Maternal health equity in Georgia: a Delphi consensus approach to definition and research priorities.

BACKGROUND: Pregnancy-related mortality in the United States is the greatest among all high-income countries, and Georgia has one of the highest maternal mortality rates-almost twice the national rate. Furthermore, inequities exist in rates of pregnancy-related deaths. In Georgia, non-Hispanic Black women are nearly 3 times more likely to die from pregnancy-related complications than non-Hispanic White women. Unlike health equity, a clear definition of maternal health equity is lacking, overall and in Georgia specifically, but is needed to reach consensus and align stakeholders for action. Therefore, we used a modified Delphi method to define maternal health equity in Georgia and to determine research priorities based on gaps in understanding of maternal health in Georgia. METHODS: Thirteen expert members of the Georgia Maternal Health Research for Action Steering Committee (GMHRA-SC) participated in an iterative, consensus-driven, modified Delphi study comprised of 3 rounds of anonymous surveys. In round 1 (web-based survey), experts generated open-ended concepts of maternal health equity and listed research priorities. In rounds 2 (web-based meeting) and 3 (web-based survey), the definition and research priorities suggested during round 1 were categorized into concepts for ranking based on relevance, importance, and feasibility. Final concepts were subjected to a conventional content analysis to identify general themes. RESULTS: The consensus definition of maternal health equity created after undergoing the Delphi method is: maternal health equity is the ultimate goal and ongoing process of ensuring optimal perinatal experiences and outcomes for everyone as the result of practices and policies free of interpersonal or structural bias that tackle current and historical injustices, including social, structural, and political determinants of health impacting the perinatal period and life course. This definition highlights addressing the current and historical injustices manifested in the social determinants of health, and the structural and political structures that impact the perinatal experience. CONCLUSION: The maternal health equity definition and identified research priorities will guide the GMHRA-SC and the broader maternal health community for research, practice, and advocacy in Georgia.

Morehouse Choice Accountable Care Organization and Education System (MCACO-ES): Integrated Model Delivering Equitable Quality Care.

Accountable Care Organizations (ACOs) seek sustainable innovation through the testing of new care delivery methods that promote shared goals among value-based health care collaborators. The Morehouse Choice Accountable Care Organization and Education System (MCACO-ES), or (M-ACO) is a physician led integrated delivery model participating in the Medicare Shared Savings Program (MSSP) offered through the Centers for Medicare and Medicaid Services (CMS) Innovation Center. The MSSP establishes incentivized, performance-based payment models for qualifying health care organizations serving traditional Medicare beneficiaries that promote collaborative efficiency models designed to mitigate fragmented and insufficient access to health care, reduce unnecessary cost, and improve clinical outcomes. The M-ACO integration model is administered through participant organizations that include a multi-site community based academic practice, independent physician practices, and federally qualified health center systems (FQHCs). This manuscript aims to present a descriptive and exploratory assessment of health care programs and related innovation methods that validate M-ACO as a reliable simulator to implement, evaluate, and refine M-ACO's integration model to render value-based performance outcomes over time. A part of the research approach also includes early outcomes and lessons learned advancing the framework for ongoing testing of M-ACO's integration model across independently owned, rural, and urban health care locations that predominantly serve low-income, traditional Medicare beneficiaries, (including those who also qualify for Medicaid benefits (also referred to as "dual eligibles"). M-ACO seeks to determine how integration potentially impacts targeted performance results. As a simulator to test value-based innovation and related clinical and business practices, M-ACO uses enterprise-level data and advanced analytics to measure certain areas, including: 1) health program insight and effectiveness; 2) optimal implementation process and workflows that align primary care with specialists to expand access to care; 3) chronic care management/coordination deployment as an effective extender service to physicians and patients risk stratified based on defined clinical and social determinant criteria; 4) adoption of technology tools for patient outreach and engagement, including a mobile application for remote biometric monitoring and telemedicine; and 5) use of structured communication platforms that enable practitioner engagement and ongoing training regarding the shift from volume to value-based care delivery.

Discerning Disparities: The Data Gap.

Health disparities that focus on gender and on the ancillary dependent variables of race and ethnicity reflect continually early illness, compromised quality of life, and often premature and preventable deaths. The inability of the nation to eliminate disparities also track along race and gender in communities where a limited number of health-care providers and policymakers identify as being from these traditionally underserved and marginalized population groups. Epidemiologists and other researchers and analysts have traditionally failed to integrate the social determinants of health and other variables known to support upward mobility in their predictive analyses of health status. The poor, and poor men of color particularly, begin a descent to invisibility and separation that has been witnessed since the early days of this nation. This history has the majority of men of color mired in poverty or near poverty and has more substantively and explicitly affected both American Indians and Africans forced into immigration into the United States and into slavery. Other racial and ethnic groups including large distinct ethnic groups of Asian Americans and Hispanics/Latinx do not have their treatment by systems fully reported from a health and social justice perspective simply because the systems do not disaggregate by race and ethnicity. It is axiomatic that examining disparities through the lens of race, ethnicity, and gender provides a unique opportunity to reflect upon what is known about boys' and men's health, particularly men from communities of color, and about payment systems. Integration of all populations into the enumeration of morbidity, mortality, and disparity indices is a dynamic reflection of the vision and exclusive actions of decision makers.

Calculated metabolic equivalents: a tool for exercise prescription among African American women.

BACKGROUND: Average daily steps (ADS) are a low-technology measurement of activity that is useful for exercise prescription. However, research demonstrates poor validity for ADS as a measure of exercise capability. We present a superior low-technology measure of exercise capability, which is easily applied by practitioners in clinical or nonclinical settings. METHODS: Based on analysis of baseline data from an intervention study to test a sustainable approach to long-term physical activity improvement for employed African American women, between 2005 and 2008, we examined exercise tolerance metabolic equivalents (METs) and ADS of 158 participants and generated an alternative measure of exercise capacity. We conducted regression analysis to determine the impact of key health indicators on exercise capacity and examined associations between our predictive model and true (MET) exercise performance. RESULTS: Using our predictive equation, 79.33% of participants were correctly categorized (very high, high, medium) based on our tool, with 10 women (6.67%) mischaracterized by one level higher than actual MET achievement and 21(14.00%) mischaracterized as one category lower than actual MET achievement. In contrast, using ADS alone resulted in 22.15% correctly categorized participants. CONCLUSIONS: The proposed tool is superior to existing low-technology measures of exercise capacity while retaining strong utility in nonclinical and low-resource settings.