A multi-level framework for advancing digital health equity in learning health systems: aligning practice and theory with the Quintuple Aim

Abstract

Achieving digital health equity is essential to realizing the transformative goals of the Quintuple. Aim: optimizing patient experience, improving population health, supporting provider well-being, reducing costs, and advancing health equity. Yet significant disparities persist in access to digital tools, driven by both traditional and digital social determinants of health (SDOH), such as housing instability and limited broadband access. Health system responses often focus on downstream interventions to meet immediate needs, such as referrals for housing assistance or smartphone distribution, while upstream strategies, like partnerships to expand access to affordable housing or advocacy to improve broadband access, remain underutilized. Similarly, targeted tools for specific populations often lack corresponding universal strategies like digital literacy campaigns. The absence of systematic Electronic Health Record (EHR) integration of SDOH data further limits health systems’ ability to identify disparities, tailor interventions, and support structural change. This paper introduces a theoretically grounded, multi-level framework for advancing digital health equity within Learning Health Systems (LHS). Drawing on insights from information systems theories, socio-ecological models, organizational learning, implementation science, and systems thinking, the framework supports alignment of equity-centered strategies across micro- (individual), meso- (organizational), and macro- (policy) levels. The framework is organized around three strategic domains: (1) building equity-driven data infrastructure through SDOH-EHR integration, (2) designing scalable, equity-centered interventions that balance targeted and universal approaches, and (3) leveraging strategic starting points to transition from downstream efforts to upstream reforms. Grounded in the U.S. context yet informed by international evidence, this framework offers a roadmap for aligning theory and practice to advance digital health equity in LHS. It is both actionable and adaptable, translating evidence and theory into a structured approach that healthcare systems can use to guide health equity initiatives. It illustrates how SDOH data can inform person-centered care, how targeted tools like multilingual telehealth apps can be integrated with universal strategies such as digital literacy campaigns, and how enabling services, community partnerships, and policy advocacy can catalyze longer-term structural reforms. Emphasizing continuous learning through feedback loops and multi-level alignment, the framework equips stakeholders to embed equity into LHS design and function, ultimately advancing sustainable progress toward the Quintuple Aim.

Introduction

The Quintuple Aim of healthcare, which includes optimizing patient experience, improving population health, supporting provider well-being, reducing costs, and advancing health equity, offers a transformative framework for healthcare systems, providers, and policymakers seeking to reduce disparities and improve outcomes across diverse populations [1, 2]. Building on the foundational Triple Aim, the Quintuple Aim positions health equity as a core objective and highlights the need to eliminate systemic disparities in access and quality of care. Achieving this aim requires sustained attention to Social Determinants of Health (SDOH), which include the social, economic, and environmental conditions that influence health outcomes and shape how individuals interact with healthcare systems [3, 4]. These determinants span both traditional SDOH, such as housing, transportation, education, and digital SDOH, such as internet access, digital literacy, and availability of technology [5]. As healthcare delivery becomes increasingly digital, addressing digital SDOH is critical to ensuring that digital health tools (such as telehealth platforms, patient portals, and mobile health applications), help mitigate and, where possible, reduce health disparities through intentional design, strategic implementation, and supportive system-level reforms [5, 6].

Digital health equity refers to the fair opportunity for all individuals to access and benefit from digital health tools, regardless of their socioeconomic background, geographic location, or demographic identity [7, 8]. Marginalized populations across both high-income and low- and middle-income countries often face significant digital barriers [9]. These include limited access to broadband, low digital literacy, and inadequate technology infrastructure, which restrict their ability to engage with healthcare and widen existing inequities [10]. Addressing these barriers requires attention to both downstream strategies, such as digital literacy support, and upstream solutions, such as broadband expansion and structural investments [5].

Policy reforms across countries have laid important groundwork for promoting health equity. In countries such as the United States, Canada, and the United Kingdom, major national initiatives have aimed to strengthen equity-oriented healthcare delivery. In the United States, for example, the Affordable Care Act (ACA) expanded insurance coverage and introduced value-based payment models that incentivize providers to address the root causes of poor health. It also mandated Community Health Needs Assessments (CHNAs) for nonprofit hospitals, encouraging organizations to identify and respond to local social barriers [11]. In Canada, the Health Equity Impact Assessment (HEIA) tool provides a structured framework for evaluating the equity implications of healthcare policies and programs [12]. Similarly, the United Kingdom’s NHS Long Term Plan commits to reducing health inequalities through integrated care systems and targeted interventions [13].

While these reforms spurred meaningful activity, many hospital and health system initiatives, both in the U.S. and internationally, have concentrated on downstream services aimed at meeting individuals’ immediate needs [14–16]. These include supports such as food assistance, transportation, and digital literacy training that help patients navigate day-to-day barriers to care. Although these efforts are important, they have often come at the expense of addressing upstream structural challenges. Issues such as housing instability and lack of broadband access are systemic in nature and play a critical role in shaping long-term health outcomes. Health systems are not powerless in the face of these challenges. Through community partnerships, strategic investments, and policy advocacy, they can play a proactive role in advancing solutions that address these deeper structural barriers. However, in practice, such upstream efforts have frequently been overlooked or only partially integrated into institutional strategies for health equity [17, 18].

Incentives and reforms supporting digital infrastructure have also emerged in many contexts. In the United States, the Health Information Technology for Economic and Clinical Health (HITECH) Act promoted the adoption of Electronic Health Records (EHRs), enabling providers to track and document SDOH data and improve care coordination [19]. Internationally, countries such as Australia and the United Kingdom have also invested in digital health infrastructure, including national electronic health record systems and interoperability initiatives [13, 20]. Yet the full potential of EHR systems remains constrained by broader structural issues, including fragmented data systems, limited interoperability, and inequitable digital infrastructure [21]. These limitations have reinforced the need for upstream policy changes and system-level investments to support equitable digital engagement.

The COVID-19 pandemic further exposed the global digital divide. Telehealth emerged as a critical access point during periods of social distancing and clinical disruption, offering new opportunities to reach patients across diverse regions. However, individuals and communities without reliable internet, devices, or digital skills were disproportionately excluded from these innovations [22]. This highlighted the importance of balancing downstream interventions, such as telehealth and patient portals, with upstream strategies aimed at addressing the root causes of digital exclusion [5].

Efforts to embed equity into healthcare quality improvement have gained momentum worldwide. In the U.S., the Centers for Medicare & Medicaid Services (CMS) Health Equity Initiative encourages healthcare systems to track and address both traditional and digital SDOH, including housing, transportation, and broadband access [23]. At the global level, the World Health Organization’s Global Strategy on Digital Health (2020–2025) underscores the importance of equity, inclusion, and access in the digital transformation of healthcare systems [9]. Such initiatives provide valuable examples of how national-level reforms can support equity goals. Together, these developments underscore the urgent need for frameworks that integrate downstream and upstream strategies to ensure digital health equity is a central focus of healthcare transformation across systems and settings.

This paper responds to that need by presenting a theoretically grounded, multi-level framework for advancing digital health equity in Learning Health Systems (LHS). By integrating downstream and upstream strategies, the framework equips healthcare systems with tools to address immediate barriers while driving structural change.

Purpose and significance

The purpose of this paper is to advance a foundational framework for achieving digital health equity within LHS. Digital health equity ensures that marginalized populations, across different countries and regions and often affected by traditional and digital SDOH, can fully access and benefit from digital health innovations. Achieving this vision requires solutions that integrate both downstream strategies, such as digital literacy training, and upstream interventions, such as broadband infrastructure investment and equitable policy reform.

Learning Health Systems are designed for continuous improvement through the use of data and evidence to drive changes in care delivery [24]. These systems have demonstrated success in meeting the goals of the Triple Aim by using real-time data and feedback loops to improve care coordination and outcomes. International and national-level organizations alike, such as Kaiser Permanente and Intermountain Healthcare, large U.S.-based integrated healthcare delivery systems, and various regional initiatives in the United Kingdom, Europe, and Australia, have led efforts to implement learning models at scale, showing that data-driven approaches can generate measurable improvements in patient care [25]. However, realizing the goals of the Quintuple Aim requires a shift in how equity is incorporated into these systems. Rather than treating equity as a downstream byproduct, LHS must embed it into the design and operation of care processes [26, 27].

Current applications of LHS often lack deliberate focus on equity, particularly in the context of digital health. While tools like telehealth and patient portals have expanded access, they often fail to reach populations with limited digital resources or low health literacy [5]. Additionally, without consistent SDOH-EHR integration, health systems are limited in their ability to identify at-risk populations or design interventions that are appropriately targeted [28]. Bridging these gaps requires a more intentional approach to equity, one that considers both individual barriers and upstream structural drivers, including digital infrastructure, policy constraints, and resource allocation.

This paper builds on these insights by proposing a multi-level framework for advancing digital health equity across micro (individual), meso (organizational), and macro (policy and system) levels. The framework integrates interdisciplinary theoretical perspectives from information systems, implementation science, socio-ecological theory, and organizational learning to guide practical action. It offers a roadmap for aligning health system efforts with the equity goals of the Quintuple Aim and supporting the development of inclusive, adaptive, and digitally enabled healthcare systems.

Research questions

Building on the purpose outlined above, this paper seeks to address a set of guiding research questions that emerged from a synthesis of current evidence and relevant theoretical foundations. These questions aim to explore how Learning Health Systems (LHS) can evolve to incorporate equity-centered strategies that address both traditional and digital SDOH across all levels of care, including downstream individual needs and upstream structural barriers. They also highlight the implications of this work for policy, practice, and future research. Together, these questions frame the rationale for this study and lay the foundation for the evidence synthesis that follows.

1. How can insights from hospital and health system efforts to address social and digital determinants of health (SDOH), across national and international contexts, be synthesized to inform strategies for advancing digital health equity in LHS?

2. What theoretical models can support the design of a multi-level framework to guide LHS in advancing digital health equity across downstream needs and upstream barriers?

3. How can the proposed framework serve as a roadmap for aligning data infrastructure, intervention design, and upstream reform across the individual, organizational, and policy levels to advance the goals of the Quintuple Aim?

4. What are the practical implications of this framework for health systems and technology developers seeking to implement equitable and scalable digital health strategies?

5. How can this framework generate actionable insights to inform future research and guide policy development aimed at reducing digital health disparities and promoting equity?

Targeted narrative review to inform framework development

To inform the development of a practical framework for advancing equity and digital health equity within Learning Health Systems (LHS) in pursuit of the Quintuple Aim, we conducted a targeted narrative review focused on how healthcare systems are addressing traditional and digital Social Determinants of Health (SDOH). Because addressing SDOH is fundamental to achieving the Quintuple Aim and improving outcomes across diverse populations, this focus provides the most meaningful foundation for developing an equity framework for healthcare systems. This targeted evidence synthesis builds on prior systematic reviews, conceptual models, and empirical studies that explore healthcare system strategies across multiple levels of action—micro, meso, and macro. While much of the literature to date has originated in U.S.-based health systems, we have purposefully expanded the scope of this synthesis to include relevant international studies that inform similar equity goals through structural, organizational, or digital interventions. Articles were identified through purposive selection and citation chaining from high-impact prior reviews, as well as expert knowledge of key theoretical and empirical contributions to the field [9, 14, 15]. This approach allows for the integration of both conceptual and applied insights to guide the development of a pragmatic, equity-centered framework.

Despite growing recognition of the importance of advancing health equity, current health system efforts to address both traditional and digital social determinants of health (SDOH) remain fragmented and underdeveloped. A synthesis of the existing literature highlights three critical gaps that hinder progress: (1) an overemphasis on downstream rather than upstream strategies, (2) a misalignment between targeted and universal interventions, and (3) the absence of systematic SDOH and digital SDOH data integration into EHRs [5, 7, 8, 10, 14, 15, 21, 28]. These gaps limit the ability of healthcare systems to address inequities effectively. In the U.S., these gaps have been well documented. International evidence from countries such as the United Kingdom, Australia, and India echoes similar challenges, underscoring the need for adaptable strategies that align with varying health system infrastructures and digital access levels [12, 13, 20, 29]. Understanding these gaps is essential to building a multi-level framework that integrates theory and practice to guide action across micro, meso, and macro levels.

Downstream vs. upstream approaches

Downstream strategies focus on addressing immediate health-related social needs but often neglect the structural root causes of inequities. Many hospital-led initiatives prioritize short-term interventions such as food assistance or temporary housing referrals, which provide relief but do not address systemic challenges like housing affordability or employment instability [14, 15, 17, 30]. Similarly, digital equity initiatives, such as distributing smartphones or promoting telehealth use, often fail to reach marginalized populations due to persistent barriers like low digital literacy and limited broadband connectivity [7, 31].

Upstream strategies, including investments in broadband infrastructure, universal digital access policies, and community-level digital literacy programs, are more sustainable but remain underutilized. In countries such as Australia and Sweden, national broadband initiatives have aimed to close digital access gaps, especially in rural or underserved regions [20, 32, 33]. Expanding public broadband networks and implementing inclusive digital education initiatives have proven essential in bridging the digital divide and advancing health equity [34]. These examples illustrate that bridging the downstream–upstream divide is a global imperative and is critical to realizing the transformative goals of the Quintuple Aim.

Targeted vs. universal interventions

Targeted interventions are designed for high-risk populations, such as frequent emergency department users or elderly patients, and are valued for their measurable, short-term outcomes [5, 22]. However, they may inadvertently exclude broader vulnerable populations, such as rural residents or low-income households, who do not meet specific criteria but still face structural barriers [10, 21].

Universal strategies aim to improve access and equity at a population level. Examples include digital literacy programs offered through schools or libraries, which improve community-wide engagement with digital health tools [5, 35]. Internationally, community-based digital literacy initiatives in countries like Singapore and the United Kingdom have also demonstrated success in improving digital inclusion and health engagement [13, 36]. Combining targeted and universal approaches, especially when linked to upstream investments, can optimize equity outcomes. For instance, targeted literacy programs for older adults may address acute needs, while universal campaigns and broadband expansion build sustainable access for all [34].

Lack of systematic integration of SDOH and digital SDOH into EHRs

Most hospital and health systems’ efforts to address SDOH lack mechanisms for systematically collecting and integrating related data into EHRs. Without integration, health systems struggle to identify disparities, design responsive interventions, and advocate for systemic change [14, 15, 28]. For example, health systems that fail to track broadband access or digital literacy metrics may overlook key opportunities to develop targeted strategies or to coordinate community-level responses.

Integrated EHRs enable personalized care through individual-level data while supporting upstream efforts through aggregate data insights. They also facilitate care coordination by tracking social service referrals and measuring outcomes, enhancing accountability and informing systemic reforms [37, 38]. While the United States has led the way in EHR adoption through policies like the HITECH Act, countries such as Denmark and the Netherlands have achieved advanced integration of health and social care data, offering additional models for inclusive digital systems [39, 40]. These functions are foundational to a multi-level approach that connects clinical care with broader structural determinants.

Key takeaways

Although many hospital-led initiatives aim to address health-related social needs through person-centered care, they often fall short of promoting systemic health equity. Downstream efforts, such as food vouchers, transportation support, or smartphone distribution, can alleviate immediate barriers but rarely confront the structural roots of inequity, such as housing instability or lack of broadband access [17]. Moreover, initiatives like “hot spotting” or targeted telehealth programs may improve outcomes for select groups but risk excluding broader vulnerable populations, such as rural residents or digitally underserved communities [10, 14, 15, 22].

Digital inclusion efforts frequently suffer from similar limitations. While mobile health apps, telehealth platforms, or internet subsidies may reach specific patients, they are rarely paired with upstream investments in digital infrastructure or universal literacy campaigns. This misalignment not only limits scalability but may inadvertently exacerbate disparities [7, 34]. Cross-national studies increasingly highlight the need for structural investments and policy coherence to ensure digital health initiatives do not deepen existing inequalities [13, 33, 40]. Evidence consistently shows that lasting impact requires combining downstream and upstream strategies with both targeted and universal approaches.

Integrated EHR systems also remain underutilized, with limited incorporation of digital and traditional SDOH data. This gap hinders care coordination, reduces the visibility of disparities, and undermines advocacy for policy change [14, 15, 28]. Strengthening data infrastructure is therefore essential to support real-time interventions, cross-sector collaboration, and long-term systemic reform. Together, these insights point to the need for a more coherent, equity-centered approach that links micro, meso, and macro-level strategies. A comprehensive framework that integrates these dimensions can bridge existing gaps and guide healthcare systems in developing digital health equity initiatives that are inclusive, sustainable, and aligned with the goals of the Quintuple Aim.

Insights for practice based on targeted narrative review

This section develops key insights to address persistent gaps in advancing health equity, drawn from a synthesis of current health system efforts. While many health system-led interventions targeting Social Determinants of Health (SDOH) offer value, they remain fragmented and lack a guiding framework for coherent implementation. This paper identifies three strategic domains as essential for progress: integrating SDOH and digital SDOH data into Electronic Health Records (EHRs), designing balanced interventions that address both downstream and upstream determinants while combining targeted and universal strategies, and leveraging strategic starting points to transition from downstream services to upstream reforms. These insights serve as the foundation for the multi-level framework presented later in the paper, offering a roadmap to advance digital health equity across micro (individual), meso (organizational), and macro (policy) levels.

Integration of SDOH and digital SDOH data into EHRs

The lack of systematic SDOH-EHR integration limits the ability of healthcare systems to align downstream and upstream efforts or to tailor interventions to the specific needs of their populations. By embedding both traditional and digital SDOH data into EHRs, health systems can more effectively identify at-risk populations, align clinical responses with community needs, and evaluate equity impacts in real time [14, 15, 28]. At the micro level, EHR integration allows providers to use data such as digital literacy status or housing instability to inform individualized care plans. At the meso level, institutions can promote standardized documentation practices and train staff to use EHR-based tools effectively, enhancing the consistency and scalability of interventions. At the macro level, policy efforts should focus on incentivizing the development of interoperable systems that link clinical data with social and community-level datasets. For example, incorporating broadband access indicators into EHRs can inform targeted interventions, such as subsidized internet access or community-based digital literacy workshops [5]. Integrating referral tracking capabilities within EHRs also supports coordination of care and social services, enabling downstream actions such as housing referrals while simultaneously producing aggregate data that supports upstream reforms, including affordable housing development and broadband infrastructure investment [10]. Emerging international efforts to develop national health data platforms, such as in Australia and the UK, reinforce the importance of interoperable systems that integrate SDOH data into routine care delivery [13, 20].

Balanced intervention design

Advancing digital health equity requires a deliberate balance between downstream and upstream strategies, as well as between targeted and universal approaches. Downstream efforts such as food vouchers, transportation assistance, or smartphone distribution address immediate needs, but without complementary upstream initiatives, such as affordable housing investments or broadband expansion, these interventions often fall short of creating sustainable change [38]. At the micro level, interventions should equip individuals with the tools and skills needed to access digital care, such as digital literacy training for older adults or linguistically diverse telehealth support. At the meso level, healthcare organizations can use community-level data to refine the scope and design of interventions that are culturally tailored and context-specific. At the macro level, policies that enable universal broadband access or incentivize digital inclusion are essential to reduce structural barriers [17].

Targeted approaches, such as hot spotting patients with high emergency department use or developing digital apps for specific populations, can yield measurable short-term outcomes but risk excluding underserved groups that fall outside narrow eligibility criteria. Universal strategies, such as community-wide digital literacy campaigns or public access Wi-Fi initiatives, reach broader populations and mitigate the unintended exclusions of targeted programs. A healthcare system, for instance, might begin with a targeted digital literacy initiative focused on elderly patients in low-income neighborhoods, implemented in multiple languages. Such an initiative not only addresses immediate needs but can also serve as a transition point to broader community-wide campaigns or upstream policy advocacy [35].

This balance between targeted and universal strategies has also been emphasized in international digital inclusion frameworks, such as the UK’s NHS Digital Inclusion program and Australia’s National Digital Health Strategy, which underscore the need for population-level engagement [13, 20]. These frameworks also highlight the importance of aligning clinical, organizational, and policy-level action to ensure long-term progress.

Transitioning from downstream to upstream strategies through strategic starting points

Transitioning from downstream service delivery to upstream policy and structural change is essential for addressing root causes of digital health inequities. Several strategic starting points can support this shift and promote long-term transformation. Policy advocacy is one such starting point. Healthcare systems can use insights from frontline efforts to influence policy decisions that dismantle systemic barriers to digital access. For example, the National Rural Health Association has advocated for federal and state investments in broadband infrastructure to improve healthcare delivery in underserved rural communities, highlighting the role of policy advocacy in supporting digital equity [41].

Community partnerships also enable healthcare organizations to extend their reach and ensure that interventions are contextually relevant and culturally responsive. Collaborations with libraries, community centers, or local nonprofits can help co-design and implement digital literacy programs that reflect community values and needs. For instance, a partnership with a local library might involve hosting multilingual workshops on telehealth navigation, thereby increasing digital confidence and uptake among marginalized populations [35].

Enabling services represent another critical starting point. These services address both individual- and organization-level barriers by providing practical support that facilitate healthcare engagement. At the micro level, digital literacy coaching for patients unfamiliar with technology can enhance their ability to participate in telehealth visits. At the meso level, eLearning programs for healthcare staff can improve digital fluency and ensure providers are equipped to support diverse patient populations [42, 43]. These services build long-term capacity while also addressing immediate gaps.

Direct investments in infrastructure can also accelerate the transition to upstream strategies. Funding for broadband expansion or telehealth platform development represents a proactive approach to eliminating digital inequities. For example, investments in rural broadband have significantly improved telehealth utilization and chronic disease management outcomes [44–46]. Academic medical centers that have invested in digital infrastructure have reported reduced hospital admissions among historically underserved groups [47].

Comparable investments in digital health infrastructure are also underway in countries such as India, where national telehealth platforms like eSanjeevani have increased access to care in remote regions—offering further support for the global relevance of upstream strategies [29]. Collectively, these starting points help translate equity goals into scalable action by integrating local evidence, fostering cross-sector collaboration, and building momentum for structural reform. Ultimately, they help translate strategic intent into scalable action and position health systems to achieve the transformative goals of the Quintuple Aim.

Theoretical foundations to inform framework development

Advancing digital health equity requires more than isolated best practices or well-intentioned interventions. Robust theoretical frameworks that explain how individuals, organizations, and systems interact are essential to grounding practical efforts. These foundations provide the structure needed to align actions across levels, support effective implementation and scaling, and ensure that change remains adaptive and sustainable. Without theoretical coherence, even promising strategies may become fragmented, misaligned, or fall short of addressing the structural drivers of inequity.

This section draws from key perspectives in Information Systems Theories, Socio-Ecological Models, Organizational Learning (OL), Implementation Science, and Systems Thinking to illuminate how digital health equity strategies can be thoughtfully designed, implemented, and adapted over time. These theoretical perspectives inform the development of the equity-centered framework introduced later in the paper, which aims to support transformation within Learning Health Systems. While the paper draws heavily from U.S.-based policy and practice examples, these theoretical underpinnings are broadly applicable and can guide health systems globally in adapting to local needs and infrastructure constraints.

SDOH-EHR integration (Information systems and implementation science theories)

One of the most pressing gaps in advancing digital health equity is the lack of systematic integration of Social Determinants of Health (SDOH) and digital SDOH data into Electronic Health Records (EHRs). Without such integration, healthcare systems struggle to transition from fragmented, downstream efforts to comprehensive, equity-centered strategies. Research highlights that most SDOH initiatives operate independently of EHR systems, making them unsustainable, non-replicable, and unable to scale effectively across populations [14, 15]. These isolated efforts fail to leverage real-time data analytics to inform practices, monitor outcomes, or advocate for systemic policy reforms [28]. The literature identifies front-end practices, such as standardized screening tools and community-level data collection, as well as back-end functions like referral tracking and automated alerts, as essential components of integrated SDOH workflows [48, 49].

The Technology Acceptance Model (TAM) offers a behavioral lens to address adoption barriers by focusing on perceived usefulness and ease of use [50, 51]. Designing intuitive tools for providers can enhance documentation fidelity, while culturally tailored digital interfaces can foster patient trust and participation. For example, a multilingual mobile application that enables patients to report housing or internet issues can increase the completeness, quality, and utility of SDOH data. Socio-Technical Systems (STS) Theory complements TAM by emphasizing alignment between technology and workflow [52]. EHR enhancements must be embedded in day-to-day clinical practice, supported by staff training and team-based workflows. For instance, integrating a community resource directory into the EHR is unlikely to drive action without organizational processes for referral follow-up.

The Diffusion of Innovations (DOI) Theory explains how early adopters can lead broader transformation by piloting tools, evaluating outcomes, and disseminating successes [53]. Learning collaboratives have proven particularly effective in scaling innovations like SDOH screening tools by enabling peer learning and adaptation [54]. Comparable efforts have been piloted in national health systems such as the UK’s NHS and Australia’s My Health Record platform, offering cross-contextual learning opportunities [13, 20].

The Consolidated Framework for Implementation Research (CFIR) addresses the multi-layered nature of implementation by highlighting factors across settings, intervention characteristics, and process domains [55]. Leadership engagement, culture of equity, and training capacity can drive success within organizations, while external policies and payer mandates can provide incentives and infrastructure. For example, Medicaid reimbursement for SDOH screening can accelerate adoption, particularly when paired with internal champions and cross-functional teams. Similarly, national policies such as Canada’s Equity-Oriented Health Care framework and Australia’s Primary Health Networks offer supportive environments for scalable implementation [12, 20]. Together, TAM, STS, DOI, and CFIR offer a comprehensive understanding of how to implement and scale SDOH-EHR integration, moving beyond pilot projects toward enterprise-wide strategies that align with both practice and policy.

Balanced intervention design (socio-ecological models and OL theories)

Designing inclusive interventions requires attention to multiple levels of influence. The Socio-Ecological Model (SEM) provides a foundational framework for understanding how health behaviors and outcomes are shaped by individual, interpersonal, organizational, community, and policy contexts [56]. SEM supports the development of interventions that are person-centered and attuned to structural and contextual factors.

For instance, digital literacy training tailored to elderly or non-English-speaking patients addresses individual barriers, while community-wide campaigns delivered through libraries or schools expand reach and promote inclusion. At the policy level, broadband expansion ensures the infrastructure exists to support sustained engagement.

Organizational Learning (OL) theories contribute a dynamic dimension, particularly through double-loop learning, which encourages organizations to question underlying assumptions [57]. A health system that routinely invests in tablet distribution may realize that broadband access is a more foundational need. This insight can inform advocacy, budget shifts, and the development of more sustainable solutions. Nonaka’s Knowledge Creation Theory emphasizes the importance of translating frontline insights into formal organizational knowledge [58]. For example, staff reports that patients struggle with portal navigation can lead to interface redesigns and support service improvements that are codified across the system.

Systems Thinking reinforces these perspectives by highlighting how interventions are connected and evolve through feedback loops [59, 60]. It encourages healthcare leaders to identify leverage points, areas where targeted actions can produce broader systemic change, and to anticipate unintended consequences. This approach is increasingly reflected in global strategies, such as the WHO’s Digital Health Action Plan [9].

Downstream-to-upstream transitions and continuous learning (OL and RE-AIM)

Many health systems begin with services that address immediate needs, such as distributing smartphones or offering transportation vouchers. While important, these services must eventually be paired with upstream reforms that address structural determinants. Implementation Science provides tools to evaluate and guide this transition.

The RE-AIM framework helps assess whether an initiative reaches those most in need, demonstrates effectiveness, and is maintained at scale [61, 62]. SEM ensures such transitions are designed with attention to multiple levels of influence. A school-based program offering technology training can enhance individual competencies and build community readiness. Policy incentives for rural connectivity or device subsidies can support these transitions [34, 56].

Organizational Learning again plays a central role. For example, a surge in telehealth demand may expose persistent connectivity barriers, prompting healthcare systems to reconsider their responsibility in advocating for public broadband access. Nonaka’s framework supports transforming such insights into institutional commitments [14, 15, 57, 58].

Real-world examples underscore the value of theory-informed transitions. Kaiser Permanente’s Thrive Local integrates resource directories into EHRs to connect patients with social services while using data to advocate for housing policy reform [63]. The University of Mississippi’s telehealth expansion, guided by RE-AIM, led to increased rural broadband investment and policy change [47]. Comparable national examples include the eSanjeevani platform in India and the UK’s Health Equity Framework [13, 29].

These frameworks, RE-AIM, CFIR, OL, SEM, and Systems Thinking, collectively support continuous learning and adaptation. They enable healthcare systems to build capacity to adapt and scale equity-driven strategies over time. This capacity is essential to advancing digital health equity as a core element of learning health systems and achieving the Quintuple Aim.

Multi-level framework for digital health equity in LHS

This section presents the culminating contribution of this work, a multi-level framework for advancing digital health equity within LHS, as illustrated in Fig. 1. Synthesizing both theoretical and practice-based insights, this framework provides a strategic roadmap to integrate SDOH data, design equity-centered interventions, and transition from downstream services to upstream reforms. It explicitly aligns with the Quintuple Aim by promoting better health outcomes, enhancing patient experience, improving provider well-being, reducing costs, and advancing health equity through targeted and scalable strategies. The framework operationalizes equity across the micro, meso, and macro levels of the health system, providing actionable guidance that connects individual care, organizational capacity, and policy change. For the purpose of this framework, the micro level refers to strategies at the individual or patient level; the meso level encompasses organizational and community-level efforts; and the macro level includes broader policy and system-level interventions.

Fig. 1.

A multi-level framework for advancing digital health equity in learning health systems (LHS). A multi-level framework illustrating how Learning Health Systems (LHS) can advance digital health equity through three core stages: (1) building equity-driven data infrastructure, (2) designing scalable, equity-centered interventions, and (3) leveraging strategic actions for upstream reform. Each stage outlines specific strategies at the micro- (individual), meso- (organizational and community), and macro- (policy and system) levels, integrating both practical implementation pathways and guiding theoretical constructs (e.g., TAM, SEM, CFIR, Systems Thinking)

The framework is structured around three interrelated domains, building the foundation through data infrastructure for equity, designing equity-centered interventions, and transforming downstream efforts into upstream reforms. These domains reflect key insights from earlier sections: that addressing digital health equity requires the intentional integration of social and digital determinants into health system data, the alignment of intervention strategies with the needs of diverse populations, and a shift in focus from short-term services to long-term systemic reform. Each domain incorporates multi-level strategies that are reinforced by complementary theoretical constructs, providing clarity, rigor, and transferability across healthcare contexts. This multi-level approach is intended to be adaptable across both U.S. and global health systems, recognizing that digital equity challenges and system structures vary across countries.

Building the foundation: data infrastructure for equity

A robust data infrastructure is the necessary starting point for any system seeking to advance digital health equity. Without consistent, actionable data on both traditional and digital social determinants, health systems cannot identify inequities or design responsive interventions. This domain draws directly from evidence showing that many digital health equity challenges stem from gaps in data visibility and integration. Theory, in turn, offers critical guidance on designing workflows, platforms, and implementation processes that align with clinical realities and patient needs across all levels. International efforts in the United Kingdom and Australia to link health records with social care or digital access data provide further support for the global applicability of such data integration strategies [13, 20].

Micro level

At the individual level, integrating digital and traditional SDOH screening tools into clinical workflows enables early identification of barriers such as broadband access, digital literacy, and housing instability. Guided by TAM and STS, embedding these tools into existing intake processes enhances usability, provider acceptance, and data accuracy [50, 51].

Meso level

At the organizational and community level, aligning EHR platforms with clinical workflows and training staff are essential for standardized and culturally responsive data collection. Drawing on CFIR, this approach ensures organizational readiness and implementation success [55]. For example, multilingual patient portals and staff training on equity-enhancing workflows improve inclusivity in data practices.

Macro level

At the policy and system level, investing in interoperable EHRs that link clinical and social data enables organizations to identify population-level inequities and advocate for systemic change. Guided by Systems Thinking, these integrated data infrastructures help health systems expose structural gaps and develop upstream strategies for reform [60]. Health systems in countries like Denmark and Singapore have advanced national-level digital infrastructure to support such integration, demonstrating scalable models for linking clinical and community-level data [39, 40].

Designing equity-centered interventions

Once data systems are in place, the next imperative is to design interventions that are responsive to the diverse needs of populations and communities. This domain is rooted in empirical insights that underscore the need to balance targeted support with universal strategies, ensuring no group is systematically excluded. The application of theory strengthens the ability to design interventions that are adaptable, scalable, and grounded in user experience, while remaining aligned with systemic goals.

Micro level

At the individual level, interventions must balance targeted tools such as multilingual telehealth platforms with universal strategies like digital literacy campaigns. Targeted tools can address specific barriers faced by marginalized populations, including language, culture, or technological proficiency. Universal strategies, such as school- or library-based digital education programs, help elevate digital readiness across broader segments of the population. Informed by the Socio-Ecological Model (SEM) and the Technology Acceptance Model (TAM), this dual approach ensures interventions are both inclusive and practical. SEM highlights the need to consider the individual’s social environment, while TAM emphasizes the importance of perceived usefulness and ease of use in promoting adoption. Together, these frameworks support personalized yet scalable solutions that empower individuals to engage more effectively with digital health tools [50, 56].

Meso level

At the organizational and community level, partnerships with schools, libraries, and community-based organizations enable the co-design and delivery of culturally tailored digital literacy programs. These programs benefit from local trust and contextual relevance, increasing the likelihood of sustained engagement. The SEM emphasizes the influence of community and organizational contexts on individual behavior, while OL theory highlights the importance of feedback loops and reflective practices within institutions. Together, they support community-informed designs that adapt to local needs and build institutional capacity for equity-focused innovation [56, 57]. Globally, models such as Australia’s Be Connected initiative and the UK’s Good Things Foundation offer tested community-based pathways for advancing digital inclusion that align with these meso-level strategies [13, 20].

Macro level

At the policy and system level, interventions must be scaled in parallel with broader advocacy efforts such as universal broadband expansion, digital infrastructure investment, or affordable housing reform. These upstream strategies are critical for addressing structural inequities that limit access to digital health tools. Systems Thinking provides a lens to identify interdependencies and leverage points across policy domains, while Organizational Learning supports the continuous adaptation of strategies in response to evolving policy environments and equity goals. When used together, these frameworks promote scalable, context-sensitive solutions that are both structurally informed and implementation-ready [7, 46].

Transforming downstream efforts into upstream reform

Even the best-designed interventions cannot achieve equity at scale without structural reform. This third domain recognizes that many health systems begin their equity journeys through downstream services and enabling support systems. However, these efforts must evolve into more durable, systemic changes. This transition can be catalyzed through strategic learning, data use, and partnerships, and is best guided by theories that emphasize adaptability, trust-building, and system-level insight.

Micro level

At the individual level, services like one-on-one digital literacy sessions or technology navigation support can reduce immediate barriers and increase engagement. When guided by CFIR and RE-AIM, these efforts contribute to sustained behavior change and lay the groundwork for broader interventions [55, 61].

Meso level

At the organizational and community level, healthcare systems can collaborate with trusted partners to deliver multilingual digital literacy workshops. These co-created interventions, informed by OL and SEM, build trust and support infrastructure for long-term equity initiatives [56]. Internationally, community-based co-design has been a key feature of successful equity programs in Canada and New Zealand, highlighting the transferability of these approaches across contexts [12, 64].

Macro level

At the policy and system level, health systems can use aggregated EHR data to inform advocacy for digital inclusion policies and broadband investment. Systems Thinking and RE-AIM ensure that macro-level changes are informed by real-world data and continuously evaluated [60, 61].

Dynamic integration and learning

Continuous learning and adaptation are essential for operationalizing the entire framework. Using real-time analytics, feedback loops, and adaptive design principles from RE-AIM and Systems Thinking, LHS can refine interventions to meet evolving equity goals [60, 61]. For instance, data collected from SDOH-EHR integration can highlight community-specific needs, informing future iterations of digital literacy campaigns. Evaluations of multilingual telehealth use can reveal infrastructure gaps that necessitate broader policy changes. These dynamic feedback loops ensure that micro-level insights inform meso-level redesigns and macro-level advocacy, creating a self-improving, equity-driven system. CFIR also highlights the importance of inner-setting factors such as leadership, culture, and readiness for change. Leadership-led initiatives such as unconscious bias training or equity metrics in performance reviews can reinforce the cultural conditions necessary to sustain equity efforts [55, 65].

Framework operationalization

To operationalize the framework, health systems should begin, or continue, to embed SDOH and digital inclusion indicators into clinical workflows, building on early-stage efforts that are already underway in some settings, albeit often in limited or pilot forms. As highlighted in our targeted narrative review, these initiatives are frequently one-off, downstream-focused, and lack systematic SDOH-EHR integration, making them unsustainable, difficult to scale, and disconnected from upstream reforms. These foundational activities should then be supported by comprehensive staff training and inclusive digital tools. Next steps include extending these efforts through partnerships and co-designed interventions that address both short-term service gaps and long-term systemic goals. Community engagement, iterative testing, and data-informed adaptations will enhance scalability. Real-time monitoring of outcomes helps refine both targeted and universal strategies, while aggregated data supports macro-level advocacy. Whether applied in a U.S. setting or adapted for use in countries with different healthcare structures, this multi-level framework offers a theory-informed, practice-grounded roadmap for achieving digital health equity within LHS and advancing the transformative goals of the Quintuple Aim.

Implications for policy, practice, and future research

Achieving digital health equity within LHS requires systemic policy reforms, organizational alignment, and evidence-based research. This section provides actionable recommendations to guide policymakers, practitioners, and researchers in advancing health equity through digital tools and strategies. While the proposed multi-level framework was primarily developed based on U.S. health system contexts and examples, it integrates global insights and is intended to be adaptable to a wide range of international healthcare settings. This balance reflects both the specificity of the U.S. landscape and the broader relevance of digital equity principles across health systems globally.

Implications for policy

While the framework was developed with the specificity of the U.S. healthcare landscape in mind, its principles are adaptable across diverse health system structures globally. Advancing digital health equity necessitates systemic reforms that align healthcare practices with societal equity goals. Policymakers must create structural conditions that incentivize healthcare organizations to integrate SDOH, adopt innovative tools, and invest in upstream solutions. One foundational step is to incentivize SDOH data integration into EHRs. In the U.S., for example, CMS and other payers should offer financial incentives tied to equity outcomes. Tools like PRAPARE (Protocol for Responding to and Assessing Patients’ Assets, Risks, and Experiences) facilitate standardized SDOH data collection, enabling healthcare systems to identify patient needs and aggregate data for community-level reforms [66]. Community resource referral platforms like NowPow and FindHelp provide real-time tracking, linking patients to resources while generating data to support policy advocacy [67].

Building a business case for equity-focused investments is critical to demonstrating that addressing health equity is both a moral and economic imperative. For example, the Medicaid ACO model, such as the Community Care Cooperative in Massachusetts, reinvests savings into upstream interventions like broadband and housing, reducing long-term healthcare costs while improving patient outcomes [68]. Scaling such models nationally within the U.S., would align financial incentives with equity goals. Similar approaches have been explored internationally, such as through regional health systems in Sweden and Canada, where equity-centered budgeting aligns with universal coverage goals and social investment policies [12, 32, 33].

Expanding universal digital infrastructure is crucial for bridging the digital divide. Programs like the Affordable Connectivity Program, which subsidizes internet for low-income households, demonstrate the potential of public investments in broadband. Expanding such initiatives alongside targeted broadband investments for rural and underserved areas can enable equitable access to telehealth and digital tools [69]. Global examples such as the UK’s National Health Service (NHS) digital inclusion initiatives and Australia’s Be Connected program illustrate similar investments that have improved digital access and health engagement among older adults and marginalized communities [13, 20].

Standardizing SDOH data collection and reporting is vital for interoperability and benchmarking across healthcare systems. Nationwide standards, such as Z-codes in ICD-10, enable actionable data collection and cross-sector collaboration. For instance, healthcare systems using Z-codes in EHRs can track disparities and inform policy decisions [70]. International health systems increasingly recognize this need as well; for example, the WHO’s Global Strategy on Digital Health (2020–2025) emphasizes structured SDOH data as a foundation for equitable digital health ecosystems [9].

Policymakers should also fund equity-centered innovation grants to pilot scalable solutions. These grants can help health systems test interventions that bridge downstream services with upstream reforms. Programs like the Delivery System Reform Incentive Payment (DSRIP) have supported upstream interventions such as culturally tailored apps and digital literacy campaigns [71]. Expanding these grants can empower healthcare organizations to address both traditional and digital SDOH.

Finally, policy frameworks should ensure accountability through regular reporting of equity-focused metrics. For example, requiring healthcare systems to report digital tool adoption rates by race, income, and geography promotes transparency and incentivizes improvement. The RE-AIM framework could provide critical insights into reach, offering information essential for evaluating scalability, effectiveness, and sustainability of these initiatives [61]. Embedding such frameworks into international standards, such as OECD health equity reporting tools, can strengthen cross-country comparisons and policy learning.

Implications for practice

Healthcare organizations must align priorities, create enabling environments, and establish infrastructure to implement the multi-level framework effectively. These foundational steps are essential for operationalizing equity-driven strategies.

Developing a business case for equity

Equity-focused initiatives deliver measurable benefits, such as reduced readmissions, improved patient outcomes, and cost savings. For instance, addressing SDOH reduces avoidable emergency visits, lowering healthcare costs while enhancing care quality [72]. By linking equity initiatives to these outcomes, organizations can gain leadership buy-in and sustained commitment.

Both public and private healthcare systems have growing incentives to pursue equity-centered models, especially under value-based care and accountability frameworks that align equity with outcomes and cost-effectiveness. In the U.S., most healthcare systems are private nonprofit institutions with a federal obligation to provide community benefit, including efforts to reduce health disparities. This reinforces the relevance of equity-focused frameworks such as the Quintuple Aim, even within largely private delivery models.

Organizational alignment for equity

Embedding equity as a core mission requires leadership-driven initiatives like unconscious bias training to foster inclusivity and readiness for systemic change [65]. Establishing measurable equity goals ensures alignment across organizational levels. For example, setting targets for increasing digital health tool adoption among underserved populations promotes focus and accountability.

Integrating SDOH data into clinical workflows

Embedding SDOH screening into EHR workflows allows providers to address social needs in real time. Identifying barriers like broadband access enables tailored interventions, such as subsidized internet programs. Standardized data collection ensures no population is overlooked, supporting equity-focused screening initiatives [48, 49].

Clarifying scope and designing equity-centered interventions

Healthcare systems must explicitly define the scope of their interventions, balancing downstream and upstream strategies as well as targeted and universal approaches. Targeted initiatives, such as telehealth programs for rural patients, can address immediate barriers but should be informed by community-level data to avoid excluding other vulnerable populations. These targeted efforts should also serve as scalable models for broader, community-wide interventions. For example, a telehealth initiative designed for one underserved group could later inform universal strategies to ensure equitable access for all populations [7, 8, 73]. Internationally, targeted pilots, such as Denmark’s mobile health unit for immigrant populations, have served as scalable entry points into broader digital health equity initiatives [39].

Engaging in strategic community partnerships

Collaborations with local organizations enhance cultural relevance and sustainability. For example, partnerships with libraries and schools offering multilingual digital literacy workshops empower underserved populations while building trust [35]. Such partnerships foster equity-focused ecosystems addressing social and digital determinants of health. Similar approaches are found globally, such as in India’s National Digital Health Mission, which collaborates with local village health committees to address digital and social health gaps [29].

Fostering continuous learning and feedback loops

Mechanisms such as patient advisory boards enable organizations to evaluate and refine digital health equity initiatives. Real-time analytics allow healthcare systems to monitor disparities and iteratively improve interventions. For instance, tracking patient portal engagement metrics can reveal barriers and inform targeted training programs [60].

Strengthening equity-focused metrics and accountability

Robust metrics are essential for tracking progress and fostering accountability. The RE-AIM framework evaluates intervention reach, effectiveness, and sustainability, ensuring equity-driven outcomes [61]. Regular reporting of equity-focused outcomes fosters transparency and creates a culture of continuous improvement. For example, organizations can track increases in digital health tool utilization among underserved groups, ensuring interventions achieve their intended impact while informing future efforts.

By aligning organizational priorities, embedding continuous learning mechanisms, and fostering strategic partnerships, healthcare systems can successfully implement the multi-level framework. These foundational steps enable sustainable equity-driven healthcare delivery aligned with the transformative goals of the Quintuple Aim. They also position health systems to contribute to the global movement toward inclusive, digitally enabled, and equity-centered healthcare transformation.

Implications for future research

The pursuit of digital health equity within LHS presents critical opportunities for research to inform best practices and refine models. Key areas include building the economic case for equity, guiding sponsorship decisions, and evaluating long-term impacts.

Building the economic case for health equity

Research should examine cost savings and health improvements from equity-focused initiatives, such as Medicaid Accountable Care Organizations (ACOs) that reinvest savings into upstream interventions. Demonstrating the financial viability of such models can encourage broader adoption and strengthen the rationale for prioritizing health equity within value-based care systems [74]. Comparative economic analyses with countries employing social prescribing, such as the UK and New Zealand, could provide additional insights into globally adaptable investment strategies [13, 64].

Guiding research sponsorship decisions

Establishing criteria for funding equity-centered initiatives is essential. Research should identify the best practices for evaluating projects that integrate SDOH into EHRs, balance downstream and upstream strategies, and employ culturally competent approaches. These efforts can ensure that resources are allocated to initiatives with the greatest potential for equitable impact.

Evaluating systemic and long-term impacts

Longitudinal studies can assess how digital health equity initiatives affect healthcare access, quality, and cost among marginalized populations. For example, evaluating broadband expansion and digital literacy programs can provide evidence of their role in reducing structural barriers and improving outcomes over time. International studies, such as Australia’s longitudinal research on telehealth uptake among First Nations communities, may also offer valuable models for culturally grounded evaluation [20].

Comparative analysis of frameworks

Assessing implementation frameworks such as CFIR and RE-AIM across diverse healthcare settings can offer insight into effective strategies for integrating SDOH into LHS and overcoming context-specific barriers.

Investigating cultural competency in digital tools

Research on designing culturally tailored digital tools that address language, literacy, and cultural norms will inform best practices for fostering trust and engagement among historically underserved populations.

Exploring scalability of the multi-level framework

Future research should examine the scalability of the proposed multi-level framework by evaluating its adaptability across various healthcare settings. Studies can identify key facilitators and constraints, such as leadership support, resource availability, and alignment with policy incentives, that influence implementation success at scale.

Examining leadership mindsets, organizational readiness, and implementation contexts

Building on the limitations identified in this study, future research should explore how healthcare leaders conceptualize their institutions’ responsibilities in addressing both traditional and digital SDOH. Variation in leadership mindset and organizational culture, particularly across settings such as academic medical centers, community hospitals, and safety-net systems, can significantly influence the prioritization, interpretation, and implementation of equity-driven strategies. As emphasized in the Consolidated Framework for Implementation Research (CFIR), factors such as leadership engagement, organizational readiness, and alignment with mission are central to implementation success [55]. Investigating these contextual influences can generate critical insights into how institutions adopt, adapt, or resist multi-level equity frameworks. Understanding these dynamics is essential to translating conceptual models into practical tools that support strategic planning, build institutional commitment, and foster a broader culture of equity in healthcare transformation.

Limitations

While the proposed multi-level framework offers a comprehensive and theory-informed roadmap for advancing digital health equity, several limitations merit acknowledgment. First, the integration of diverse theoretical models into a single structure required inherent simplifications. While each model contributes distinct strengths across individual, organizational, and systemic dimensions, aligning them into one unified framework may limit their full explanatory power when applied in isolation or in highly complex settings.

Second, the framework assumes a level of organizational readiness and leadership alignment that may not exist uniformly across healthcare institutions. Differences in culture, mission, and resourcing between academic medical centers, community hospitals, and safety-net settings can influence the feasibility and sustainability of equity-focused initiatives. Additionally, institutional variation in leadership mindset, particularly regarding the perceived scope of hospital responsibility for upstream determinants, may affect how the framework is interpreted and applied. These contextual differences are not unique to the United States and have also been reported in international settings, such as the UK’s National Health Service and Australia’s primary health networks, underscoring the framework’s adaptability across health systems with varying structures and equity mandates [13, 20].

Third, stakeholder misalignment poses a significant barrier. Conflicting incentives between health systems, payers, policymakers, and technology developers can hinder collective action on equity goals, especially when immediate financial returns are not evident. Fourth, policy and regulatory constraints continue to limit progress in key upstream areas. Gaps in incentives for SDOH-EHR integration, insufficient broadband infrastructure, and fragmented data-sharing mechanisms present persistent implementation challenges. These challenges are echoed globally, as evidenced by emerging literature from countries like India and Canada, where disparities in interoperability and infrastructure remain critical hurdles to achieving digital inclusion [12, 29].

Despite these limitations, the multi-level framework remains a highly relevant and practical tool for healthcare leaders, policymakers, and technology developers. It invites critical reflection on the broader value proposition of addressing SDOH, not only to promote equity, but also to improve outcomes, reduce preventable costs, and build the foundation for sustainable transformation. As healthcare systems shift toward value-based care, equity is not a peripheral concern but a core operational priority. This framework can support strategic planning, guide investment decisions, and reinforce the case for embedding equity into the heart of health system design and accountability.

Conclusion

Achieving digital health equity within Learning Health Systems is both a moral imperative and a strategic necessity for realizing the transformative goals of the Quintuple Aim. This paper has presented a theoretically grounded, multi-level framework that integrates SDOH data, implements balanced intervention designs, and facilitates strategic transitions from downstream to upstream solutions. By synthesizing practical insights with robust theoretical underpinnings, this framework offers a cohesive roadmap for healthcare systems to advance equity in digital health delivery.

The framework’s strength lies in its alignment across micro, meso, and macro levels, ensuring that interventions are not only immediate and impactful but also systemic and sustainable. Drawing from information systems theories, socio-ecological models, organizational learning, implementation science, and systems thinking, it equips stakeholders with actionable strategies to address urgent social needs while driving structural change. This paper also emphasizes the critical need for continuous learning and adaptation, offering tools and strategies to operationalize the framework in diverse healthcare settings. Although developed with illustrative examples from the United States, the framework’s emphasis on theoretical generalizability and implementation adaptability makes it highly applicable across global healthcare systems. By design, the framework accommodates varying delivery structures and sociopolitical contexts, enabling its relevance beyond U.S. borders. International parallels, such as digital health reforms in Denmark, Australia, and India, affirm the broader relevance of the insights and strategies proposed.

Realizing this vision demands a collaborative effort across healthcare providers, policymakers, researchers, and technology developers. Healthcare organizations must prioritize equity-centered practices, cultivate partnerships, and employ iterative learning to scale and sustain impactful interventions. Policymakers must foster enabling environments through incentives, infrastructure investments, and equity-focused accountability mechanisms. Researchers have a vital role in refining evidence-based strategies, ensuring that interventions are effective and adaptable across populations. Technology developers must also engage proactively, designing inclusive digital tools that address barriers such as digital literacy, language accessibility, and connectivity, ensuring that innovations are equitable by design.

Ultimately, achieving digital health equity requires aligning innovation with inclusivity and fostering a collective commitment to systemic change. By embedding equity into the core of healthcare delivery, LHS can develop adaptive and resilient structures that effectively address the needs of marginalized and underserved populations. This approach ensures that digital health innovations function as integral solutions for reducing disparities, creating a future where equitable healthcare is a measurable and attainable standard for all.

Abbreviations

ACA

Affordable Care Act

CHNA

Community Health Needs Assessment

CMS

Centers for Medicare & Medicaid Services

COVID-19

Coronavirus Disease 2019

DSRIP

Delivery System Reform Incentive Payment

EHR

Electronic Health Record

FCC

Federal Communications Commission

HHS

Health and Human Services

HITECH

Health Information Technology for Economic and Clinical Health

HRSN

Health-Related Social Needs

ICT

Information and Communication Technology

IRB

Institutional Review Board

LHS

Learning Health System

OL

Organizational Learning

PRAPARE

Protocol for Responding to and Assessing Patients’ Assets, Risks, and Experiences

RE-AIM

Reach, Effectiveness, Adoption, Implementation, Maintenance

SDOH

Social Determinants of Health

SEM

Socio-Ecological Model

STS

Socio-Technical Systems

TAM

Technology Acceptance Model

Author contributions

PR conceptualized and led the design, drafting, and revision of the manuscript. KAA contributed to writing, editing, and refining the manuscript. RS contributed to writing and editing. All authors read and approved the final manuscript.

Funding

No funding was received to support this work.

Data availability

No datasets were generated or analysed during the current study.

Declarations

Ethics approval and consent to participate

Not applicable. This study does not involve human subjects research and does not require Institutional Review Board (IRB) approval.

Author information

The authors bring a multidisciplinary perspective to the study of digital health equity. PR, is a Professor in the Department of Population Health and Leadership with expertise in health services research, public health, and health equity. KAA is an Associate Professor of Management with expertise in organizational behavior and inclusive leadership, and RS is an Assistant Professor of Accounting and Information Systems with expertise in health informatics and digital transformation. Together, the team integrates knowledge from healthcare, business, and information systems to address complex challenges at the intersection of health equity and digital innovation.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.