ZS’s Sumit Verma and Bevan Levy joined Tanya Shepley and Vicky Zhou for this Q&A.

Patients are increasingly navigating healthcare with a consumer mindset as they seek convenience, transparency and frictionless experiences that resemble modern retail. At the same time, AI and large language models (LLMs) are shaping how patients find information and form expectations, even before they enter a clinician’s office.

According to the ZS Future of Health Report, 42% of U.S. patients say they “always” or “often” research their symptoms online before deciding to see a doctor. That early influence carries forward: 52% of U.S. survey respondents report having asked a healthcare provider for a specific medication or type of medication, highlighting how patients are bringing more informed—and often more directive—expectations into their care decisions.

These developments are redefining what patients expect from the healthcare experience and exposing gaps in how the system delivers care. But what does it all mean for patient services?

As we detail in the fifth annual Patient Support and Services Trends Report, patient services must continue to evolve from manual, reactive support models toward scalable, intelligence‑led capabilities that guide patients from one step to the next. This includes focusing on proactive journey orchestration, engaging AI-enabled patients and experimenting with new direct‑to‑patient (DTP) approaches.

We recently spoke with the report’s authors—ZS’s Tanya Shepley, Vicky Zhou, Sumit Verma and Bevan Levy—to discuss consumerization, orchestration, AI and more. If you would like to see more data from the Patient Support and Services Trends Report, connect with us.

ZS: Our research shows that consumerization in healthcare is often misunderstood as being primarily about channels, convenience or choice. What’s the most important misconception life sciences leaders still have about the consumerization of healthcare, and how should they rethink patient support to address the emotional, financial and treatment-related burdens that affect patient decision-making?

Tanya Shepley: One of the biggest misconceptions is that consumerization is about giving patients more choice or convenience. In reality, it’s about continuity and confidence. To take an example from retail, the online retailer Zappos differentiated itself by instituting a 365‑day return policy. This policy was designed to reduce customers’ cognitive burden and anxiety while making them feel confident and supported.

In healthcare, that anxiety is amplified. Patients are navigating diagnosis, cost, access and treatment decisions all at once. Life sciences organizations should understand where confidence breaks down along the journey and design patient support that restores it. When you reduce that emotional burden, you reduce abandonment—and that’s what ultimately drives better outcomes.

Bevan Levy: That’s a good callout about anxiety and cognitive burden. Our research reveals 37% of patients consider emotional burdens to be challenging, compared to 31% who said financial burdens are challenging. This means consumerization in healthcare is also about designing experiences that are empathetic, transparent and coordinated.

Vicky Zhou: Consumerization is often treated as a one‑size‑fits‑all solution, but it’s really a mindset. It requires continuous feedback loops that adapt to different patient contexts. The goal is to understand how patients engage and then refine support so we can meet their needs and drive better outcomes in real time.

ZS: We’ve heard you describe a shift from reactive, transactional support to proactive journey orchestration. In practical terms, how can life sciences organizations make this shift a reality? Which capabilities need to change first to move from point solutions to coordinated, end-to-end patient journeys?

TS: Many pharma and healthcare organizations have the right ingredients, but they’re still operating in silos. Their point solutions aren’t designed to work together. Improving on this model requires an architectural commitment to connect data, technology and roles so that intelligence-led support services, rather than individuals, orchestrate what happens next. Of course, you also need meaningful change management.

Sumit Verma: Data connectivity is foundational as well. Patient support data often isn’t linked to outcomes or specialty pharmacy data. But when those data sources are connected, organizations can generate better intelligence and deploy the right interventions at the right time across the journey.

VZ: That’s a good point about data, Sumit. Because you need a platform that brings together data from hubs, specialty pharmacies, vendors and more. Without that, you only see part of the picture. Proactive journey orchestration needs connected data.

BL: And we need to take better advantage of existing data by considering the volume and variety of data that we collect from calls, chats, emails and other patient engagement channels—because we can mine potentially hundreds of data points from each interaction. When organizations apply analytics and language processing to understand the sentiment and intent behind these interactions, they can learn how to intervene earlier, before friction turns into drop‑off.

ZS: You write that AI and platform modernization are moving patient services from manual execution to scalable decision support, and also toward intelligent orchestration. Where do you see AI creating the most value first: earlier risk detection, access, task automation, coordinated engagement at scale or in another area? Why?

SV: AI’s biggest value goes beyond predicting drop-off, because it can identify friction early and explain why it exists. This includes surfacing payer issues, pharmacy complexity or emotional barriers by scanning multiple data sources. These insights allow organizations to design targeted interventions that meaningfully improve the patient experience.

VZ: I think of AI in three steps: summarizing, generating insights and taking action. The real power comes when you connect those steps and start taking actions based on these insights. Efficiency improvements may lead to the immediate wins, but long-term value comes from AI taking on actions and thus enabling people to focus on the moments and activities that require the human touch.

TS: Those are good points from Sumit and Vicky. We’re also seeing strong proof points when AI is used for intelligence and prioritization, not just speed. The Patient Support and Services Trends Report details how one organization used AI to surface the right patients during the right intervention window—and reduced never-starts by 26%.

BV: There are also opportunities for front-end or patient-facing AI capabilities. Patients increasingly expect AI-enabled support, and some are even noting a preference for AI assistance for simple tasks like status checks or off-hours questions. And while not every patient is ready to use AI to navigate the healthcare system, even these types of lower‑risk use cases can reduce friction and improve the patient experience.

ZS: Thanks everyone. The report frames DTP as evolving from awareness into an integrated operating model that addresses friction across pre-prescription and post-prescription journeys. What signals tell you a DTP approach is strategically justified for a therapy area, and conversely, when is a DTP approach the wrong choice?

VZ: In our work with clients, we see DTP works best in therapy areas where patients are able to influence treatment decisions, where journey orchestration is complex or where there’s a cash‑pay dynamic. And the approach will differ between therapies. For example, for some therapies, it’s possible DTP may focus only on acquisition or only on fulfillment, depending on where the friction exists. But DTP is almost always worth considering, with 67% of patients saying that DTP platforms make it easier and faster to start medication, and 69% of patients saying DTP offers convenience.

SV: Regarding patients influencing decisions, we’re seeing opportunities in areas where patients actively research options, such as depression. In these areas, DTP can support awareness and early fulfillment. The model may differ by therapy, but there are plenty of opportunities for DTP to play a meaningful role.

TS: When exploring a DTP approach, one key consideration is channel conflict readiness. At a recent industry roundtable, we discussed how DTP can create friction with specialty pharmacies or referral pathways if governance isn’t clear. So the question shouldn’t be if DTP is the right approach, but whether it’s designed to complement existing workflows rather than fragment them further.

One example that I think the industry overlooks is Lilly Direct’s inclusion of Alzheimer’s as part of the DTP platform. It involves a core specialty product with a strategic focus on reducing pathway frictions to help connect people to care. Another example is UCB and myasthenia gravis, with the DTP experience centered on a journey orchestration model.

ZS: Thank you. Let’s move on to metrics. The report says patient services support measurement is advancing from activity reporting to defensible impact attribution, while also informing investment decisions. If you could standardize one North Star metric for patient services leaders to track across activation, access and adherence, what would it be and why?

SV: I’d focus on incremental patient impact, because it helps you understand which services or combinations actually change outcomes. Fulfillment and adherence are table stakes. What matters is isolating which interventions drive more value so organizations can invest where it truly makes a difference.

TS: Good point, Sumit. I think time to sustained therapy is an important complement to incremental patient impact. Getting patients started is important, but success depends on keeping them on treatment through multiple fills—in fact, our 2026 ZS Future of Health Report found 28% of U.S. patients report stopping a treatment prematurely. Measuring which services support long‑term persistence is critical.

SV: That’s a great point and it brings to mind some work we did with Novo Nordisk. We measured how different services affected persistence and found that programs like their We Go Together, which provides coaching, increased persistence by about 21 days. That kind of measurement helps isolate which services drive incremental impact and allows organizations to prioritize patient-facing solutions that keep patients on therapy longer.

VZ: These types of metrics also justify continued investment in critical platforms and infrastructure. Being able to tell a story with numbers allows organizations to optimize their patient services mix by doubling down on what creates the most patient impact.

ZS: One final question. The report argues that enterprise service platforms are shifting roles from siloed execution to orchestrated deployment, with a centralized system defining “what action is needed, when and by whom.” What does this mean practically for the nurse educators, patient navigators and case managers who have long been the human face of patient support? How does this evolution redefine their roles?

BV: We’re seeing roles shift from transactional execution toward more specialized, high‑impact engagement. Proactive journey orchestration enables that by identifying key friction points and guiding interventions at the right moments. With integrated data and AI, there’s now continuity across interactions. It’s encouraging that a case manager today, for example, can more easily pick up a patient interaction and know what’s already happened and what’s needed next.

Proactive journey orchestration also supports a more collaborative, coaching‑oriented model. It doesn’t just route tasks, but gives guidance on how to engage, what resources to offer, and even how to tailor your tone based on patient needs. The result is more cohesive, personalized support that moves away from manual, siloed execution and toward targeted, coordinated care.

VZ: Well said, Bevan. We’re also seeing that integrated data and AI is removing administrative burden so that humans can focus on complex cases and human connection. Of course, these are the areas where people add the most value—nuanced problem‑solving and coordination across stakeholders.

TS: And that brings up something important: Organizations must be careful not to over‑automate or under‑communicate this shift. The goal should be to augment or enhance the impact of support service roles. Success depends on training, change management and performance frameworks that measure quality of engagement, not just activity.

SV: Proactive journey orchestration also creates shared memory across roles. When information flows between field reimbursement managers, case managers and others, the conversations become more effective. We’re also seeing clearer segmentation of no‑touch, medium‑touch and high‑touch activities, ensuring humans intervene where they matter most.

Want to learn more about our patient services research and how it can help you deliver value and improve outcomes for all? Let’s talk.