Health equity is increasingly being recognised as a critical pillar of sustainable business, linking social impact with long term resilience, governance accountability, and inclusive growth. In this context, this conversation with Rohit Bhagwat, Global ESG Committee Member & Office Managing Principal at ZS, offers timely and relevant insights into how organisations can move health equity from an ESG commitment to a system level driver of business value and measurable impact. Drawing on ZS’s deep experience in healthcare transformation, the discussion traces the shift in health equity from a peripheral concern to a core, outcome driven strategic priority within ESG frameworks. It examines common blind spots, the role of AI and advanced analytics in identifying underserved populations, and the need to operationalise social determinants of health. The interview also brings in an India lens, highlighting systemic challenges and the importance of data, partnerships, and governance in enabling scalable and inclusive healthcare solutions.
For more insights, read the full interview below.
Q&A
Q. From your experience working across global healthcare systems, how has the conversation around health equity evolved in recent years?
A. When we look at our work in global healthcare systems, it’s clear: the conversation around health equity has undergone a significant revolution. ZS views health equity as integral to its identity, particularly given its deep roots in healthcare and life sciences. The firm focuses on addressing social and environmental determinants of health by working closely with clients, nonprofits, and communities to help reduce disparities. Within ZS’s ESG framework, health equity is not treated as a standalone priority but is embedded across its environmental and social commitment
Earlier the focus was more on identifying disparities and pointing out access gaps but health equity has truly escalated into a strategic, outcome-driven priority for everyone - healthcare organisations and life sciences companies alike. Once identified, we need to quantify those inequities, actively address the social drivers of health, because those are critical and then design actionable interventions that demonstrably improve patient outcomes for underserved populations. It’s about creating more tangible impact.
At ZS, we pride ourselves in partnering with organizations to embed equity right into their core decision-making, utilizing really robust, data-driven approaches. For example, our Health Inequity Treatment Index (HITI) is designed to help quantify precisely where these inequities exist across different therapy areas. This isn’t just an academic exercise; it empowers our clients to zero in on specific, visible care gaps and then develop truly tailored strategies that genuinely make a difference.
Q. Health inequity is often seen as a public health issue. Why should company boards and ESG leaders also view it as a long-term business and sustainability risk?
A. Health inequity is a complex problem in today’s healthcare ecosystem. The WHO clearly highlights how these inequities lead to massive long-term costs and systemic inefficiencies. it erodes workforce productivity, shrinks future markets, amplifies social and regulatory pressure, and undermines health outcomes. From a governance and ESG standpoint there are operational risks, regulatory and investor risks, supply-chain and community risks.
ESG leaders are starting to treat health equity as both risk and growth thesis. mitigating inequity protects value (productivity, affordability, license to operate) and creates value (new segments, trust, innovation in prevention and access models).
ZS has explicitly made advancing health equity one of its three ESG goals, alongside empowering people and operating sustainably and responsibly, aligning ESG with its core vision of improving health outcomes for all. For us and our clients, health inequity is a systemic business concern that suppresses productivity, inflates costs and constrains market growth over decades. Our role as an ESG leader is to hard-wire health-equity considerations into strategy, analytics and innovation so that addressing inequity becomes core to value creation—not an optional add-on.
Q. What are some of the most common blind spots you see when organisations attempt to address health equity through ESG frameworks?
A. One key blind spot is limiting health inequity to ‘access to care’ only which ignores the broader Social Determinants of Heath (SDoH) such as income, housing, gender, informal work and environmental exposure. SDoHs account for nearly 80% of patient outcomes and each SDoH impacts different patients, differently.
Another blind spot is commonly created when health inequity is not embedded in strategy, data, products and partnerships as core, measurable business outcome. Tracking and reporting social indicators with actual health outcomes or disparities across segments helps in measuring whether the gap is widening or narrowing. ZS research notes fragmented data, limited sharing and inconsistent outcome measures as major barriers to addressing variations in care.
For organizations to address this, there is a need for robust partnership criteria, shared objectives, and aligned data infrastructure
Q. How can AI and advanced analytics help identify underserved populations without reinforcing existing biases or inequities?
A. Diverse data packs, explicit equity goals and strong guidelines against bias are elementary for AI and advanced data analytics to reveal disparities and patterns in access, behaviour and health outcomes. It all starts at building inclusive datasets to avoid reinforcing biases and inequities. Actively include under-represented groups, addresses to decode structural inequities. Define clear objectives, bias-mitigation techniques to reflect actual health need during AI model development. Regular equity audits to determine the model performance across demographic and geographic subgroups, and continuously recalibrate as care patterns and populations change.
AI can then use multi-source data to identify unmet needs, high disease burden against low treatment rates, healthcare provider shortages or barriers. Using gen AI and analytics, predictive models can be deployed to flag patients or communities at risk of poor outcomes, enable targeted outreach for screenings, tests and treatments. AI can also help generate demographic archetypes that help design tailored interventions for different healthcare needs by different individuals or groups.
ZS’s Health Inequity Treatment Index quantifies inequities in therapy areas such as heart failure, diabetes, HIV, obesity and lung cancer by combining patient-level and socioeconomic data to highlight where certain populations are systematically undertreated. Through ZAIDYN Care Gap Intelligence, ZS helps a large pharma client use AI-driven analytics to identify latent demand, care gaps and SDOH barriers at ZIP-code level, then segment patients and providers in disproportionately affected communities to guide targeted, equity-focused interventions.
(Source: Pharma company builds health equity using ZAIDYN® intelligence platform).
Q. How can organisations move from data insights to action when addressing social determinants of health, especially in complex and resource-constrained environments?
A. By bringing Social Determinants of Health (SDoH) within operational priorities; translating data into concrete workflows, partnerships and incentives that can work in resource‑constrained realities. Start by linking SDOH insights to clear business and health objectives upfront, choose partners with complementary assets (data, local trust, delivery capability) and ensure there is enough data infrastructure to track referrals and outcomes together.
ZS’s SDOH and health-equity work shows that moving to action requires: granular segmentation (who is affected and where), practical intervention menus (what can realistically be done locally), and an operating model for ongoing monitoring.
Q. What indicators or outcomes should organisations track to ensure health equity initiatives are delivering real impact and not just ESG disclosures?
A. We refer to ZS Health Inequity Treatment Index (HITI) which provides a structured way to quantify inequities across therapy areas, geographies and patient segments, helping leaders set clear equity goals and monitor progress in care delivery over time rather than just reporting intentions.
Tracking whether underserved populations whether defined by region, income level or other factors show improved care engagement and outcomes allows organisations to see if equity programs are working where disparities are greatest. Indicators can include diagnosis rates, treatment uptake, and changes in care outcomes across demographic groups. This aligns with the broader health equity framing that underserved groups often face systematic barriers that must be identified and addressed.
Understanding whether efforts with partners and clients are translating into broader reach and better outcomes is key. For example, increased numbers of patients touched through partnerships, expanded access points, or broader stakeholder engagement are measurable outcomes that indicate movement beyond reporting. ZS’s business responsibility reporting shows how such partnership impact can be tracked quantitatively.
Indicators such as changes in gaps along the patient journey for example, fewer missed diagnoses or improved follow-up care rates help determine whether organisations are closing inequities in a tangible way rather than simply initiating programs.
Q. From an India lens, which health equity challenges require urgent attention today, and where do you see the greatest opportunity for technology-led, scalable solutions?
A. India’s most urgent health equity challenges sit at the intersection of geography, income, gender and digital access implying the biggest opportunity is to use India’s fast-maturing digital public infrastructure to deliver low-cost, tech-enabled primary and chronic care at scale. Some urgent health equity challenges that India faces today-
• Large parts of rural India and urban slums still face shortages of facilities, specialists and diagnostics which causes delay in right diagnosis, providing right treatment, care and therefore results in low outcomes compared with better-served urban populations.
• Despite Ayushman Bharat and state schemes, high out-of-pocket spends continue to push large population below the affordable mark particularly for hospitalisation and NCD care
• Fragmented, uneven quality care quality and continuity varies widely geographically and demographically; data on outcomes and equity are still inconsistent, making it hard to target interventions through technology advancements.
• Emerging digital divide: the rapid growth in telehealth and apps risks excluding those with low digital literacy, poor connectivity or non-English language
ZS is already positioning India as a global hub for AI‑ and analytics‑led healthcare innovation, building solutions (via platforms like ZAIDYN and bespoke GCC models) that can run on top of digital health infrastructure and be adapted across markets.
Q. What role can private sector consulting and analytics firms play in strengthening public health systems without overstepping into areas traditionally led by governments or civil society?
A. Private consulting and analytics firms can add real value to public health systems when they focus on technical capacity, data, and collaboration. Firms can help ministries, public agencies and NGOs translate research into practical strategies, delivery models and costed implementation plans, especially for complex areas like primary care, SDOH and digital health. They can design and run analytics platforms for surveillance, population health management and SDOH programs, helping public actors identify high-risk populations, target scarce resources and evaluate what works. Cross-sector partnerships between HCPs, pharmaceuticals, payers and community to bring data, trust and infrastructure together.
ZS explicitly frames its role as bringing human-centered design, analytics and cross-ecosystem partnerships to help address health inequities, including through work with nonprofits and community organisations.
Q. As AI becomes more embedded in healthcare decision-making, what governance principles are essential to build trust, accountability and transparency?
A. In addition to technical performance, trustworthy healthcare AI needs clear guidelines on how systems are built, deployed and managed anchored in human rights, clinical safety, data privacy and outcome accountability. That means clinicians and decision-makers need clear, practical visibility into how an AI model arrives at its recommendations: the data it uses, the blind spots, and performance. Pairing that with human oversight, documentation, compliances to govern implementation regulation enables leaders to validate and ultimately trust AI-supported decisions.
Strong data governance, explicit fairness testing and clear ownership for model performance are non-negotiable if we want AI to advance health equity and align with both clinical priorities and broader societal expectations.
Q. As a global ESG leader, what mindset shift do you believe business leaders must adopt over the next decade to meaningfully embed health equity into long-term sustainability strategies?
A. Business leaders need to shift from viewing health equity as a philanthropic add-on to recognising it as a core performance and resilience driver that belongs at the heart of long-term strategy. At ZS, we have made “advance health equity” one of our three ESG focus areas, directly linked to our purpose of improving health outcomes for all, which means we already approach equity as a core business responsibility.
The second mindset shift is from project thinking to systems and accountability thinking. Over the next decade, leaders will need to apply a health-equity lens across governance, incentives, analytics and ecosystem partnerships, with clear ownership and measurable outcomes.
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