For years, we have talked about primary healthcare, universal health coverage, and integrated care. Yet, when a person actually falls sick, what they encounter is anything but integrated. They navigate a maze of facilities, providers, schemes, and digital platforms that rarely speak to one another. The result is duplication, delay, high out-of-pocket spending, avoidable complications, and an erosion of trust in the health system.
Over the past two years, we at ACCESS Health, along with government partners, development partners, and academic collaborator,s have been working on care coordination not as a buzzword, but as a concrete health systems function. What has become clear is this: if we are serious about value-based, people-centred care, then care coordination and integrated care are not optional innovations. They are core health system capabilities.
Fragmented journeys, not fragmented diseases
Modern healthcare in India, as in many low- and middle-income countries, has been built program by program, scheme by scheme, disease by disease. This vertical orientation helped scale specific interventions, but it also produced fragmented care journeys. A person with diabetes and heart disease may be registered in one primary care programme, hospitalized under a different insurance scheme, and seen by multiple specialists in both public and private facilities, each maintaining its own record, each making decisions with limited visibility of the whole picture.
COVID-19 exposed this fragmentation in stark terms. During the pandemic, several states were forced to improvise coordination mechanisms almost overnight: triage centres, bed management systems, digital dashboards, and call centres that followed patients across facilities. Once the crisis passed, many of these arrangements fell away, but they left behind an important lesson. When systems choose to coordinate, outcomes improve, and waste is reduced. When they do not, citizens pay the price.
Care coordination, in this sense, is not a single project. It is the deliberate organisation of care across time, providers, and levels of the system so that every patient’s journey is coherent, continuous, and aligned with their goals, not with institutional silos.
What the evidence told us
Recognizing both the promise and the conceptual confusion around care coordination, our team, in collaboration with CMC Vellore, undertook one of the first systematic reviews of care coordination models in Southeast Asia and the LMIC context. We analysed over 4,000 studies and distilled 46 primary studies that directly engaged with the coordination of care. Three things became evident.
First, the evidence confirmed what practice had long suggested: fragmented care leads to repeated tests, conflicting treatment plans, inefficient use of human and financial resources, and compromised quality. The imperative for care coordination is rooted in avoiding these predictable failures.
Second, while global agencies such as AHRQ and WHO have developed useful definitions and frameworks, most of them emerged from high-income settings. They do not fully reflect the complexity of mixed health systems like India’s, where public and private providers, multiple payers, and varying levels of digital readiness coexist.
Third, across contexts and disease areas, a set of recurring elements began to appear. Effective care coordination was usually team-based, with clearly defined roles for nurses, coordinators, and multi-disciplinary teams. It relied on continuous training and supervision, and on better integration between services and policies. It used digital health tools and health information systems to track patients, support decisions, and close feedback loops. It did not end at discharge. Community and home-based follow-up, reminder systems, and patient education were integral to keeping people well and preventing readmissions.
We tried to look at care coordination from three perspectives: the health system’s need to use resources wisely, the provider’s need to deliver safe and coherent care, and the patient’s need for a dignified, navigable journey. We also added a fourth perspective that is often neglected in theory: that of the administrator, who must make these models operational, measurable, and financially viable.
We learnt that it is neither possible nor desirable to impose a single “universal” framework for care coordination on all settings. India’s geographies, health markets, and institutional capacities are too varied. What we need instead are differentiated models that are context-appropriate but share a common set of principles and building blocks.
Three pilots, one shared purpose
It is this search for context-specific yet principled models that has guided our current work in three very different settings: a public purchaser in one large Indian state, a public provider system in another, and a private provider-driven integrated care model in a large metropolis. Together, they illustrate how the same idea can be translated along different institutional pathways.
In Uttar Pradesh, a large state in north India, our work here has been rooted in Ayushman Bharat Pradhan Mantri Jan Arogya Yojana (PM-JAY), which covers nearly nine crore people in the state. Here, care coordination began from the reality that most PM-JAY use was through unplanned walk-ins and word of mouth. There were no clear forward or backward referral pathways, limited citizen visibility into which facilities were empanelled for which services, and few mechanisms for structured follow-up.
We worked with the State Health Agency to gradually transform the PM-JAY call centre from a narrow grievance and information helpline into a multi-channel care coordination hub. Today, citizens can discover empanelled hospitals, schedule appointments, receive basic navigation support, and provide structured feedback on their experience. A citizen-facing app and chatbot complement the assisted channels. In parallel, we are supporting digital integration between PM-JAY information systems and primary health platforms such as health and wellness centre applications, so that beneficiaries can be identified, followed up, and, where needed, “handed back” to primary care for continuity. The work is modest compared to the scale of Uttar Pradesh, but it has already shown that even a large public purchaser can start orienting its systems around coordinated journeys rather than isolated claims.
In another Indian state, our partnership with the health department has focused on a different question: how can a strong public health system coordinate care within its own network, from primary care centres to higher hospitals? A district-level care coordination pilot builds on the state’s long-standing health information platform and the triage and bed-management innovations that emerged during COVID-19.
The pilot did not create a parallel system. It used existing infrastructure and human resources, but assigned new roles and workflows. Care coordinators, drawn from existing hospitals and district-level staff, were appointed at different levels of care. Their job was to ensure that once a patient entered the system, their journey across facilities was guided, documented, and tracked. The emphasis was on decongesting higher facilities through protocol-based referrals, strengthening the use of electronic health records, and closing the loop through structured feedback collected via an existing health helpline. Over time, the pilot has expanded to over a hundred facilities, demonstrating not only improved use of the health information platform by the healthcare professionals but also better patient experience and more rational use of services.
In the southern metropolis of Hyderabad, through TRUST Healthcare and Durgabai Deshmukh Hospital, we have been attempting perhaps the most comprehensive version of this idea: building a people-centred, integrated, value-based model of care anchored in a single provider ecosystem but connected to the broader health information exchange under Ayushman Bharat Digital Mission. Our starting point has been clinical: well-defined care pathways for common symptoms, acute conditions, procedures, and chronic diseases that together cover the majority of health needs.
We have insisted on robust paper-based health records coexisting with structured electronic health records, with deliberate processes to convert unstructured data into usable, audited digital data. This hybrid approach respects clinical workflow while preparing the ground for automation. We have linked our legacy systems to ABDM through an open-source “wrapper” so that patients’ records can eventually flow into national personal health records.
Around this, we are building disease registries, chronic care programmes (using diabetes as a tracer condition), nurse-led handover systems across settings, and a bi-directional referral network with trusted external providers. On top of the data layer, we are now designing AI-enabled applications: dynamic case summaries for referrals, decision support tools for doctors and nurses, and population dashboards that allow us to track long-term outcomes, premature deaths, and avoidable hospitalizations. Our aim is simple but ambitious: to show that a provider-driven, value-based model can maximize outcomes for a defined population while reducing per capita costs by eliminating low-value care.
From digital projects to digital backbone
Across these three settings, a common thread has emerged. Care coordination at scale is impossible without a digital backbone, but it also cannot be reduced to a “digital project”. Many states and providers now have multiple platforms, apps, and dashboards. What is missing is an architecture that ties them together around the person’s journey and the health system’s goals.
In our work, we have treated the digital layer as an enabler of three things. First, continuity of information, so that wherever a person seeks care, their essential health data can follow them in a structured, secure, consented manner. Second, continuity of decision-making, so that clinicians and nurses at each touchpoint see not only past records but also risk flags, standard pathways, and suggested next steps. Third, continuity of accountability, so that administrators and payers can see, in near real time, whether care is timely, guideline-concordant, equitable, and financially sustainable.
Digital transformation, however, is not just a technical challenge. It is a change management and financing challenge. Small and medium-sized providers, and even public facilities, will need support to adopt interoperable health information systems. States will need to invest in training, governance reforms, and blended financing models, including CSR and philanthropic capital, to underwrite the transition. If we want care coordination to be more than a few pilots, we must make the economics visible and favourable for both payers and providers.
A health systems imperative, not a luxury
Care coordination is sometimes perceived as a “nice to have” add-on, a navigation service, a call centre, or a digital layer that sits on top of business as usual. I believe we must stop thinking of it this way. In settings where resources are constrained and disease burdens are rising, uncoordinated care is a luxury we can no longer afford.
Our work is still evolving. We have not solved all the challenges of scale, interoperability, or behaviour change. But we have seen enough to be confident about the direction of travel. When systems deliberately coordinate care through teams, processes, data, and digital infrastructure, patients experience less friction, providers work with more clarity, and payers have a realistic path to value-based purchasing. Care coordination and integrated care are not a separate agenda from health systems strengthening. They are at its heart.