrated into an institutional quality scorecard.

Few healthcare provider organizations systematically track their healthcare equity, and fewer enable direct interaction with such data by their employees. From May to August 2019, we enhanced the data architecture and reporting functionality of our existing institutional quality scorecard to allow direct comparisons of quality measure performance by gender, age, race, ethnicity, language, zip code, and payor. The Equity Lens was made available to over 4000 staff in September 2019 for 82 institutional quality measures. During the first 11 months, 235 unique individuals used the tool; users were most commonly from the quality and equity departments. Two early use cases evaluated hypertension control and readmissions by race, identifying potential inequities. This is the first description of an interactive equity lens integrated into an institutional quality scorecard made available to healthcare system employees. Early evidence suggests the tool is used and can inform quality improvement initiatives.

Second Dose of Epinephrine for Anaphylaxis in the First Aid Setting: A Scoping Review.

Anaphylaxis is a life-threatening hypersensitivity reaction where rapid, early administration of epinephrine (adrenaline) can be lifesaving in the first aid setting. There are instances where a single dose of epinephrine does not relieve symptoms and a second dose may be required to further mitigate symptoms and preserve life. We performed a scoping review as part of an update to a previously conducted International Liaison Committee on Resuscitation First Aid Task Force (ILCOR) review. PubMed and Embase were searched using the strategy from the 2015 ILCOR review (dates January 1, 2015 to October 22, 2019) and a review of the grey literature (all dates up to November 18, 2019) was performed to identify data on the requirement, use, and effectiveness of a second dose of epinephrine. Each search was rerun on June 26, 2020. We included all human studies of adults and children with an English abstract. Critical outcomes included resolution of symptoms, adverse effects, and complications of second dosing of epinephrine in the treatment of acute anaphylaxis. Included studies are presented descriptively. Our updated search identified 909 potential sources, 890 from the published literature and 19 from the grey literature. After full text review, two studies met our eligibility criteria (Campbell et al. and Akari et al.). For the outcome of resolution of symptoms, both studies found that two or more doses of epinephrine were required in 8% of 582 patients and 28% of 18 patients, respectively, with anaphylaxis requiring treatment with epinephrine. The other a priori outcomes were not reported. This scoping review identified limited evidence regarding the use of a second dose of epinephrine for anaphylaxis in the first aid setting, however, due to the potential benefit, it is reasonable to administer a second dose when symptoms of severe anaphylaxis fail to resolve following an initial dose. Given the potential mortality associated with anaphylaxis, further research is needed to better identify individuals who may benefit from a second dose of epinephrine.

Teaching Intersectionality of Sexual Orientation, Gender Identity, and Race/Ethnicity in a Health Disparities Course.

Introduction: Intersectionality considers how different identities simultaneously affect an individual's experiences. Those of multiple minority statuses may experience effects of intersecting systems of oppression. Most health disparities curricula do not focus on intersectionality. We studied the impact of an innovative module teaching intersectionality of sexual orientation, gender identity, and race/ethnicity issues in the required Pritzker School of Medicine course Health Care Disparities: Equity and Advocacy. Methods: A short lecture reviewed sexual and gender minority (SGM) health disparities, intersectionality, minority stress, and shared decision making (SDM) to establish shared language among 83 first-year medical students. Students then viewed four videos of SGM patients of color (POC) describing their health care experiences, each followed by moderated discussion about how compounded minority stress affects lived experiences and health and how to improve SDM for SGM POC. One video interviewee attended the session and answered students' questions. Evaluation was performed using pre- and postsurveys. Results: Feeling somewhat/completely confident in defining intersectionality increased from 57% to 96%. Prior to the session, 62% of respondents reported feeling somewhat/completely confident in identifying barriers to care for SGM patients, and 92% after. Thirty-three percent felt somewhat/completely confident in asking SGM patients about their identities before the session, and 81% after. Eighty-four percent rated the session as very good or excellent. Discussion: The session was well received, improved student knowledge of intersectionality, and improved confidence in communicating with and caring for SGM patients. Future iterations could include condensing the lecture and including a patient panel and/or small-group discussion.

Healthcare Experiences of Transgender People of Color.

BACKGROUND: Transgender people and racial/ethnic minorities separately report poor healthcare experiences. However, little is known about the healthcare experiences of transgender people of color (TPOC), who are both transgender and racial/ethnic minorities. OBJECTIVE: To investigate how TPOC healthcare experiences are shaped by both race/ethnicity and gender identity. DESIGN AND PARTICIPANTS: Semi-structured, in-depth individual interviews (n = 22) and focus groups (2; n = 17 total); all taken from a sample of TPOC from the Chicago area. All participants completed a quantitative survey (n = 39). APPROACH: Interviews and focus groups covered healthcare experiences, and how these were shaped by gender identity and/or race/ethnicity. The interviews and focus groups were audio recorded, transcribed verbatim, and imported into HyperRESEARCH software. At least two reviewers independently coded each transcript using a codebook of themes created following grounded theory methodology. The quantitative survey data captured participants' demographics and past healthcare experiences, and were analyzed with descriptive statistics. KEY RESULTS: All participants described healthcare experiences where providers responded negatively to their race/ethnicity and/or gender identity. A majority of participants believed they would be treated better if they were cisgender or white. Participants commonly cited providers' assumptions about TPOC as a pivotal factor in negative experiences. A majority of participants sought out healthcare locations designated as lesbian, gay, bisexual, and transgender (LGBT)-friendly in an effort to avoid discrimination, but feared experiencing racism there. A minority of participants expressed a preference for providers of color; but a few reported reluctance to reveal their gender identity to providers of their own race due to fear of transphobia. When describing positive healthcare experiences, participants were most likely to highlight providers' respect for their gender identity. CONCLUSIONS: TPOC have different experiences compared with white transgender or cisgender racial/ethnic minorities. Providers must improve understanding of intersectional experiences of TPOC to improve quality of care.

Bivalent rLP2086 (Trumenba®): Development of a well-characterized vaccine through commercialization.

The phrase "Process is the Product" is often applied to biologics, including multicomponent vaccines composed of complex components that evade complete characterization. Vaccine production processes must be defined and locked early in the development cycle to ensure consistent quality of the vaccine throughout scale-up, clinical studies, and commercialization. This approach of front-loading the development work helped facilitate the accelerated approval of the Biologic License Application for the well-characterized vaccine bivalent rLP2086 (Trumenba®, Pfizer Inc) in 2014 under Breakthrough Therapy Designation. Bivalent rLP2086 contains two rLP2086 antigens and is licensed for the prevention of meningococcal meningitis disease caused by Neisseria meningitidis serogroup B in individuals 10-25years of age in the United States. This paper discusses the development of the manufacturing process of the two antigens for the purpose of making it amenable to any manufacturing facility. For the journey to commercialization, the operating model used to manage this highly accelerated program led to a framework that ensured "right the first time" execution, robust process characterization, and proactive process monitoring. This framework enabled quick problem identification and proactive resolutions, resulting in a robust control strategy for the commercial process.

Two Wrongs Make a Right: Addressing Underreporting in Binary Data from Multiple Sources.

Media-based event data-i.e., data comprised from reporting by media outlets-are widely used in political science research. However, events of interest (e.g., strikes, protests, conflict) are often underreported by these primary and secondary sources, producing incomplete data that risks inconsistency and bias in subsequent analysis. While general strategies exist to help ameliorate this bias, these methods do not make full use of the information often available to researchers. Specifically, much of the event data used in the social sciences is drawn from multiple, overlapping news sources (e.g., Agence France-Presse, Reuters). Therefore, we propose a novel maximum likelihood estimator that corrects for misclassification in data arising from multiple sources. In the most general formulation of our estimator, researchers can specify separate sets of predictors for the true-event model and each of the misclassification models characterizing whether a source fails to report on an event. As such, researchers are able to accurately test theories on both the causes of and reporting on an event of interest. Simulations evidence that our technique regularly out performs current strategies that either neglect misclassification, the unique features of the data-generating process, or both. We also illustrate the utility of this method with a model of repression using the Social Conflict in Africa Database.

Solving Disparities Through Payment And Delivery System Reform: A Program To Achieve Health Equity.

Payment systems generally do not directly encourage or support the reduction of health disparities. In 2013 the Finding Answers: Solving Disparities through Payment and Delivery System Reform program of the Robert Wood Johnson Foundation sought to understand how alternative payment models might intentionally incorporate a disparities-reduction component to promote health equity. A qualitative analysis of forty proposals to the program revealed that applicants generally did not link payment reform tightly to disparities reduction. Most proposed general pay-for-performance, global payment, or shared savings plans, combined with multicomponent system interventions. None of the applicants proposed making any financial payments contingent on having successfully reduced disparities. Most applicants did not address how they would optimize providers' intrinsic and extrinsic motivation to reduce disparities. A better understanding of how payment and care delivery models might be designed and implemented to reduce health disparities is essential.

A Model of Organizational Context and Shared Decision Making: Application to LGBT Racial and Ethnic Minority Patients.

Shared decision making (SDM) occurs when patients and clinicians work together to reach care decisions that are both medically sound and responsive to patients' preferences and values. SDM is an important tenet of patient-centered care that can improve patient outcomes. Patients with multiple minority identities, such as sexual orientation and race/ethnicity, are at particular risk for poor SDM. Among these dual-minority patients, added challenges to clear and open communication include cultural barriers, distrust, and a health care provider's lack of awareness of the patient's minority sexual orientation or gender identity. However, organizational factors like a culture of inclusion and private space throughout the visit can improve SDM with lesbian, gay, bisexual, and transgender ("LGBT") racial/ethnic minority patients who have faced stigma and discrimination. Most models of shared decision making focus on the patient-provider interaction, but the health care organization's context is also critical. Context-an organization's structure and operations-can strongly influence the ability and willingness of patients and clinicians to engage in shared decision making. SDM is most likely to be optimal if organizations transform their contexts and patients and providers improve their communication. Thus, we propose a conceptual model that suggests ways in which organizations can shape their contextual structure and operations to support SDM. The model contains six drivers: workflows, health information technology, organizational structure and culture, resources and clinic environment, training and education, and incentives and disincentives. These drivers work through four mechanisms to impact care: continuity and coordination, the ease of SDM, knowledge and skills, and attitudes and beliefs. These mechanisms can activate clinicians and patients to engage in high-quality SDM. We provide examples of how specific contextual changes could make SDM more effective for LGBT racial/ethnic minority populations, focusing especially on transformations that would establish a safe environment, build trust, and decrease stigma.

Surgical pulmonary embolectomy in a community hospital.

BACKGROUND: Surgical pulmonary embolectomy (SPE) is indicated for a pulmonary embolism associated with hemodynamic instability. A review of the literature demonstrates that most studies of SPE are conducted at large academic medical centers. This series is from a 325-bed community hospital. METHODS: A retrospective chart review was performed of patients undergoing SPE from January 2008 to December 2012. All patients aged >18 years were reviewed for 30-day mortality, length of hospital stay, comorbidities, and preoperative hemodynamic parameters. RESULTS: Fifteen patients (7 men and 8 women; median age, 55.5 years; range, 20-72 years) underwent SPE. There were 2 deaths (13.3%). Four of the patients underwent catheter-directed interventions before SPE. The mean length of hospital stay was 12 days. CONCLUSIONS: These data suggest that SPE is associated with favorable outcomes in the appropriate community setting, and the mortality rate seen in this study compares favorably with the nationwide average of 27.2%.

A roadmap and best practices for organizations to reduce racial and ethnic disparities in health care.

Over the past decade, researchers have shifted their focus from documenting health care disparities to identifying solutions to close the gap in care. Finding Answers: Disparities Research for Change, a national program of the Robert Wood Johnson Foundation, is charged with identifying promising interventions to reduce disparities. Based on our work conducting systematic reviews of the literature, evaluating promising practices, and providing technical assistance to health care organizations, we present a roadmap for reducing racial and ethnic disparities in care. The roadmap outlines a dynamic process in which individual interventions are just one part. It highlights that organizations and providers need to take responsibility for reducing disparities, establish a general infrastructure and culture to improve quality, and integrate targeted disparities interventions into quality improvement efforts. Additionally, we summarize the major lessons learned through the Finding Answers program. We share best practices for implementing disparities interventions and synthesize cross-cutting themes from 12 systematic reviews of the literature. Our research shows that promising interventions frequently are culturally tailored to meet patients' needs, employ multidisciplinary teams of care providers, and target multiple leverage points along a patient's pathway of care. Health education that uses interactive techniques to deliver skills training appears to be more effective than traditional didactic approaches. Furthermore, patient navigation and engaging family and community members in the health care process may improve outcomes for minority patients. We anticipate that the roadmap and best practices will be useful for organizations, policymakers, and researchers striving to provide high-quality equitable care.