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OBM Geriatrics

(ISSN 2638-1311)

OBM Geriatrics is an international peer-reviewed Open Access journal published quarterly online by LIDSEN Publishing Inc. The journal takes the premise that innovative approaches – including gene therapy, cell therapy, and epigenetic modulation – will result in clinical interventions that alter the fundamental pathology and the clinical course of age-related human diseases. We will give strong preference to papers that emphasize an alteration (or a potential alteration) in the fundamental disease course of Alzheimer’s disease, vascular aging diseases, osteoarthritis, osteoporosis, skin aging, immune senescence, and other age-related diseases.

Geriatric medicine is now entering a unique point in history, where the focus will no longer be on palliative, ameliorative, or social aspects of care for age-related disease, but will be capable of stopping, preventing, and reversing major disease constellations that have heretofore been entirely resistant to interventions based on “small molecular” pharmacological approaches. With the changing emphasis from genetic to epigenetic understandings of pathology (including telomere biology), with the use of gene delivery systems (including viral delivery systems), and with the use of cell-based therapies (including stem cell therapies), a fatalistic view of age-related disease is no longer a reasonable clinical default nor an appropriate clinical research paradigm.

Precedence will be given to papers describing fundamental interventions, including interventions that affect cell senescence, patterns of gene expression, telomere biology, stem cell biology, and other innovative, 21st century interventions, especially if the focus is on clinical applications, ongoing clinical trials, or animal trials preparatory to phase 1 human clinical trials.

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Open Access Original Research

Transforming Community Strategy from Population Health to Quality Aging — The Role of Digital Technologies

Mohan Tanniru *, Amanda Sokan 

College of Public Administration, University of Arizona, Tucson, AZ, USA

* Correspondence: Mohan Tanniru

Academic Editor: Bartolomeo Sapio

Special Issue: Aging and Technology Use in the Era of Digitization and Automation

Received: March 03, 2025 | Accepted: August 05, 2025 | Published: August 11, 2025

OBM Geriatrics 2025, Volume 9, Issue 3, doi:10.21926/obm.geriatr.2503321

Recommended citation: Tanniru M, Sokan A. Transforming Community Strategy from Population Health to Quality Aging — The Role of Digital Technologies. OBM Geriatrics 2025; 9(3): 321; doi:10.21926/obm.geriatr.2503321.

© 2025 by the authors. This is an open access article distributed under the conditions of the Creative Commons by Attribution License, which permits unrestricted use, distribution, and reproduction in any medium or format, provided the original work is correctly cited.

Abstract

Aging is a multifaceted journey shaped by diverse life-course experiences, which contribute both to the challenges populations face in achieving their health goals and to the competencies they can bring to sustain health and aging. Community strategies designed to support population health—by leveraging technology and external partners—require transformation to effectively extend their focus to aging-related goals. In this paper, we adopt a service lens to examine how these community strategies, which co-produce practices and services, can be adapted to leverage population competencies. Drawing on social diagnosis research, we categorize key challenges and competencies and present four case scenarios that illustrate how advanced technologies can be leveraged to transition community strategies to support aging goals. The paper concludes by exploring how populations can actively design their own aging pathways and offers suggestions for future research.

Keywords

Quality aging; community strategies; social diagnosis; digital technologies; population health

1. Introduction

The term “aging” often refers to the progressive decline in health that occurs during adulthood [1]. Measured on the life calendar, aging is typically reduced to the setting of retirement age, eligibility for health insurance, and an individual’s contribution to healthcare costs. In practice, many strategies aimed at supporting this population—referred to here as community strategies—leverage technology and external partners to design services based on the assumption that older adults face a range of challenges, such as diminished vision and mobility, limited technological access and literacy, and various socio-economic barriers. However, this perspective often introduces bias into service design by stereotyping all adults above a certain age as a homogeneous group. Even when services are differentiated based on age, geography, or socio-cultural factors, such approaches tend to overlook design opportunities that could empower older adults to leverage their distinct competencies to access resources through technology [2].

Research on the life course perspective [3] encourages a more nuanced understanding of aging by recognizing that individuals’ past life experiences—from birth to the present—shape both the challenges they face in accessing care and the competencies they can leverage to age successfully. Viewed through the lens of the psychology of aging [4], aging may involve physical decline, but it also brings strengths such as positive thinking, spirituality, and adaptability [5]. This holistic perspective on older adulthood calls for consideration of a broad array of factors—social, psychological, physical, financial, environmental, and spiritual [6]—when defining the aging population and developing community strategies to support successful aging, even if there is no consensus on the metrics for defining success or who determines them. To support inclusiveness in strategy development, the concept of optimal aging encourages older adults to define their own metrics for success—setting personal aging goals that enhance their physical, mental, emotional, and social well-being [7].

Recognizing the diverse perspectives on aging and individual definitions of quality of life, a systematic review of aging research [8] suggests that strategies to support healthy aging should consider the role of individuals’ ecosystems and the relationships they have nurtured over their lifetimes. This is particularly important for underserved aging populations who, despite facing multiple challenges such as poverty, limited education, unsafe housing, and cultural barriers to healthcare, still maintain a sense of purpose and aspiration to improve their quality of life [9]. In other words, regardless of the life course experiences that have shaped a population, strategies must support resilient aging, which involves empowering individuals to shape their own future trajectories and age well.

Many community strategies are designed to support population health by leveraging technology and external partners to help individuals transition from their current health state toward achieving desired health goals [10]. These strategies, particularly in the realm of preventive care, often require cross-sector collaboration to enable systemic action, especially when addressing the health goals of individuals with chronic conditions [11]. While community strategies do attempt to address social determinants of health (e.g., social, economic, and cultural disparities) that hinder access to care, they often do not explicitly consider the competencies individuals have developed through their life experiences or their desire to shape their own aging trajectory. This consideration becomes critical as aging populations seek to align their values—historical, cultural, and social contexts, as well as current circumstances [12]—with capabilities to access financial, physical (e.g., housing and infrastructure), human (e.g., knowledge and skills), and social (e.g., networks and relationships) resources in order to choose their life’s path and age well [13]. This leads to our research question:

How can community strategies transition from a focus on population health to supporting quality aging?

As our understanding of aging evolves—from concepts of “successful aging” to “aging well” [14]—there is growing recognition that much of this aging process occurs at home, emphasizing the need to support populations as they age in place [15]. Enabling aging populations to use their capabilities to age well requires providing them with the necessary technologies to access resources, while also addressing the ethical and practical considerations of using information and community technologies [16]. Ultimately, these technologies should be need-driven, designed to address health, social, and functional challenges [17], and should range from self-directed to autonomous solutions depending on the users’ capabilities [18]. Often described as the process of gathering user requirements and assessing operational viability prior to system design [19], community strategies intended to support aging-in-place [20] must help individuals prioritize their needs and leverage technology to age well. This leads to a companion research question:

Who is responsible for coordinating the transformation of community strategies to support quality aging?

In this paper, we expand the concept of human agency [21] to include a network of both human and machine (technology) to support populations in aging well by leveraging their competencies and technological tools. The paper is organized as follows: Section 2 uses a service lens to initiate the discussion on transforming community strategies from a focus on population health to quality aging. Section 3 examines the role of social determinants and categorizes them into population challenges and competencies as individuals pursue their health and aging goals. Section 4 presents five use cases to illustrate how community strategies originally developed for population health can be adapted to support aging objectives. Section 5 discusses the coordination required for transforming community strategies, and the final section offers concluding remarks and directions for future research.

2. Community Strategies to Support Population Health

Service-dominant logic research [22,23] argues that organizational transformation requires a re-envisioning of the customer’s role as they engage in their purchase journey. This perspective uses a service lens to design services that leverage technology to support three key value cycle activities:

  • Value Creation: Designing services that help customers search for information and evaluate products based on decision criteria such as cost, convenience, quality, and novelty—corresponding to the intelligence and design/choice phases of the decision journey [24].
  • Value Fulfillment: Developing services that facilitate the purchase of products that firms design to generate value for the customer.
  • Value-in-Use: Assessing customer experience while using a product, identifying value gaps, and refining offerings before beginning the next value cycle.

Community strategies designed to transform healthcare organizations in support of patient care journeys share many parallels with the value cycle activities used in business organizations. However, unlike traditional businesses, many value cycle activities in healthcare take place within the patient ecosystem, requiring the active engagement of both patients and a range of external partners—both clinical and non-clinical. There is also growing recognition that healthcare organizations must re-envision the role of patients as co-producers of preventive or treatment practices and services throughout their care journey [25].

Viewed through a service lens, healthcare organizations create value by co-producing preventive and treatment practices with patients and their communities. They should design services that inform and educate patients about their health conditions (awareness services) and support informed decision-making regarding the practices chosen for prevention or treatment of their illness (decision support services). In the value fulfillment phase, they co-produce services that engage patients in adhering to prescribed practices (engagement services). As part of value-in-use, they should provide feedback on patients’ health conditions and adherence, using partners when appropriate, which can lead to modifications in their value creation (post-engagement services). When appropriate, these services are supported by digital technologies. This process is illustrated in Figure 1.

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Figure 1 Co-production of practices and services supporting the patient care journey.

The impact of social determinants on health inequities has been highlighted by policymakers, including the World Health Organization [26], and research on the determinants of health [27]. In response, community strategy design came to view social determinants as reflective of the patient ecosystem—or problem environment—and began to consider these factors in the co-production of practices and services to help patients overcome their barriers and achieve their health goals. A systems approach [28] encourages healthcare organizations to first understand this problem environment, which has shaped the patient’s current health condition, before generating solutions that will enable them to reach their desired health outcomes—potentially in a more sustaining environment. Elder’s [21] life-span development principles also underscore the importance of historical time and place in shaping an individual’s life trajectory, including the role of the “linked lives” principle—i.e., the influence of network actors—in helping individuals overcome challenges and attain their health and aging goals. The next section discusses some of the factors that shape life experiences and their contribution to both challenges and competencies.

3. Role of Social Determinants in Community Strategies

Designing a community strategy can be understood as creating a bounded agency—that is, agency exercised within existing structures [29,30]. This bounded agency enables patients to navigate their care journeys and overcome challenges to achieve their health goals. In this paper, we draw on social diagnosis research and the 4R model [31] to categorize the factors that shape individuals’ life experiences. These factors, reactions, resources, and relationships—are outlined in Table 1. Each of these can influence both health inequities experienced by specific populations and the competencies they have developed across their life trajectories.

Table 1 Social diagnosis factors to categorize life experiences as barriers and competencies.

The 4R model has been applied, for instance, in identifying patients’ moods and emotional states to inform sustainable mental health strategies in organizational settings [32]. Similarly, social diagnosis factors can be used to identify individual patient strengths, enabling the development of strength-based approaches to social policy formation [33]. These four factors are also interdependent, particularly from the perspectives of social science and social work [34,35]. For example, an individual’s role can shape their cognitive and behavioral reactions to illness [36], influence how family relationships are nurtured [37], affect emotional responses to health challenges [38], and determine how community resources are leveraged [39].

Two additional components—stress and social support—can be integrated with the 4Rs to strengthen family-centered programs [40] and trusted and empathetic relationships within families or communities can significantly aid patients in managing chronic illnesses [41]. These studies underscore how the 4Rs and their interdependencies can be leveraged to bring a strength-based perspective [42], thus supporting the notion that populations can work towards both their health and aging goals. In the next section, we present five use cases to illustrate how the 4Rs can be applied to help transform community strategies from a focus on population health to one that supports quality aging.

4. Transforming Community Strategy: From Population Health to Quality Aging

Developing a community strategy to support population health by addressing health inequities linked to the social determinants of diverse populations is a complex task. Extending this strategy to support quality aging—by incorporating a broader network of actors, including patients—adds an additional layer of complexity. One common approach to managing complexity is to decompose the problem into components and tailor interventions to high-priority needs. The decomposition of complex, knowledge-intensive problems into structural components to aid decision-making has been widely discussed in the business and computer science literature [43,44,45]. Research also shows that individuals mentally deconstruct problem characteristics, making implicit trade-offs based on perceived utility [46], or applying internal logic [47] to assign priorities to different aspects of a given problem.

We will use the 4Rs framework and associated information to decompose the complex task of categorizing social determinants into two dimensions: the challenges individuals may have faced in reaching their health goals, and the competencies they may have developed to overcome these challenges. For the purposes of this discussion, we will not explicitly examine the interdependencies among the 4Rs, except in terms of how they may indirectly and cumulatively contribute to both challenges and competencies that community strategies should consider in the co-production of practices and services. As illustrated in Figure 2, community strategies designed to support population health (shown on the left) by helping individuals overcome challenges and achieve their health goals are discussed in the first part of this section. The second part of this section then extends the community strategies to help individuals reach their aging goals. To explore this transformation in community strategy, we will use five illustrative use cases. Four are drawn from previously published research, while one is based on direct personal contact with the patient involved.

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Figure 2 Transformation of community strategy from population health to quality aging.

4.1 Community Strategies to Help the Population Reach Their Health Goals

4.1.1 Case 1: Older Adults with Disabilities

An older man in his 60s sustained a severe injury in an accident, resulting in disabilities that require him to use a walker and move slowly with a limp. Despite these physical limitations, he remains active and engaged in his community. The current community strategy supporting him includes the provision of a caretaker who assists with tasks at home and access to a specialized van service, which he can call for transportation to medical appointments, shopping, and other essential outings. His daily routine includes walking through his neighborhood, where he greets other older adults with a smile, which contributes to his physical well-being and social connectedness. He lives at home in a well-established neighborhood that supports his independent lifestyle.

4.1.2 Case 2: Caregivers Supporting Chronic Care Patients (2.1) and Children with Disabilities (2.2)

To improve health outcomes for patients receiving care from informal caregivers—such as family members, health systems’ community strategies have begun to address caregivers’ needs. In Case 2.1, an mHealth application is provided to support caregivers of chronic care patients [48]. The app offers access to detailed care instructions, facilitates the sharing of patient health information with providers, and enables communication with friends and family to coordinate caregiving responsibilities. This functionality allows caregivers to schedule assistance and take breaks when needed. In Case 2.2, a caregiver mother supports a child with disabilities while facing significant financial hardship and community stigma [49]. The current strategy provides her with a mobile application that tracks the child’s rehabilitation progress at a nearby facility.

4.1.3 Case 3: Older Adults with Chronic Care Conditions Living at Home

Many older adults with chronic conditions live either alone or with a spouse, while their adult children and other family members reside far away [50]. Although these individuals often drive and maintain an independent lifestyle, they face ongoing challenges in managing their health, such as getting timely medication reminders and assistance with home maintenance to prevent falls. Community strategies frequently support this population by providing access to local community centers, which offer opportunities for social engagement, peer interaction, and learning about technology allowing them to stay connected with family members. This scenario is common among older adults living alone or with a spouse in retirement communities or neighborhoods ranging from urban to suburban settings [51]. Community strategies often incorporate mobile applications and provider portals that facilitate virtual consultations and provide access to services and resources needed for support at home.

4.1.4 Case 4: Older African American Population with Heart Conditions and Obesity

Many older African Americans suffer from chronic health conditions and obesity, and they face significant socio-economic challenges in accessing care. To support their needs—particularly in reducing weight and managing blood pressure—the community wellness center implemented an educational program focused on healthy eating and physical activity. This was complemented by a mobile app and digital tools such as Fitbits, blood pressure monitors, and weight scales to help participants apply what they learned and track their progress [52].

Table 2 illustrates the challenges faced by the population and the health priorities used to design a targeted community strategy in each of the cases. Note that many of these strategies use technology to engage older adults in their care journeys, even when the primary goal is to help them overcome barriers to accessing care.

Table 2 Community strategies designed to address health goals.

4.2 Community Strategy Transformation Using Technology to Support Quality Aging

This section discusses how the patient populations in each case can choose to leverage their competencies to co-produce practices and services and use technology to support their aging goals. Some of these aging goals can be focused on improving health and others on increasing social engagement within the community. The community strategy transformation to support Aging goals is often incremental and cumulative based on the population priorities as they continue to evolve, thus making this a dynamic process. The calls for community strategies to be resilient as they adapt to changing population requirements. In this section, we will first illustrate the community strategy transformation by first discussing the technologies that can be used to leverage competencies of the population discussed in the five use case scenarios as well as identify the first aging goal identified by the population groups. Table 3 discusses their aging goal in column 3 and highlights (in bold letters) the potential technology that may be used to support this goal in column 4.

Table 3 The role of technologies in leveraging population competencies.

Use Case Scenario 1: The older man with physical challenges has a strong educational background and high energy levels, and his immediate goal is to seek opportunities to remain mentally and socially engaged. He enjoys visiting libraries, discussing politics, and staying informed about current events.

Co-production of practices: The patient’s education and cheerful outlook may enable him to explore the use of assistive technologies [53] to help manage continuous physical challenges [54]. He can use smartphone apps to monitor visual impairments and physical activity [55,56], as well as to track any signs of health deterioration and seek timely interventions. Additionally, he can use real-time monitoring of vital signs to assess stress levels or cognitive decline and participate in activities—such as reading or playing cognitive games—that help reduce stress and maintain mental acuity.

Co-production of services: He can use artificial intelligence (AI) and data analytics [57] to support the development of tailored services that engage him in social discourse with peers through discussion forums and blogs.

Use Case Scenario 2: Caregivers of patients with chronic care conditions (2.1) have expressed an interest in receiving support for financial planning related to the care they provide, as well as assistance in transitioning patients from home to independent living facilities. This would allow them to develop their own professional skills for life after caregiving. Caregiver mothers of children with disabilities (2.2) have expressed a desire to learn about therapy guidelines and adopt best practices to support their children at home. They are also interested in opportunities to volunteer and mentor other caregivers facing similar challenges.

Co-production of practices: Caregivers can help co-produce practices that address mental health challenges by extending the use of mHealth interventions, while continuing to manage the chronic conditions of the patients under their care [58,59]. They can also use mobile alert systems to trigger emergency responses and telehealth technologies to communicate with healthcare providers. Additionally, they can leverage digital services to engage socially with peers and family, enhancing their quality of life as they age [60].

Co-production of services: Caregivers can help co-produce services by using AI chatbots to ask questions and receive timely responses. They can get training on how to use search engines—some supported by AI—to find information on caregiver services [61]. Additionally, they can use social media platforms to learn about best practices and share their own experiences by mentoring other caregivers.

Use Case Scenario 3: The older adults expressed a desire to learn how to use telehealth technology to connect with providers, utilize wearables to track their health conditions, and engage with social media to stay connected with family members. They also wish to interact with peers at the community center to share knowledge and learn new skills [50].

Co-production of practices: The older population can help co-produce practices that include remote monitoring by providers using sensor-based technologies, which automatically transmit health data for physician follow-up [62] and consult with hospital staff or local healthcare professionals who provide in-home care [50]. They may also use apps to assess cognitive decline due to aging [63]. If experiencing symptoms of delirium, they can utilize virtual reality technologies or AI-based natural language processing tools to support early diagnosis of dementia [64,65].

Co-production of services: The population can also help co-produce services that enable them to use social media to access social, emotional, and peer support through affinity groups and other online networks [66]. Community centers and other facilities frequented by this population can be leveraged to help design and support these services.

Use Case Scenario 4: While the older African American population faces significant challenges, they view the community facility as a valuable space to engage with peers through social activities and seek encouragement and support, preferably using social media. They also express interest in expanding their use of technology to interact with physicians and share updates on their health progress.

Co-production of practices: Since the COVID-19 pandemic, many underserved population groups have preferred to use telemedicine technologies to overcome transportation barriers, enabling them to interact with physicians and share their health data remotely [67]. The wellness center can co-produce practices by integrating phone apps with smart home technologies [68] to monitor physical activity at home, reduce the risk of falls, and track changes in health conditions for provider follow-up. They can also make use of mobile health (mHealth) clinics that visit neighborhoods to provide routine screenings and referrals [69,70,71]. Additional co-produced practices may include tools to support medication adherence and issue alerts for physician follow-up appointments [72].

Co-production of services: The population can help co-produce customized services by sharing data gathered through smartphones [73] and by using AI agents to receive personalized recommendations for alternative wellness activities, such as cooking lessons, group walks, and community gardening.

In summary, the five use cases (UC) illustrate how patient population competencies—in terms of education, motivation, social networking interests, and relationships with family and friends—can be leveraged to support their aging goals. These priorities can range from simply maintaining health to enhancing the overall quality of aging by improving health care or strengthening social engagement through peer and community connections. While these goals are not mutually exclusive, their relative importance may shift over time. Community strategies must therefore rely on flexible digital platforms that can adapt as individual priorities evolve. As illustrated in Figure 3, the needs of the population may vary—from health maintenance and social connectivity (UC 1, 2.2, and 4) to improving care quality (UC 2.1), or a combination of both (UC 3).

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Figure 3 Expanded community strategies to support the aging goals of each use case.

Given the role that technologies play in the co-production of practices aimed at improving health quality—often coordinated by health systems—and in the co-production of services that enhance social well-being—typically facilitated by providers, partners, or even patients themselves—the central challenge becomes identifying who should coordinate community strategies as they transition from a focus on population health to quality aging (the second research question). This question will be explored in the next section.

5. Coordinating Community Strategy Transformation to Support Quality Aging

Dynamic capabilities theory suggests that an organizational strategy must integrate its own resources and competencies with those of its partners to meet the evolving needs of its customers [74]. To support this dynamism, organizations may adopt different inter-organizational dynamic capability (IDC) models, depending on how relationships among partners are coordinated and resources are orchestrated [75]. Coordination can be led by a single focal organization, jointly by a focal and one or more collaborating organizations, or through a network formed by all participating organizations.

Within healthcare, community strategies require inter-organizational or inter-sector collaboration and dynamic capabilities to address evolving patient goals. We refer to these IDC models as community models. As shown in Figure 4, these models may be coordinated by a single focal organization that co-produces both practices and services (Q1: provider-centric IDC model), or by a combination of providers and partners. In mixed models, coordination may be led by providers and supported by partners (Q2) or led by partners and supported by providers (Q3). Community models may also adopt a network-based approach (Q4), where coordination is overseen by an external entity—such as a public health agency, a health or community exchange, or even by the patient themselves.

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Figure 4 Community strategies to support population health.

While all use cases may use provider-coordinated models (Q1) to co-produce healthcare practices, they often rely on different models for co-producing services. For instance, provider-supported and partner-supported models (Q2) are used in UC 1 to access transportation and home support, in UC 2.1 to use an app that helps reduce stress through social interaction, and in UC 2.2 to use an app to track a child’s progress as well as learn about therapy guidelines. In contrast, partner-coordinated and provider-supported services(Q3) are used in UC 3 and 4 to enable community centers and organizations to help patients connect socially and engage in peer learning.

However, as the population shifts from pursuing health goals to achieving broader aging goals, the community strategies required to support this transition may no longer be effectively coordinated by providers or partner organizations. These entities typically focus on population health and may not address the evolving, individualized priorities that define quality aging. Given that aging goals are self-defined and dynamic, we propose that the patient team, including patients, their families, and their communities, must serve as the focal organization in coordinating the community models needed to achieve these goals.

Depending on the types of practices and services required, the patient team may engage other IDC models—such as provider-led, partner-led, or network-based—as appropriate. We classify the community strategies coordinated by the patient team as micro-, meso-, or macro-level strategies, which are discussed in the next section.

5.1 Micro-, Meso-, and Macro-Level Strategies to Support Quality Aging

The micro-level strategy centers on extending the human agency of the patient population by emphasizing their ability to recognize and apply their competencies to maintain health and pursue evolving aging goals. This is an example of a patient team using a healthcare organization’s digital front door or portal to access information relevant to their care journey, visiting a public health agency’s website to learn about preventive practices, or utilizing the resources of external partner organizations for social and emotional support. Because the micro-level strategy is patient-centric and personal, individuals rely on personal technologies—such as mobile apps, websites, and wearable devices—to access clinical and social services that support both their health maintenance and broader aging goals. In each of the cases discussed earlier, patients with sufficient education and access to technology can be trained to use the resources necessary to support their aging goals.

The meso-level community strategy involves collaboration between the patient care team and providers and/or partner organizations to co-produce practices and services that support aging goals. In this strategy, a patient care team may contribute by sharing their knowledge, supporting others, and engaging with the community as part of their own aging journey. In these cases, the patient team uses shareable technologies—such as social media, video or audio communication tools, and blogs or discussion forums—to coordinate with or contribute to others based on their goals.

For example, in UC1, the older man may lend his expertise to help others manage disabilities or reduce social isolation through discourse. Similarly, in UC 2.2, a caregiver of children with disabilities may seek out therapeutic best practices and mentor peers facing similar challenges. In each of these cases, the initiative is coordinated by the patient but supported by providers or partner organizations, depending on the type of service. In UC 3 and 4, older adults, and minority populations may draw on their lived experiences and cultural knowledge to mentor others or promote social engagement. In these instances, patients contribute content and support, while providers or community partners may coordinate platforms such as social media or discussion forums to facilitate broader participation.

The macro-level community strategy recognizes that the cumulative competencies and expertise of patient teams can contribute to best practices that benefit the broader community. These capabilities can be leveraged to co-produce new practices, such as therapy guidelines for children with specific disabilities (UC 2.2), and new approaches to managing physical disabilities and reducing social isolation (UC 1). They can also foster family and cultural engagement that helps reduce stress and support purposeful activities for individuals from similar backgrounds (UC 2.1, 3, and 4). Implementing such a strategy, however, may require coordination by an external entity that manages the digital platform, such as community portals, to enable individual patient populations to contribute to addressing wider community needs. Potential coordinators of such a platform may include public health agencies or nonprofit foundations focused on population health priorities such as fall prevention, smoking cessation, addiction treatment, or mental health support.

These observations are summarized in Figure 5. The nodes are labeled as “T” to represent transformed community strategies that support quality aging.

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Figure 5 Community models to support quality aging.

In summary, while health systems and public health agencies have traditionally used provider-centric or network-centric models to support population health, they have increasingly begun to leverage a mix of provider- and partner-coordinated community models to address social determinants of health and help patients achieve their health goals. However, as the focus shifts from health goals to aging goals, it becomes essential to empower the patient team to coordinate, and support stated aging goals based on their priorities—unless these aging goals remain minor extensions of health goals that a provider or partner can manage.

6. Conclusions and Direction for Future Research

This paper demonstrates the critical need to transform community strategies beyond their traditional focus on population health toward a more nuanced approach centered on quality aging. A holistic view of successful aging requires an understanding of how the life course shapes individuals’ definitions and expectations of health and well-being, as well as recognition of the heterogeneity in outcomes and experiences among older adults. By leveraging a deeper understanding of the social determinants of health, we can begin to distinguish the challenges that populations face from the competencies they possess—competencies that can be mobilized to enhance their lived experience and ability to thrive as they age.

Integrating patient competencies into community models help create comprehensive frameworks that address the diverse needs of aging populations as they transition from health maintenance goals to those of meaningful and successful aging. Specifically, by inverting the traditional focus—from provider-led to patient team–coordinated models—we can begin to reimagine how to empower aging individuals to pursue goals beyond health, drawing on their life experiences to shape and contribute to their communities.

6.1 Directions for Future Research

Business literature has used both SWOT (Strengths, Weaknesses, Opportunities, and Threats) and SOAR (Strengths, Opportunities, Aspirations, and Results) for strategic planning. However, there has been a shift from SWOT to SOAR so that focus can move from identifying weaknesses and threats to emphasizing opportunities, aspirations, and results. Similarly, healthcare organizations that have used community strategies focused on population weaknesses and the threats they posed to reach their health goals, may need to re-evaluate this strategy and transition it to an aspiration-focused approach that supports aging goals and engages patients to use their competencies and a patient-driven community model to seek the results they are looking for.

In other words, to what extent can a health system or public health agency function as a provider or partner to address patient challenges in reaching their health goals, and reverse their role as a partner in helping the population use their competencies and technologies to reach their aging goals? This question highlights the dual role these organizations may have to play in identifying barriers to helping the population reach their health goals and facilitating solutions through collaborative partnerships to address their aging goal. One approach to support such a shift is to examine how health systems themselves play a dual role – both as a focal organization of a micro-strategy that is provider-centric and as a member of a macro-strategy that uses health or community exchanges to contribute to and share patient information with others. Macro-level strategies require network technologies that facilitate knowledge sharing among population groups [76], peer-to-peer connectivity [77,78], and leverage advanced tools to analyze and tailor information to meet their own specific needs [79]. Can the providers/partners help build a patient-exchange network that supports the macro-level strategy of patients by enabling them to contribute to and share information with other patients, while also using this network to develop their own patient-centric micro-level strategies?

These strategies rely not only on shareable technologies, but also on data informatics, knowledge management systems, and AI tools capable of synthesizing information to generate best practices. AI-driven analytics can help identify emerging challenges and opportunities, enabling adaptive strategies that better support both health and aging goals at the population level. As noted by Bharel et al. [80], the application of AI in public health is a promising area for research. If health promotion and prevention are key goals of public health, should the role of public health begin to accommodate patient exchanges and help populations leverage AI tools to identify a network of actors who can extend their human agency as they pursue their aging-related goals? Also, in addition to using patient exchanges to support their micro-level strategies, can they also be used to help them transition to meso-level strategies and seek appropriate providers and partners?

This remains a critical area for further exploration, as technologies continue to evolve to enhance human agency and support the pursuit of aging-related goals by patient teams as they shape their micro- and meso-level strategies. In summary, community models designed by providers using partners to support population health strategies may have to be turned upside down by creating a patient exchange that enables patients to form their own community models to address their aging goals.

Author Contributions

Conceptualization, Mohan Tanniru; methodology, Mohan Tanniru; validation, Mohan Tanniru and Amanda Sokan; formal analysis, Mohan Tanniru and Amanda Sokan; investigation, Mohan Tanniru and Amanda Sokan; resources; Self funded; data curation, Not relevant; writing—original draft preparation, Mohan Tanniru; writing—review and editing, Mohan Tanniru and Amanda Sokan; visualization, Not relevant; supervision, Not relevant; project administration, Mohan Tanniru; funding acquisition, Not relevant.

Competing Interests

The authors have declared that no competing interests exist.

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