Scaling-up Evidence-based Interventions for Communities of Color With Marked Health Disparities: Lessons Learned From COVID-19 Can Be Applied to Reduce Morbidity and Mortality and Achieve Health Equity

BACKGROUND

Existing research has established the promise of multilevel evidence-based interventions (MEBIs/EBIs) to reduce the severity of noncommunicable (ie, hypertension, sickle cell disease)1–4 and communicable disease5 among various racial and ethnic groups. Moreover, over the past decade studies related to racial and ethnic representation in which participatory communication centered on effective dialogue between researchers and community stakeholders with the goal of creating an equitable partnership for health and social change has increased.6 However, as the world continued to grapple with mitigating the COVID-19 pandemic, until early 2022, the utilization of equitable-based approaches was seldom in the social discourse.7,8

The broad adoption and scale-up of MEBIs to reach communities with marked health disparities was slow due to several factors (eg, slow mobilization of state and federal resources to communities of color to mitigate the impact of COVID, decreased implementation of MEBI in Black and Brown communities).9 The delayed implementation of MEBI in communities of color resulted in significantly increased disease burden and mortality; moreover, the increased mortality also translated to reductions in life expectancy.10 Between 2019 and 2021, US life expectancy declined by 2.7 years, with most of the decline (66.7%) occurring in the first year of the COVID-19 pandemic10; over 1 million residents within the United States have succumbed to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is far more than any country.10 From 2019 to 2021, large disparities were seen in the loss of life expectancy. The non-Hispanic American Indian Alaska Native (AIAN) population lost 6.6 years, followed by the Hispanic population with a loss of 4.2 years, the non-Hispanic Black population with a loss of 4.0 years, the non-Hispanic White population with a loss of 2.4 years, and the non-Hispanic Asian population with a loss of 2.1 years.10 Furthermore, COVID-19 was the leading cause contributing negatively to the change in life expectancy. Non-Hispanic Black and non-Hispanic AIAN populations experienced 82.5% and 71.2% of their declines during the first year of the pandemic,10 which suggests that if evidence-based mitigation strategies were imposed earlier in the pandemic, many lives could have been saved. This data suggests that for communities of color, implementation of essential public health interventions at the patient, provider, and organizational levels and scaling up those MEBI would have been critical life-saving strategies for closing the clinical evidence-to-practice gap. The delay in this critical step was a high cost for many communities during the early stages of the COVID-19 pandemic, resulting in higher mortality among communities of color.11

SCALE-UP IS AN ESSENTIAL COMPONENT IN IMPLEMENTATION RESEARCH

Scalability is defined by ExpandNet/WHO as “deliberate efforts to increase the impact of successfully tested health innovations so as to benefit more people and to foster policy and programme development on a lasting basis,”12 Scalability entails, “taking an intervention that is known to be effective and applying it more broadly in other health care settings and/or with additional patient population”13; moreover developing a translatable scale-up process for use in implementation research is a nascent area that is underresearched. In that vein, scalability/scale-up remains an emerging area of implementation research with few assessment instruments. Currently, only 4 checklists exist for scale-up,14–17 and these tools have not been adequately adapted for use in communities of color. Most researchers must develop ad hoc tools suitable for the specific project. When planning for scalability, it is important to consider these elements (ie, intervention cost, intervention innovation, resource team, infrastructure or environment, organization/users, and policy context)12 that are likely to influence the scale-up process. Scale-up may be facilitated and/or hindered by many factors including; the evidence of benefit that the intervention provides; demand for the intervention; compatibility with the cultural norms and values; how quickly the impact of the intervention is observed; complexity of the intervention, and how well the intervention aligns with the strategic aims of the existing health care system or target community. Furthermore, the integration of impact, process evaluation, and outcome evaluation plans into intervention protocols is essential for scale-up data harmonization, although often underreported in the literature.18

Bringing to scale EBI has bidirectional benefits for communities of color and the scientific community. Nevertheless, to accomplish this significant challenge, researchers need additional guidance on strategies and tools for scaling-up EBI especially for communities of color with populations disproportionately burdened with comorbid health conditions, complicated by limited access to adequate care due to structural inequalities. Considering the burden of racial discrimination experienced by communities of color (ie, Blacks, Hispanics, Asians) in the United States, a health equity lens is needed to ensure promotion and adoption of equity-responsive health programs designed to address disparities and reduce the detrimental impact of communicable and noncommunicable disease and its sequelae. Racial discrimination has been defined as unfair treatment received because of one’s ethnicity, race, or culture of origin, and adversely affect physical and mental health.19 William and colleagues describe the detrimental effects of racism and racial discrimination on health suggesting that race matters even after socioeconomic factors are considered, as risks and resources are systematically patterned by race, ethnicity, and socioeconomic status.20 This impacts health care–seeking behavior and access to services for low-resource populations.21 Therefore, a systems thinking approach that addresses the social determinants of health (economic stability, social and community context, neighborhood and built environment, health care, and education) at the systems, provider, and patient level may reduce excess morbidity and mortality resulting from comorbid diseases, and improve the overall quality of life and advancement of health equity. Guided by the health equity implementation framework,22 we discuss the various dimensions of scalability and the importance of stakeholder engagement throughout the intervention design and implementation process to increase the likelihood of the scale-up process being feasible and acceptable.

CONCEPTUAL FRAMEWORKS FOR SCALE-UP OF EVIDENCE-BASED INTERVENTION AND RECOMMENDATIONS

When considering scale-up efforts, within communities of color, we advocate for the use of the Health Equity Implementation Framework, which integrates and modifies the Integrated-Promoting Action on Research Implementation in Health Services (i-PARIHS), and the Health Care Disparities Framework, to explain multilevel factors (ie, patient, provider, the clinical encounter, and the health care system) contributing to unwarranted differences in health care for vulnerable populations to elucidate and address factors impacting health equity.22 The Health Equity Implementation Framework integrates the aforementioned frameworks into implementation research via examination of the interaction between the intervention, recipients (patients/provider) during the clinical encounter, and the sociopolitical environment which impacts implementation.22 The success of the implementation requires an active facilitation process or robust implementation strategy with relationship building at its core to address health disparities and promote sustainable change.

Few papers have addressed the importance of using an implementation lens to assess the lessons learned from COVID-19 for various aspects of the pandemic response (eg, contact tracing and community engagement), moreover, there is little discussion on health equity.23,24 Our recommendations for implementation strategies25 focus on promoting scalability with an emphasis on strong stakeholder engagement for communities of color using COVID-19 as a case study.

Furthermore, we can also utilize the Health Equity Implementation Framework1; to understand patient, provider, and organizational/systems level factors interactions with societal influences and how it has impacted the scale-up of EBI for COVID-19 screening, testing, prevention, and treatment. The following scalability dimensions including innovation/intervention characteristics, resource team, and environment are embedded within the components of the Health Equity Implementation Framework: Intervention characteristics, provider factors, context or clinical encounter, and patient factors26—were likely to impact the adoption of COVID-19 mitigation strategies and its potential for scalability.22,26 Although conceptual frameworks for individuals unfamiliar with health equality might seem formidable, the following recommendations are provided as a lessons learned for researchers unfamiliar with the use of the aforementioned frameworks.

RECOMMENDATION 1: IDENTIFY ESSENTIAL INTERVENTION CHARACTERISTICS THAT ARE NECESSARY FOR IMPLEMENTATION AND SCALE-UP OF EVIDENCE-BASED INTERVENTION

During the peak of COVID-19, a range of mitigation strategies were being implemented to reduce transmission in the community and among health care workers (ie, testing, contact tracing, social distance, self-quarantine); and health care systems changes and robust treatment procedures to prevent nosocomial spread (isolation of infected individuals).24,27 Although these preventative strategies were evidence-based, adoption was slow and reach was suboptimal among communities of color. Successful scalability of an intervention requires: (1) considerations be made to ensure cost-effectiveness; (2) the intervention is simple to understand; and (3) implementation should be tailored to the implementation context.28 Our ability to strategically scale-up EBI for COVID-19 and reduce morbidity and mortality and the economic burden of treating the virus was significantly hampered by the inability to scale-up MEBI due to costs of some COVID treatment.29,30 Nonetheless, interventions should be designed and implemented with the recipients (eg, communities of color) at the center if the goal is to reduce morbidity/mortality. COVID-19 has taught many researchers/clinicians/policymaker that31 identifying the essential elements of the intervention is critical because that component can be adapted to different context and scaled.12 Lessons learned from COVID-19, include a focus on the importance of the essential intervention components and how adaptable those components are to various settings. Moreover, an essential part of the discussion has also included scalability of interventions and equity. Pre-COVID, the thought among implementation research about scalability of interventions was confined to global health, but the post-COVID world is now focusing on scalability of interventions among individuals of various economic strata in the United States.31

RECOMMENDATION 2: BUILDING INFRASTRUCTURES THAT INCORPORATE FLEXIBILITY AND ALLOWS FOR SCALABILITY DURING TIMES OF NATIONAL CRISIS

Capacity building of health care professionals was essential for the appropriate delivery of medical services to high-risk populations during the COVID-19 pandemic and for future global disease outbreaks. COVID-19 demonstrated that there was a need for robust training systems that were adaptable for providers’ needs. Adaptability of health care systems required sharply increased level of intensive care, and respiratory therapy to safely manage mechanical ventilation for COVID-19 patients. Future pandemics might require different skillsets. Hence, the ability to augment the training system to the identified needs will be essential for mitigation strategies for any future global disease outbreak. Furthermore, public health workers will require training in implementation strategies to assess intervention effectiveness, implementation and service outcomes as recommended by Proctor et al32 to ensure greater intervention reach, uptake/adoption, and long-term sustainment. Infrastructure development will need to include cultural competency training for health educators to enable dissemination of preventative information to populations with low health literacy to avoid misinformation.28 Practitioners should apply the WHO Risk communication and community engagement readiness and response guidance while disseminating recommendations.33 To facilitate appropriate risk communication and provide conditions that promote sustained health behavior changes among communities of color, training of health care professionals in the social determinants of health and cultural competency in health care delivery is pertinent.34 Finally, promoting diversity in institutional leadership for health professionals and policymakers is essential. The lessons learned from COVID-19 exposed rigid health systems which cost lives as recalcitrant to incorporation of emerging EBI because of the inflexible of the existing infrastructure and not necessary because of the staff. In a time of crisis, inflexible systems have significant worse outcomes.35

RECOMMENDATION 3: DEVELOP EQUITABLE PARTNERSHIP FOR HEALTH AND TRANSPARENCY IN DECISION-MAKING BY BUILDING TRUST WITH EFFECTIVE DIALOGUE

The implementation context should focus on strengthening the patient-provider/implementor-intervention recipient/researcher-community communication led by culturally competent providers/researchers/policymakers. Ensuring that communities have the conditions for optimal health will require that disproportionately affected communities of color are at the decision-making tables, recognizing and if possible rectifying historically injustices—unequal living conditions, preexisting conditions, etc. and providing resources according to need. Many communities of color have a long collective memory of medical historically injustices.36,37 During COVID-19, there was missed opportunities to apply precautions to curtail the pandemic hindered by contextual challenges. Lessons learned from COVID-19 were that many of these barriers could have been addressed with strong public collaborations among communities and health care professionals guided by an equity framework. There is clearly a need to strengthen the health care community linkages if as implementors/public health professionals, our goals are to contain and prevent resurgence of COVID-19 and other future pandemics. Equitable partnerships built on trust are essential. Ensuring availability of sufficient human and material resources may nurture the scale-up process.

CONCLUSIONS

As President Joe Biden signed a resolution on April 11, 2023, ending the COVID-19 national emergency which was declared in January 31, 2020, under President Trump, we must heed the lessons learned from this moment in our history.38 In this commentary, we have provided the lessons learned from the COVID-19 pandemic from a health equity lens focused through a specific framework to illuminate reasons for disengagement of communities of color, and collaboratively provide recommendations that we believe could have bridged the differences in outcomes for SARS-CoV-2 for various communities of color in the United States. Identifying effective implementation strategies that may increase reach, promote and achieve health equity is essential for improving health outcomes and also strengthening the current health system. Our ability to successful scale MEBI/EBI for noncommunicable and communicable diseases through evidence-based research27 will advert additional morbidity and mortality for vulnerable communities39,40 and can improve our response to the next pandemic. This is feasible if researchers/implementors/policymakers are able to contextualize knowledge, attitudes, and culture, and approach health interventions with cultural sensitivity, innovation, and solidify community-health systems partnership. Moreover, sustain collaboration and equitable partnerships are needed to ensure that interventions reach communities with marked health disparities without further delay, to improve population health outcomes, and advance health equity. The pandemic has challenged us to create a more equitable standard for science, medicine, and public health and strengthen the health care infrastructure. We should also strive to innovatively bring care to the communities who need it the most.

REFERENCES 1. Agarwal R, Bills JE, Hecht TJ, et al. Role of home blood pressure monitoring in overcoming therapeutic inertia and improving hypertension control: a systematic review and meta-analysis. Hypertension. 2011;57:29–38. 2. De las Nueces D, Hacker K, DiGirolamo A, et al. A systematic review of community-based participatory research to enhance clinical trials in racial and ethnic minority groups. Health Serv Res. 2012;47(3pt 2):1363–1386. 3. Ogedegbe G, Schoenthaler A. A systematic review of the effects of home blood pressure monitoring on medication adherence. J Clin Hypertens (Greenwich). 2006;8:174–180. 4. Ogedegbe G, Gyamfi J, Plange-Rhule J, et al. Task shifting interventions for cardiovascular risk reduction in low-income and middle-income countries: a systematic review of randomised controlled trials. BMJ Open. 2014;4:e005983. 5. Questa K, Das M, King R, et al. Community engagement interventions for communicable disease control in low- and lower- middle-income countries: evidence from a review of systematic reviews. Int J Equity Health. 2020;19:51. 6. Julian McFarlane S, Occa A, Peng W, et al. Community-Based Participatory Research (CBPR) to enhance participation of racial/ethnic minorities in clinical trials: a 10-year systematic review. Health Commun. 2022;37:1075–1092. 7. Vasan A, Foote M, Long T. Ensuring widespread and equitable access to treatments for COVID-19. JAMA. 2022;328:705–706. 8. White House. Executive order on ensuring an equitable pandemic response and recovery; 2021. 9. DeSalvo K, Hughes B, Bassett M. Public health COVID-19 impact assessment: lessons learned and compelling needs. NAM Perspect. 2021;2021:1–29. 10. Arias E, Tejada-Vera B, Kochanek KD, et al. Provisional life expectancy estimates for 2021; 2022. 11. Mackey K, Ayers CK, Kondo KK, et al. Racial and ethnic disparities in COVID-19-related infections, hospitalizations, and deaths: a systematic review. Ann Intern Med. 2021;174:362–373. 12. WHO/ExpandNet. ExpandNet—Advancing the science and practice of scale up; 2010. 13. Zullig LL, Gellad WF, Moaddeb J, et al. Improving diabetes medication adherence: successful, scalable interventions. Patient preference and adherence. 2015;9:139–149. 14. Cooley LLJ Taking innovations to scale: methods, applications and lessons. Washington DC: Management Systems International; 2014. 15. Milat A, Lee K, Conte K, et al. Intervention Scalability Assessment Tool: a decision support tool for health policy makers and implementers. Health Res Policy Syst. 2020;18:1. 16. Cooley LKR, Ved R Scaling up—from vision to large scale change: a management framework for practitioners. Management Systems International; 2016. 17. WHO. Beginning with the end in mind: planning pilot projects and other programmatic research for successful scaling up; 2011. Accessed April 20, 2023. https://expandnet.net/PDFs/ExpandNet-WHO%20-%20Beginning%20with%20the%20end%20in%20mind%20-%202011.pdf. 18. Zamboni K, Schellenberg J, Hanson C, et al. Assessing scalability of an intervention: why, how and who? Health Policy Plan. 2019;34:544–552. 19. Viswanathan M, Kraschnewski JL, Nishikawa B, et al. Outcomes and costs of community health worker interventions: a systematic review. Med Care. 2010;48:792–808. 20. Williams DR, Lawrence JA, Davis BA. Racism and health: evidence and needed research. Ann Rev Public Health. 2019;40:105–125. 21. Hasnain-Wynia R, Baker DW, Nerenz D, et al. Disparities in health care are driven by where minority patients seek care: examination of the hospital quality alliance measures. Arch Intern Med. 2007;167:1233–1239. 22. Woodward EN, Matthieu MM, Uchendu US, et al. The health equity implementation framework: proposal and preliminary study of hepatitis C virus treatment. Implement Sci. 2019;14:26. 23. Means AR, Wagner AD, Kern E, et al. Implementation science to respond to the COVID-19 pandemic. Front Public Health. 2020;8:462. 24. Wensing M, Sales A, Armstrong R, et al. Implementation science in times of COVID-19. Implement Sci. 2020;15:42. 25. Shelby T, Schenck C, Weeks B, et al. Lessons learned from COVID-19 contact tracing during a public health emergency: a prospective implementation study. Front Public Health. 2021;9:721952. 26. Wyatt R, Laderman M, Botwinick L, et al. Achieving health equity: a guide for health care organizations. IHI White Paper. Cambridge, MA: Institute for Healthcare Improvement; 2016. 27. Wilder-Smith A, Chiew CJ, Lee VJ. Can we contain the COVID-19 outbreak with the same measures as for SARS? Lancet Infect Dis. 2020;20:e102–e107. 28. Chambers DA. Considering the intersection between implementation science and COVID-19. Implement Res Pract. 2020;1:0020764020925994. 29. Healthcare Finance. Hospitalized care for COVID-19 averages $34,662 to $45,683, varying by age; 2020. 30. Lopez L III, Hart LH III, Katz MH. Racial and ethnic health disparities related to COVID-19. JAMA. 2021;325:719–720. 31. Muttamba W, O’Hare BA, Saxena V, et al. A systematic review of strategies adopted to scale up COVID-19 testing in low-, middle- and high-income countries. BMJ Open. 2022;12:e060838. 32. Proctor EK, Landsverk J, Aarons G, et al. Implementation research in mental health services: an emerging science with conceptual, methodological, and training challenges. Adm Policy Ment Health. 2009;36:24–34. 33. World Health Organization. Risk communication and community engagement readiness and response to coronavirus disease (COVID-19): interim guidance, 19 March 2020; 2020. 34. Brottman MR, Char DM, Hattori RA, et al. Toward cultural competency in health care: a scoping review of the diversity and inclusion education literature. Acad Med. 2020;95:803–813. 35. Cook TM, Camporota L. Critical care outcomes from COVID-19: patients, interventions, healthcare systems and the need for core datasets. Anaesthesia. 2021;76:1155–1158. 36. Byrd WM, Clayton LA. Race, medicine, and health care in the United States: a historical survey. J Natl Med Assoc. 2001;93(suppl):11s–34s. 37. Nuriddin A, Mooney G, White AIR. Reckoning with histories of medical racism and violence in the USA. Lancet. 2020;396:949–951. 38. NPR. Biden ends COVID national emergency after Congress acts; 2023. Accessed April 20, 2023. https://www.npr.org/2023/04/11/1169191865/biden-ends-covid-national-emergency. 39. Ogedegbe G, Ravenell J, Adhikari S, et al. Assessment of racial/ethnic disparities in hospitalization and mortality in patients with COVID-19 in New York City. JAMA Netw Open. 2020;3:e2026881. 40. Artiga S, Garfield R, Orgera K. Communities of color at higher risk for health and economic challenges due to COVID-19; 2020.

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