Equitable implementation of innovations to promote successful aging in place

INTRODUCTION

The United States population is growing older and more racially diverse. In 2015, Black, Indigenous, and other persons of color comprised 22% of the older adult population, and by 2060, this is expected to rise to 43%.¹ Thus, hospital and public health systems, surrounding communities, policymakers, and society will grapple with how to manage a growing and diversifying aging population requiring more complex and costly care for social, mental, and physical needs.² Meeting these needs is essential to allowing older adults to achieve outcomes most meaningful to them.

Among the most important outcomes for older adults are maintaining functional independence, social participation, and community living—collectively termed “Aging-in-Place.” Successful Aging-in-Place honors older adults' preferences for how they receive services, participate in care, and are included and respected in the home and community.³ To optimize Aging-in-Place, researchers have developed and tested aging innovations designed to enhance care for older adults, with delayed institutionalization as a distal outcome and Aging-in-Place as a long-term vision.⁴ Many aging innovations have undergone rigorous empirical testing for effectiveness in improving aging-related outcomes. Emerging attention in the field has prompted researchers to develop or adapt innovations to comprehensively and equitably address the needs, strengths, and preferences of racially and ethnically marginalized populations.^5-7 However, even evidence-based innovations developed with equity in mind may not translate to equitable implementation because of different contextual barriers experienced by a diverse population of older adults. The lack of equitable implementation may further reinforce health disparities⁸ that challenge the ability of the growing diversified aging population to successfully Age-in-Place. Accordingly, the purpose of this paper is to: (1) define the concept of “equitable implementation” and note current equity gaps in aging research and (2) present a customizable research logic model that can guide the equitable implementation and scaling of aging innovations.

IMPROVING THE EQUITABLE IMPLEMENTATION OF AGING INNOVATIONS

Health equity refers to an individual's opportunity to attain their full health potential regardless of their socially-determined circumstances.⁹ Inequity refers to disparities that are unjust and avoidable, resulting in further disadvantage to historically marginalized populations. Health inequities often manifest across racial, ethnic, or socioeconomic lines and can be a result of discriminatory behaviors by healthcare clinicians or structural disadvantages (e.g., access to healthcare, racism).⁸ Broadly defined, equitable implementation includes the provision of innovations in a manner that is fair and just and leads to improved outcomes for recipients, communities, and systems.¹⁰

Equitable implementation of evidence-based aging innovations has yet to be realized for older adults who experience frequent and complex transitions in care across the healthcare continuum. For example, home- and community-based services are designed to delay or prevent the need for institutionalization. Yet, little evidence has supported the extent to which Black and Hispanic older adults find these services valuable, acceptable, or appropriate, impacting the extent to which evidence-based care reaches and effectively impacts these populations.⁸ As another example, a qualitative study examined factors influencing access to and use of the Program of All Inclusive Care for the Elderly (PACE) by racially marginalized populations.¹¹ PACE has been shown to assist in prolonging community living and thereby promoting Aging-in-Place for nursing-home eligible adults. The authors found PACE staff identified challenges in recruiting people who are non-English speaking and/or have different cultures. As a result, those marginalized individuals may go to other, less clinically effective programs due to these cultural barriers. Finally, a study showed non-English speaking older adults within an Age Friendly health system were 2.3 times less likely than those who were English speaking to receive advanced care planning (ACP),¹² an evidence-based practice to allow expression of preferences for medical care. Collectively, these studies suggest that evidence-based innovations available in health and social service systems may not be equitably implemented in a way that meets the needs, strengths, or preferences of marginalized populations. This discordance impacts Aging-in-Place as both individuals and families may struggle with navigating decisions regarding where and how they receive care when changes in function and health occur, despite the availability of evidence-based innovations designed to help in these situations.

A LOGIC MODEL TO ADVANCE THE EQUITABLE IMPLEMENTATION OF AGING INNOVATIONS

The implementation research logic model¹³ provides a structured approach to conceptualizing and designing implementation studies. Below, we describe the four central activities of an adapted logic model informed by the Health Equity Implementation Framework^{14, 15} to guide empirical inquiry and advance equitable implementation of aging innovations (Figure 1).

FIGURE 1

Applied research logic model for the equitable implementation of advanced care planning (ACP) to promote Aging-in-Place.

Identifying equitable implementation determinants

First, identifying determinants (barriers or facilitators) of equitable implementation is a process best guided by existing implementation theories, models, and/or frameworks. In the context of health equity, the Health Equity Implementation Framework categorizes the most salient implementation determinants at one or more of the following interacting factors: clinical encounter, innovation, recipients, context, and societal influence (see Table 1 for definitions).^{14, 15}

TABLE 1. Health equity implementation framework determinant factors and definitions

Factors of implementation	Definition
Clinical encounter	Interaction between patient and clinicians that influence discussion of shared and patient-centered goals
Innovation	The practice, intervention, program, or policy being implemented and adopted
Recipients	Individuals who influence implementation or are impacted by implementation outcomes
Context	Multi-level factors such as resources, culture, local, organizational, or system structure
Social influence	Forces outside the healthcare system that include economies, physical structures, and sociopolitical forces.

• Note: Definitions are drawn from the original health equity implementation framework.^{14, 15}

Selecting equitable implementation strategies

Understanding determinants of equitable—or inequitable—implementation allows researchers to select implementation strategies that address these determinants, thereby improving the delivery of high-quality care or services.¹⁶ Implementation strategies may be defined as the methods or techniques used to support the uptake of evidence-based innovations¹⁷ and can directly pair one-to-one with corresponding factors or be grouped to crosscut one or more determinant factors. Before and during their deployment, these implementation strategies should be vetted and refined by representative community groups to ensure all partners involved in implementation efforts know, believe in, and deliver culturally responsive care or services.¹⁸

Identifying hypothesized mechanisms of change

Careful examination of mechanisms helps researchers understand why an implementation strategy did or did not lead to equitable implementation or how (in)equitable implementation influenced individual or population-level outcomes.¹⁹ Understanding and measuring the mechanistic link between strategies and outcomes are essential to interpreting outcomes and adapting implementation strategies to promote the equitable implementation of aging innovations.

Evaluating outcomes

The extent to which equitable implementation is achieved can be measured through the assessment of outcomes across (1) the individual (older adult), (2) implementation, and (3) population levels. As an example of a framework to guide the measurement of outcomes at the implementation level, we encourage researchers to reference the foundational Implementation Outcomes Framework by Proctor and colleagues.¹⁶

APPLICATION OF THE EQUITABLE IMPLEMENTATION LOGIC MODEL

To demonstrate the applied use of the equitable implementation logic model (Figure 1), we expand upon the health inequity mentioned previously between the use of ACP in racially and ethnically diverse patient populations who are non-English speaking.¹² Of note, the determinants in the model are not linear or hierarchical, but interactive and weighed differently based on the contextual factors of the study. For this illustrative example, we start with the determinants at the clinical encounter and then move outwards toward the societal context. In determinants of equitable implementation in a clinical encounter, clinicians often rely on medical interpreters to facilitate communication with non-English speakers during the clinical encounter. However, both the clinician and interpreter may not be trained in the cultural nuances that play a role in ACP discussions. For example, the word “hospice” in Spanish may have negative connotations as a place where people are institutionalized and abandoned before death,²⁰ which is often discordant with desires and preferences to successfully Age-in-Place. To address this determinant, an equitable implementation strategy to enhance the clinical encounter may be to train clinicians and interpreters on culturally appropriate ways to discuss advanced directives by bringing in stakeholders from those marginalized communities to explore their experiences with ACP. As a result, a hypothesized mechanisms of change may include an increase in positive interactions between clinicians, interpreters, and patients, which may foster an equitable context in which ACP occurs to successfully integrate patient or family preferences for care. Measurable outcomes include: individual (quality of life at the end-of-life), implementation (acceptability of staff training on culturally appropriate delivery of advanced care planning), and population (comparable rates of advanced care planning between older adults who regardless of language). Figure 1 further outlines determinants at the other four levels, corresponding equitable implementation strategies, hypothesized mechanisms, and outcomes.

CONCLUSION

Despite the critical importance of ensuring equitable implementation across evidence-based interventions, practices, and policies, approaches to advance equity in the aging field have yet to be clearly established. This gap jeopardizes the ability of aging innovations to reach and positively impact successful Aging-in-Place across diverse older adult populations, particularly those in racial or ethnically marginalized groups who are at the greatest risk for institutionalization. The proposed logic model provides the research community a preliminary tool to guide (1) the development of aging innovations in empirical studies, so they are well positioned to rapidly implement equitably and (2) equitable implementation of previously established aging innovations for broader reach and more substantial impact on Aging-in-Place. Integration of implementation science with aging innovations will lead to the development, implementation, and evaluation of equitable innovations that support Aging-in-Place for all older adult populations, especially those most marginalized.

“Despite the critical importance of ensuring equitable implementation across evidence-based interventions, practices, and policies, approaches to advance equity in the aging field have yet to be clearly established.”

AUTHOR CONTRIBUTIONS

All authors had a role in conceptualization of the manuscript and preparing the manuscript for submission.

ACKNOWLEDGMENTS

The authors thank Drs. Eva N. Woodward and Geoffrey M. Curran for their expert review and comments on this manuscript. The authors also extend their sincere gratitude to Roger M. Gustavson for his unwavering support throughout all phases of this manuscript's conceptualization, development, and refinement.

FUNDING INFORMATION

Dr. Gustavson is supported by the Agency for Healthcare Research and Quality (AHRQ) and Patient-Centered Outcomes Research Institute (PCORI) (K12HS026379), National Institutes of Health's National Center for Advancing Translational Sciences (KL2TR002492), and the Minneapolis Veterans Affairs Center of Innovation, Center for Care Delivery and Outcomes Research (CIN 13-406). Dr. Vincenzo is supported by the National Institutes of Health's (NIH) National Center for Advancing Translational Sciences grants KL2TR003108, UL1 TR003107 and NIH/National Institutes of Aging (NIA) grant K76AG074920, Dr. Miller is supported by the National Institutes of Health (KL2TR001870). Dr. Falvey is supported by NIH/NIA K76AG074926. Dr. Lee is supported by the NIH Clinical Translational Science Awards grant UL1TR00037 and the NIH/NIA K23AG072042. The views expressed in this article are those of the authors and do not necessarily reflect the position or policy of the Department of Veterans Affairs or the United States Government, AHRQ, PCORI, NCATS, or Minnesota Learning Health System Mentored Career Development Program (MN-LHS).

CONFLICT OF INTEREST

The views expressed in this article are those of the authors and do not necessarily reflect the position or policy of the Department of Veterans Affairs or the United States Government, AHRQ, PCORI, or Minnesota Learning Health System Mentored Career Development Program (MN-LHS).

SPONSOR'S ROLE

The sponsors had no role in influencing this publication.