From Compliance to Ecosystem Adoption: A Mixed-Methods Assessment of HL7 FHIR Implementation in India

1. Introduction

Interoperability underpins digital health transformation, allowing health information to be exchanged securely and seamlessly across disparate systems while supporting continuity of care through longitudinal patient records. As countries invest further in digital health infrastructure, adopting internationally recognised health data standards has become central to reducing fragmentation, improving data quality, and enabling integrated care delivery. Among the standards available, HL7 Fast Healthcare Interoperability Resources (FHIR) has emerged as the leading global framework for health information exchange [1,2]. Developed by Health Level Seven International (HL7), a global standards-development organisation, FHIR evolved out of earlier, more complex frameworks, specifically HL7 v2 and v3, to overcome longstanding interoperability constraints. Its architecture is organised around modular, discrete Resources (e.g., Patient, Observation, Medication) and draws on modern web technologies, including RESTful APIs and JSON/XML serialisation, which together reduce implementation barriers and accelerate digital health innovation.

FHIR has become a leading global standard for interoperability across electronic health records, mobile health applications, and national data networks [2]. It is mandated or strongly encouraged in jurisdictions such as the United States, the United Kingdom, Australia, and Brazil, where it has supported greater data liquidity, improved patient access, and reduced administrative burden. This widespread acceptance has cemented FHIR’s position as one of the leading standards for modern health information exchange globally. Uptake has followed a similar trajectory across the WHO South-East Asia Region, with a growing number of countries embedding the standard into their national digital health systems. Yet, despite this momentum, rigorous, systematic assessments of FHIR implementation and adoption maturity remain scarce in low- and middle-income countries (LMICs), and evidence specific to the South-East Asia Region is particularly limited. National adoption of FHIR does not automatically produce meaningful interoperability. Countries may publish implementation guides, create sandboxes, and certify vendors while still lacking the institutional mechanisms required for routine exchange, data quality, semantic consistency, workflow integration, and reuse. The critical transition is therefore from standards adoption to implementation maturity: whether implementers have the incentives, tools, governance pathways, terminology services, validation infrastructure, and workforce capacity needed to use FHIR beyond programme compliance.

In the Indian context, FHIR provides the critical technical foundation for the Ayushman Bharat Digital Mission (ABDM), the national programme establishing a longitudinal, consent-based digital health infrastructure [3]. ABDM uses FHIR profiles as the national data standard, ensuring that health information exchanged between hospitals, laboratories, and insurers is uniformly structured [4]. Notably, while FHIR defines the data model and exchange semantics, secure transmission occurs through ABDM’s Gateway APIs rather than native FHIR RESTful APIs—a design choice intended to align with India’s consent and privacy frameworks. FHIR has been further localised by the National Resource Centre for EHR Standards (NRCeS), whose India-specific Implementation Guide underpins ABDM and the National Health Claims Exchange (NHCX) [4]. This adoption aligns with India’s broader digital health policy architecture and creates a foundation for longitudinal, consent-mediated health information exchange across providers, payers, laboratories, and patient-facing applications.

In addition to ABDM and NHCX, FHIR serves as a building block for a wider transformation of the ecosystem. This open and modular design can help streamline integration, encourage private sector innovation, and enable scalable applications across various domains such as telemedicine, remote patient monitoring, clinical decision support, and AI/ML-based analytics [5]. The Indian health system can harness the power of real-world evidence for multiple applications, such as research, predictive modelling, and public health surveillance, by standardising clinical data as FHIR resources. However, for this to become a reality, policy attention needs to be paid beyond compliance to long-term adoption of the ecosystem approach. This means that incentives should be clear, governance strengthened, capacity built, and public and private digital health systems’ aligned.

In its current state, India’s healthcare system presents a uniquely demanding context for this transition. It is among the most diverse and complex health systems in the world, spanning over 1.5 million healthcare facilities [6], thousands of diagnostic laboratories, and an estimated 6 million health workers [7], with care delivery ranging from large tertiary hospitals in metropolitan centres to single-provider clinics in rural areas [8]. But the system is very fragmented, both institutionally and technologically. Public services are organised in a number of vertical programmes within the central and state government and are often based on separate, non-interoperable digital solutions [8]; the private sector (which accounts for over 70% of outpatient care and over 60% of inpatient care) consists of thousands of small providers with their own health IT solutions developed in-house or using proprietary software [8]. As a result, patient data stays fragmented and linkages in patient journeys remain broken between care settings.

Despite these structural hurdles, India’s digital health landscape is expanding rapidly. ABDM, NHCX, and a growing number of state-led programmes are creating foundational layers of digital public infrastructure, while community-led initiatives such as HL7 India and the FHIR India Community are fostering bottom-up technical capacity [9]. With the wide-scale adoption of FHIR, understanding the transition from policy adoption to ecosystem-wide implementation becomes all the more important for large, federated health systems such as India’s, where digital health programmes must reconcile centralised national standards with vast sub-national diversity. To date, however, no systematic, evidence-based assessment has examined the gap between India’s policy-level FHIR commitments and its practical, ecosystem-wide adoption.

This study assessed the current landscape of HL7 FHIR adoption in India and identified the barriers and strategic priorities shaping its transition from compliance-driven adoption to ecosystem-wide interoperability. Specifically, the assessment sought to: (i) map current FHIR adoption and maturity across national programmes, state systems, and private-sector actors; (ii) assess alignment between India’s national FHIR profiles and selected global implementation cores; (iii) identify institutional, technical, and operational barriers constraining adoption at scale; and (iv) derive strategic priorities for strengthening India’s FHIR ecosystem. The analysis focuses not only on whether FHIR has been adopted, but on whether the governance, incentives, technical infrastructure, workforce capacity, and implementation support mechanisms needed for sustainable adoption are in place.

2. Methods

2.1. Study Design

We conducted a rapid mixed-methods implementation assessment of HL7 FHIR adoption in India between September and October 2025. The study was designed as a national implementation assessment rather than a formal conformance audit. It combined stakeholder survey data, semi-structured interviews, desk research, field validation, and international benchmarking to examine both technical and ecosystem-level dimensions of FHIR adoption. Quantitative and qualitative data were collected concurrently and integrated during analysis. The assessment was led by eGov Foundation with support from the WHO Regional Office for South-East Asia.

The assessment addressed four questions: (i) what is the current landscape of FHIR adoption in India; (ii) what maturity levels are visible across different stakeholder groups; (iii) what institutional, technical, and operational barriers are limiting adoption; and (iv) what strategic priorities can support a transition from compliance-oriented adoption to ecosystem-wide interoperability. The study was intended to generate an implementation-oriented baseline and strategic assessment; it was not designed to estimate the national prevalence of FHIR adoption or to conduct system-level technical certification.

2.2. Desk Research and Practitioner Insights

Desk research was undertaken to establish the policy, technical, and implementation context for FHIR adoption in India. Materials reviewed included ABDM and NHCX documentation, NRCeS FHIR Implementation Guide material, national digital health policy documents, global HL7 resources, implementation guides from selected comparator countries, and publicly documented pilot and production deployments across clinical, insurance, and digital health domains. The review also examined international examples of FHIR governance, implementation support infrastructure, validation tooling, terminology services, and incentive mechanisms. Documents and artefacts were included if they described India’s digital health architecture, ABDM or NHCX implementation requirements, NRCeS FHIR profiles, national or international FHIR implementation guides, terminology services, conformance testing, sandbox infrastructure, health information exchange, digital health procurement, or documented FHIR-related pilots and production deployments. Information was extracted on policy context, technical architecture, implementation guide structure, FHIR resources and profiles, terminology bindings, validation tooling, governance arrangements, evidence of deployment, and implications for implementation maturity.

The desk review was used to characterise India’s national FHIR architecture, identify areas of alignment and divergence between NRCeS profiles and selected global implementation cores, document visible pilots and production deployments, and contextualise survey and interview findings. The study team also drew on practitioner experience from ongoing engagement with digital health interoperability initiatives in India and other countries. These practitioner insights were used to both interpret findings and triangulate with survey, interview, and documentary evidence before inclusion in the results.

2.3. Stakeholder Survey

A structured online survey was conducted between September and October 2025. The survey used purposive sampling of stakeholders known to be engaged in digital health, interoperability, ABDM implementation, FHIR adoption, or related health IT activities. It therefore over-represents digitally engaged implementers and should not be interpreted as representative of all healthcare providers or health IT organisations in India. Survey items included closed-ended questions on perceived maturity, implementation status, barriers, and support needs, as well as open-text questions allowing respondents to describe implementation challenges and recommendations. Twenty-two completed responses were received from stakeholders across India’s digital health ecosystem, including health information system vendors, hospitals, insurers, third-party administrators, diagnostic laboratories, digital health start-ups, government digital health teams, and academic institutions.

Survey responses were analysed descriptively. Closed-ended responses were summarised to identify recurring patterns in perceived maturity and adoption barriers. In responses where participants were asked to select their top barriers, responses were summarised by frequency of selection. Open-text responses were reviewed thematically, with attention to recurring terms and concepts such as training, support, tooling, governance, incentives, and compliance. Because the survey used purposive ecosystem sampling rather than random sampling, findings were interpreted as an implementation-oriented baseline rather than a statistically representative estimate of national adoption.

2.4. Key Informant Interviews

Ten semi-structured key informant interviews were conducted with stakeholders selected from the survey sample and broader implementation networks. Participants included representatives of HIS vendors, healthcare provider organisations, insurers and third-party administrators, government digital health teams, and system integrators engaged in ABDM- or FHIR-related implementation.

Interviews explored participants’ understanding of FHIR as distinct from ABDM, implementation experiences, perceived technical and institutional barriers, governance and policy clarity, workforce and tooling constraints, business incentives, and priorities for scaling adoption. Interview analysis used a pragmatic thematic approach. Notes were reviewed and coded against the study objectives, with initial categories reflecting institutional, technical, and operational domains. Additional themes were added inductively when recurrent issues emerged, including confusion between ABDM compliance and FHIR conformance, absence of clear incentives, uncertainty about validation pathways, and the need for focused high-value public-sector use cases. Themes were retained when they appeared across more than one data source or were judged to be important for explaining implementation barriers. These themes were triangulated with survey findings and desk-review evidence to identify recurring bottlenecks and strategic priorities.

2.5. Field Validation

Preliminary findings from the survey, interviews, and desk review were validated through structured conversations with early implementers, including health-IT vendors, provider organisations, and system integrators actively engaged in ABDM- or FHIR-based implementation. These conversations were used to assess whether the identified barriers reflected implementation realities, refine the wording of bottlenecks, and validate the practical relevance of proposed recommendations. Because the field validation was qualitative and implementation-oriented, it was used to strengthen interpretation and recommendation development rather than to generate additional quantitative estimates.

2.6. International Benchmarking

India’s FHIR adoption landscape was compared descriptively with selected international FHIR ecosystems: the United States, the United Kingdom, Australia, Singapore, and Israel. These comparator settings were selected because they have publicly documented FHIR governance arrangements, implementation support infrastructure, developer ecosystems, terminology services, conformance or certification mechanisms, and incentive or procurement levers. Benchmarking was based on publicly available documentation and was used to identify transferable lessons rather than to generate a statistical ranking.

Comparator ecosystems were assessed across five domains: (i) governance and stewardship of national FHIR specifications; (ii) maturity and publication model of implementation guides; (iii) developer enablement, including sandboxes, validators, test suites, and reference implementations; (iv) terminology infrastructure, including medication and laboratory terminologies; and (v) incentive alignment through regulation, procurement, reimbursement, or certification. These domains were selected because they emerged from the Indian data as recurring constraints and are visible in mature FHIR ecosystems. Given differences in health-system structure, survey instruments, and data availability, findings should be interpreted as illustrative and contextual rather than directly comparable across countries.

Table 1 provides a summary of data sources and analytical contributions.

2.7. Synthesis Process

Findings from desk research, survey responses, interviews, field validation, and international benchmarking were triangulated to develop an integrated assessment of India’s FHIR adoption landscape. Quantitative survey patterns guided the identification of recurring barriers, while qualitative interview themes and desk-review evidence informed interpretation and recommendations.

A study-derived FHIR implementation maturity landscape scale was developed to summarise variation in implementation maturity across stakeholder groups. The scale was not intended to replace the formal HL7 FHIR Maturity Model or any validated national digital health maturity framework. It was developed inductively for this assessment and should be interpreted as a descriptive baseline. Level assignments were based on triangulated evidence from self-reported maturity, interview narratives, and desk-review evidence of implementation status. Candidate barriers were generated from the convergence of survey responses, interview themes, desk-review findings, and field validation. Similar barriers were merged and grouped into three domains: institutional and policy, technical and infrastructure, and operational and capacity. The final list of 21 barriers was retained because each barrier was supported by either multiple data sources or by strong implementation relevance identified through field validation.

2.8. Ethics

No patients, clinical procedures, or personally identifiable health records were involved at any stage of this work. All participants were professionals contributing in their organisational or technical roles — drawn from HIS vendors, hospitals, insurers and TPAs, diagnostic laboratories, digital health start-ups, government digital health teams, and academic institutions. Each was briefed on the assessment’s purpose ahead of time and gave consent before taking part in the survey or interviews. Individual responses were stripped of identifying detail during analysis and are presented only in aggregate form.

Given the nature of this work as an institutional, programme-level review of digital health interoperability rather than a clinical study involving human subjects, it fell outside the scope requiring formal ethics committee clearance under prevailing Indian research-governance norms, including the ICMR National Ethical Guidelines for Biomedical and Health Research Involving Human Participants, which apply to biomedical and clinical research rather than assessments of this kind. At no point was data about individual patients or service users accessed or reviewed.

3. Results

3.1. National Policy and Implementation Landscape

The use of HL7 FHIR has been consistently increasing in India since 2020 with the support of Ayushman Bharat Digital Mission (ABDM) and National Health Claims Exchange (NHCX). These two national programmes have laid the groundwork for interoperability of health data within the country, through the development of FHIR profiles, gateway APIs, and the development of a FHIR sandbox environment that will influence the approach to standards-based health data exchange [3]. The stakeholder ecosystem (Appendix A) spans national programmes, state health missions, private hospital chains, diagnostics networks, insurers and third-party administrators, digital health start-ups and PHR vendors, and ABDM adaptor/middleware providers bridging smaller facilities into the national ecosystem. Evidence also identified a growing inventory of pilot and production deployments across clinical, insurance, and digital-health domains (Table 2), most of which were anchored to ABDM or NHCX compliance requirements rather than autonomous innovation.

The inventory indicates that India has progressed beyond policy adoption into early implementation across several domains, including e-prescriptions, laboratory result sharing, personal health record applications, hospital EMR integration, telemedicine platforms, and claims exchange. However, most deployments remain linked to ABDM or NHCX compliance requirements rather than autonomous innovation. The evidence also shows uneven adoption across sectors and geographies: larger private actors and national programmes are more advanced, while smaller providers, rural facilities, and many state systems remain at earlier stages of readiness. Desk review also highlighted India’s community-based infrastructure, which includes the FHIR India Community and HL7 India as institutional anchors involved in connectathons, workshops, and meetups alongside national activities and helping to validate Implementation Guides for India.

3.2. Technical Alignment with Global FHIR Cores

The Indian national Implementation Guide (v6.5.0) is based on HL7 FHIR Release 4 (R4), consistent with the version of the US Core (v6.1.0; HL7 International, n.d.) and AU Core (HL7 Australia & Australian Digital Health Agency, n.d.), which allows standard validators (e.g., HAPI-FHIR) to validate Indian resources without changes (National Resource Centre for EHR Standards, 2024). However, the desk review identified important areas of divergence from US Core and AU Core. These divergences are not necessarily weaknesses; some reflect India-specific requirements around identity, consent, and national programme architecture. Yet in their current form, several add real adoption friction beyond mere implementation effort: certain profiles, extensions, and code definitions are not yet fully supported by standard FHIR tooling, making conformance harder to verify in practice; prescriptive national compositions introduce rigidity; and both NHCX claims workflows and national terminology remain works in progress. Unless addressed through well-packaged implementation guides, public validators, and terminology services, these divergences risk slow or reluctant adoption rather than only increased implementation effort (Table 3).

At the version level, India is broadly aligned with global practice through the use of FHIR R4. At the profile level, India introduces national identifiers such as ABHA and context-specific extensions. For consent, ABDM uses a structured national consent artefact rather than relying solely on FHIR Consent or SMART-on-FHIR patterns. For terminology, India uses ICD-10, SNOMED CT, and LOINC to varying degrees, but lacks a mature national medication terminology comparable to RxNorm or the Australian Medicines Terminology; this gap is among the most significant constraints on prescription and claims portability, with downstream effects on semantic interoperability and analytics. For claims and insurance, NHCX represents an important payer-provider standardisation effort but diverges from frameworks such as CARIN Blue Button. These divergences increase the need for India-specific conformance testing, terminology mapping, implementation guidance, and developer support.

These findings suggest that India’s challenge is not lack of FHIR alignment at the base specification level, but the operationalisation of India-specific profiles and artefacts — and, where national compositions add rigidity without commensurate benefit, the design of those artefacts themselves. For record types where the “Record” wrapper adds limited value — such as prescriptions and diagnostic reports — alignment with the leaner, resource-based global approach could reduce developer burden; India-specific prescriptiveness may be better reserved for document types where national consistency is essential, such as discharge summaries and outpatient consultation records. More broadly, developers require accessible implementation packages, public validators, examples, synthetic datasets, terminology services, and conformance test suites to translate profile-level requirements into consistent implementation.

3.3. Participant Details

The stakeholder survey received 22 completed responses from organisations spanning HIS vendors, hospitals, insurers, and third-party administrators, diagnostic laboratories, digital health start-ups, government digital health teams, and academic institutions. Respondents were drawn primarily from software vendors and provider organisations, with smaller representation from academia, consultants, and government actors, suggesting that survey findings predominantly reflect the implementer perspective. This survey was complemented by ten semi-structured interviews conducted with HIS vendors, provider organisations, insurers/TPAs, government teams, and system integrators. Across both data sources, most participating organisations placed themselves at early stages of FHIR maturity, typically exploration or limited piloting, with only a small number reporting sustained operational use. Because participant recruitment was purposive and focused on stakeholders already engaged in digital health implementation, the findings should be interpreted as reflecting the perspectives of digitally engaged ecosystem actors rather than the wider universe of Indian healthcare providers. This is important because smaller providers, rural facilities, and frontline clinicians are likely to experience additional constraints not fully captured in this sample.

When asked to identify their top adoption challenges (selecting up to three; n=22), respondents most frequently cited the absence of clear economic incentives: “lack of funding or business incentives” appeared among the top three barriers for nearly two-thirds of respondents, making it the single most commonly reported constraint. Word-frequency analysis of open-text responses reinforced this pattern, with terms such as “training”, “support”, and “tooling” recurring most often, pointing to a parallel demand for structured enablement and shared infrastructure. Consistent with the maturity mapping below, most organisations self-positioned at exploration or limited-pilot stages, and only national programmes and a small number of large vendors reported sustained operational use.

3.4. Key Bottlenecks to FHIR Adoption

Despite strong national intent under the Ayushman Bharat Digital Mission (ABDM), adoption was found to remain fragmented and uneven. 21 barriers were identified through thematic analysis of the qualitative and quantitative findings. The most critical bottlenecks were institutional and financial in nature, shaped by limited non-compliance-based incentives, fragmented governance, and weak enforcement across a largely unregulated private sector. For many hospitals and health-tech vendors, FHIR implementation was perceived as complex and low-return, resulting in operational inertia and superficial integration. These systemic issues were further compounded by technical and operational constraints, notably a shortage of skilled FHIR professionals, difficulties integrating with legacy hospital and laboratory management information systems, and inadequate digital infrastructure in smaller and rural facilities. For providers still early in digitisation, the dual burden of digitising core operations while simultaneously achieving FHIR compliance was identified as prohibitively difficult without targeted financial support, simplified tooling, and sustained capacity-building.

The following subsections group these challenges into institutional, technical, and operational bottlenecks. Detailed description of each of the 21 barriers can be found in the Appendix C.

Institutional and policy. India’s FHIR adoption is constrained not only by technical limitations but also by the structural characteristics of the health ecosystem itself. The landscape remains fragmented, spanning national and state programmes, diverse private actors, and widely varying levels of digital maturity. This fragmentation makes it difficult to coordinate standards, align investment, or sustain interoperability beyond isolated pilots. Across all stakeholder groups, a recurring theme was the absence of strong incentives. For most implementers, FHIR adoption entails additional cost, complexity, and learning effort without immediate financial or operational reward; without tangible benefits such as faster reimbursement, reduced administrative load, or enhanced patient retention, interoperability efforts were often viewed as compliance obligations rather than value-creating opportunities. Compounding this is a highly centralised, compliance-driven governance model that leaves limited room for co-design or iterative feedback from the broader ecosystem. While such top-down direction has helped accelerate initial roll-out, it has also constrained innovation and ecosystem ownership, resulting in shallow, checklist-based conformance rather than meaningful data exchange.

Five themes emerged from interview data corroborating these institutional dynamics:

Lack of incentive. Interview participants frequently questioned the underlying business case for adoption; one participant described FHIR as “hard to implement” and questioned why organisations should make the effort absent tangible returns. Without clear benefits such as faster claims processing or reduced administrative burden, adoption was often experienced as a compliance exercise rather than an efficiency investment.

Complexity and learning curve. Interviewees described FHIR as technically complex and time-intensive to master. Many were unaware of global learning resources — such as HL7 FHIR Fundamentals training, international connectathons, or open-source toolkits — because these are not referenced within ABDM documentation.

Unclear compliance pathway. In the absence of a public validator or conformance test suite, interview participants reported persistent uncertainty about what constitutes “FHIR-compliant” implementation, which was described as fostering risk aversion and inconsistent implementation practices. Participants repeatedly called for national validation and sandbox environments.

Governance and policy clarity. Several participants identified fragmented or evolving guidance as a source of implementation hesitancy. While ABDM was widely recognised as the steward of national standards, stakeholders sought a more stable release process and clearer communication of updates.

Community and collaboration. Interviews carried a comparatively positive tone around peer collaboration, with references to community, open source, and connectathons suggesting an emerging belief that shared learning and open tooling could reduce the cost and complexity of adoption. This was tempered by the observation that many implementers continued to conflate “FHIR” with “ABDM,” underscoring a need for standalone capacity-building beyond compliance mandates.

Need for implementation focus. A recurrent theme across interviews was a perceived need for greater implementation focus: several participants felt that government-led initiatives could achieve stronger impact by concentrating on two to four high-value, demonstrable use cases — particularly within public-sector facilities — rather than pursuing universal rollout simultaneously.

Technical and infrastructure. While India’s adoption of HL7 FHIR R4 provides a robust foundation for health-data interoperability, implementers face persistent technical bottlenecks that affect scalability, conformance, and confidence. Many arise from the mismatch between existing health information systems (HIS) and FHIR’s data model, compounded by limited tooling, immature validation infrastructure, and weak ecosystem support for developers. India’s health-IT environment remains heterogeneous: decades of bespoke, locally customised software coexist with emerging ABDM-compliant products. Bridging these layers demands costly data transformation and sustained governance. Yet the lack of standardised tooling, certification clarity, and predictable version management renders implementation uneven and resource-intensive.

Operational and capacity. Even where technical readiness exists, day-to-day operational realities slow India’s FHIR implementation. Many healthcare organisations lack integrated workflows, defined accountability, and skilled personnel to operationalise standards. The result is fragmented execution, inconsistent data quality, and limited realisation of interoperability’s potential benefits.

Table 4 summarizes the key bottlenecks identified in each domain and their implication

3.4.1. Field Validation of Key Bottlenecks to FHIR Adoption

Field validation reinforced three cross-cutting findings. First, implementers distinguished between willingness to adopt FHIR and the practical cost of doing so without visible business returns. Second, stakeholders repeatedly identified the absence of public validators, packaged implementation artefacts, and practical troubleshooting support as a source of uncertainty. Third, implementers emphasized that FHIR is often understood through the lens of ABDM certification rather than as a reusable global interoperability standard. These findings strengthened the interpretation that India’s next phase requires not only technical specifications, but also incentives, tooling, community support, and clearer communication. Consolidated insights from the field are provided in Appendix D.

3.5. Triangulated Maturity Assessment from the Synthesis

Through triangulated integration of desk research, survey responses, and interviews, we developed a study-derived FHIR implementation maturity landscape scale (Table 5). The six-level scale summarises implementation depth across India’s ecosystem, ranging from basic awareness to ecosystem-wide scale and optimisation. It was developed for this assessment, drawing on the staged logic of established digital-health and health-IT maturity models, and is intended as a descriptive baseline rather than a validated maturity score. Level assignments were based on self-reported maturity, documentary evidence of implementation status, and interview descriptions of operational use.

Because this scale is descriptive and study-derived, level assignments should be interpreted as indicative of implementation depth rather than as formal certification of maturity. At the time of assessment, no stakeholder group was assessed as having reached Level 5 maturity. ABDM and NHCX represented the most advanced national implementations, functioning between operational and institutionalised maturity based on evidence of production deployment, sandbox infrastructure, and national programme integration. Large EMR vendors and hospital chains had reached operational use in selected workflows. Most state health departments, smaller HIS vendors, and smaller providers remained in exploration, sandbox testing, or limited-pilot stages. This distribution suggests that India’s FHIR adoption is broad in policy visibility but uneven in operational depth.

3.6. International Benchmarking

Benchmarking against five countries with established FHIR ecosystems, namely the United States, the United Kingdom, Australia, Singapore, and Israel, drew on desk-reviewed documentation of each comparator’s governance arrangements, implementation-support infrastructure, and incentive mechanisms. Across these systems, our findings indicate that successful FHIR adoption depends on more than technical alignment with the specification itself. Our findings found that it rests on three reinforcing levers, namely governance clarity, developer enablement, and economic incentives, which come together to translate a published standard into sustainable, large-scale practice. India’s efforts under ABDM and NHCX share comparable ambition with these mature ecosystems but differ in the depth of governance institutionalisation, tooling infrastructure, and incentive design, as summarised below.

Governance and procurement alignment. Australia’s experience illustrates how clear governance, paired with procurement leverage, can drive standards adoption at scale. The Australian Digital Health Agency (ADHA) embeds FHIR within national policy through its Digital Health Procurement Guidelines, which require that software purchased by health services support FHIR-conformant APIs, converting conformance into a market-driven expectation rather than a voluntary technical choice [10]. ADHA co-develops national core profiles (AU Core) together with HL7 Australia and CSIRO under a shared governance arrangement, in which one body publishes and the other governs, balancing technical rigour with community input [11]. This has supported focused, high-value national rollouts, including ePrescriptions, Secure Messaging, and the My Health Record system, rather than diffuse, simultaneous implementation across all use cases.

For India, this suggests that procurement could function as an underused lever: embedding FHIR conformance requirements within government software procurement, in collaboration with HL7 India, NRCeS, and vendors in profile co-development, could create vendor accountability without relying solely on regulatory mandate.

Regulation paired with open innovation. The United States demonstrates how statutory mandates and open application ecosystems can reinforce one another. The 21st Century Cures Act and CMS Interoperability Rules establish a legal requirement for FHIR-based patient data access, while SMART on FHIR standardises app security and launch protocols, enabling a large ecosystem of third-party clinical and consumer applications to connect to any certified EHR [12]. FHIR has additionally been extended into high-friction administrative workflows such as prior authorisation and claims processing.

India’s ABDM “Patient Access” architecture already parallels elements of this approach - the US experience suggests that pairing clear, enforceable regulation with a deliberate app-ecosystem strategy could help convert ABDM compliance into a platform for innovation, rather than treating the two as separate objectives.

Clinical leadership and change management. Singapore’s National Electronic Health Record (NEHR) illustrates the importance of clinical ownership alongside technical infrastructure. Clinical leadership roles bridge information technology and clinical teams to ensure that systems are designed around real clinical workflows, while a federated architecture allows FHIR APIs to overlay existing hospital systems rather than requiring wholesale replacement. FHIR underpins major national programmes such as Healthier SG, linking preventive and clinical care under a unified standards foundation [13].

This experience suggests that as India scales ABDM, technical infrastructure alone may be insufficient. Building clinical ownership of interoperability, positioning FHIR as an enabler of better care rather than solely a compliance requirement, is likely to be a necessary complement to governance and tooling investments.

Collaborative community development. Israel’s FHIR-IL community demonstrates the value of open, multi-stakeholder collaboration in localising a global standard. The community connects the Ministry of Health, health maintenance organisations (HMOs), vendors, and academia in a transparent, iterative process of co-developing local FHIR profiles and sharing implementation experience, which has helped link Israel’s highly digitised but historically siloed HMOs for patient access, research, and public health purposes [14].

Given the scale of fragmentation across India’s public hospitals, private chains, and small clinics, a comparable “FHIR India Community,” built on existing HL7 India and NRCeS foundations, could provide a similar participatory structure for co-creation and faster ecosystem-wide alignment.

Comparative findings by domain. Beyond these governance and community models, domain-specific benchmarking indicated a mixed picture of relative strength and lag. On laboratory and diagnostic reporting, India’s profiles were found to be closely aligned with global benchmarks, though requiring scale-up beyond the current pilot geography [15,16]. On prescriptions and claims, India diverged most substantially from international practice, primarily due to the absence of a national medication terminology comparable to RxNorm [17] or the Australian Medicines Terminology, alongside NHCX-specific claims structures that differ from frameworks such as CARIN Blue Button [18]. On consumer-facing personal health records (PHR) and patient access, India’s ABDM-linked application ecosystem appears relatively advanced compared with many LMIC settings, although direct comparative empirical evidence remains limited. However, it requires stronger cross-vendor governance to sustain consistency as the vendor base grows [12]. On state-level health information exchange, India was found to lag behind comparator countries such as Singapore [13] and Israel’s national HMO exchange [14], where FHIR-based exchange operates at a mandated national scale rather than on a state-by-state basis, as illustrated by India’s own state-level pilots such as the Kerala DHIS2–FHIR bridge [19].

3.7. Strategic Priorities and National Roadmap

Drawing the survey, interview, and benchmarking evidence together, the assessment identified a phased set of strategic priorities for moving India from compliance-driven adoption to ecosystem-wide interoperability (Table 6). A recurring theme from stakeholders was that government implementation capacity is finite and should be strategically directed: rather than pursuing universal rollout, national agencies could concentrate on two to four high-value public-sector use cases to demonstrate operational value, establish reusable templates, and attract wider ecosystem participation.

The roadmap is organised around seven mutually reinforcing priorities: participatory governance and stewardship; a layered, openly governed IG model — with the India Core as a recommended (not mandated) baseline; focused government implementation through a limited number of high-value public-sector use cases; meaningful incentives and policy alignment; developer tooling and shared sandbox infrastructure; capacity building and knowledge commons; and regional and global leadership. These priorities respond directly to the barriers identified above: governance reforms address fragmented stewardship, tooling addresses validation uncertainty, incentives address weak business rationale, and capacity building addresses workforce constraints (Table 7).

4. Discussion

4.1. Principal Findings

This mixed-methods assessment shows that India has established a strong national foundation for FHIR-aligned interoperability through ABDM and NHCX. National implementation guides, sandbox environments, consent-based exchange architecture, and early pilots across clinical, diagnostic, claims, and patient-facing applications demonstrate that FHIR-aligned exchange is feasible in selected national workflows. However, the wider ecosystem remains uneven in maturity. Most participating organisations are still at exploration or limited-pilot stages, and adoption is often driven by compliance with ABDM or NHCX requirements rather than by broader organisational use of FHIR for data quality, analytics, clinical workflow improvement, claims automation, or innovation.

4.2. Interpretation

The central finding is that India’s interoperability challenge has shifted from standards selection to ecosystem-wide adoption. FHIR has been integrated within national programme architecture, but it has not yet become shared infrastructure that the wider ecosystem can easily understand, validate, implement, and extend. The dominant barriers are therefore socio-technical rather than purely technical. They include weak business incentives, fragmented and rigid governance, limited public validation tooling, absence of comprehensive conformance test suites, terminology gaps, limited workforce capacity, and uncertainty about the distinction between ABDM compliance and FHIR conformance.

4.3. A Comparison with Mature FHIR Ecosystems

Compared with more mature FHIR ecosystems, India has made rapid progress in national programme adoption but has less mature developer-enablement infrastructure, conformance testing, procurement alignment, and terminology services. International experience suggests that successful FHIR adoption depends on three mutually reinforcing levers: clear and inclusive governance, robust developer tooling and validation infrastructure, and meaningful incentives for implementers. India’s next phase should therefore prioritise a few high-value public-sector use cases, establish public validators and sandboxes, embed conformance in procurement and reimbursement pathways, and institutionalise capacity building through a national FHIR learning ecosystem.

4.4. Policy and Implementation Implications

A key implication is that compliance alone is unlikely to produce meaningful interoperability. ABDM and NHCX have created the policy foundation and initial implementation pathways, but long-term adoption will require clearer value propositions for implementers. These may include faster claims processing, procurement preference, accreditation benefits, reduced administrative burden, improved patient access, analytics readiness, and participation in wider digital health networks. Without such incentives, FHIR risks remaining a programme-specific requirement rather than a reusable interoperability layer.

India’s experience also highlights the importance of layered and participatory governance. A single centrally controlled specification can accelerate early rollout, but as adoption deepens, implementers require transparent versioning, public comment, conformance testing, and mechanisms to contribute implementation experience back into national profiles. A layered model—India Core as a recommended baseline, domain-specific guides for priority areas, and programme-specific guides for ABDM, NHCX, and state implementations—could balance national consistency with ecosystem flexibility. Stewardship of each layer should rest with its domain community, with implementation experience flowing upward through a coordinated national platform.

The technical findings reinforce the need for public tooling and terminology infrastructure. India’s use of FHIR R4 provides a strong baseline alignment with global standards, but profile-specific validation requires well-packaged NRCeS artefacts, accessible validators, terminology services, synthetic datasets, and reference implementations. The absence of a national medication terminology comparable to RxNorm or AMT is particularly important for prescriptions, claims, analytics, and semantic interoperability.

4.5. Strengths and Limitations

This study has several strengths. It triangulated evidence from a structured stakeholder survey, semi-structured interviews, desk research, field validation, and international benchmarking. It included perspectives from implementers across vendors, providers, insurers, diagnostic laboratories, start-ups, government digital health teams, and academic institutions. It also linked operational findings to technical assessment of India’s FHIR architecture and to lessons from selected international ecosystems.

The findings should be interpreted with several limitations. First, the survey and interview samples were purposive and relatively small, and therefore are not statistically representative of India’s large and diverse health-IT ecosystem. Second, respondents were primarily implementers, especially vendors and provider organisations, with less representation from frontline clinicians, patients, rural facilities, and smaller providers. Third, maturity levels were self-reported or inferred from desk-review and interview evidence and were classified using a study-derived descriptive scale rather than a validated maturity instrument. Fourth, the study did not independently test payload quality, message volumes, clinical impact, or administrative outcomes of FHIR-aligned exchange. Fifth, the international benchmarking was descriptive and based on publicly available documentation, not a statistical comparison. Sixth, the findings represent a point-in-time baseline from September–October 2025 and may not capture subsequent changes in ABDM, NHCX, NRCeS implementation guides, or state-level deployments. Finally, the study did not assess implementation costs, cost-effectiveness, or return on investment, which should be priorities for future research.

5. Conclusions

India has moved beyond formal standards selection in selected national programmes, with ABDM and NHCX demonstrating the feasibility of FHIR-aligned exchange in defined workflows. However, ecosystem-wide adoption remains the main challenge: converting a centrally mandated standard into shared infrastructure that implementers can validate, trust, extend, and use beyond programme compliance. The dominant barriers are socio-technical rather than technical: misaligned incentives, centralised governance, limited shared tooling, terminology gaps, and constrained workforce capacity. Addressing these through participatory governance, balanced economic and procurement incentives, shared validator and sandbox infrastructure, and sustained capacity building—sequenced along the phased roadmap presented here—offers a credible path from compliance to ecosystem-wide interoperability. India’s experience offers practical lessons for other large, federated, and resource-diverse health systems seeking to move from interoperability by policy to interoperability by practice.