Unlocking AI’s Promise in Patient Support Programs

Today’s guest post comes from Chris Apolito, Chief Strategy Officer, and Karina Castagna, Senior Vice President, Commercial Strategy at Mercalis.

Chris and Karina describe four ways that artificial intelligence (AI) can improve patient access, affordability, and adherence.

To learn more, join Mercalis for a complimentary webinar on March 13, 2025: Modernizing Patient Support: Harnessing Advanced Automation, Artificial Intelligence and Machine Learning to Improve Efficiency and Performance of PSPs.

Read on for Chris and Karina’s insights.

Unlocking AI’s Promise in Patient Support Programs
By Chris Apolito, Chief Strategy Officer and Karina Castagna, Senior Vice President, Commercial Strategy, Mercalis

To hear market analysts and early adopters tell it, artificial intelligence (AI) has already started to revolutionize healthcare. It has begun to play a more prominent role in drug discovery by predicting molecular interactions and subsequent clinical drug profiles. It has also found utility in the realms of diagnostics, personalized medicine, and patient stratification.

AI has not, however, fully been deployed to address existing needs in biopharma patient support programs, which help patients navigate a range of access and affordability challenges. That is why Mercalis has set about exploring potential uses of AI to drive efficiencies and help hub agents focus on more complex, impactful support services.

Four key areas for AI implementation have been examined: AI-enabled enrollment to complement patient self-service; transparency and real-time action around payer restrictions; the enablement of an AI-driven technology for administrative efficiencies within hub operations (i.e., next best action); and predictive analytics.

Here is how Mercalis is innovating to realize the inherent promise of customer-centricity within patient support programs.

EASING ENROLLMENT

Connecting patients to existing support systems has ranked among the biopharma sector’s most stubbornly persistent problems. That is why the use of AI in the enrollment process for patient support programs could prove among its most subtly revolutionary upgrades.

AI can be deployed to automate patient enrollment, reducing or even eliminating the paperwork and manual data entry that has long been a source of frustration for patients and their healthcare providers. Those AI-powered digital self-enrollment channels can ultimately lead to less outreach for missing information and higher patient enrollment rates.

Additionally, complementary technologies like optical character recognition (OCR) can be used both to reduce duplicative data entry and, when paired with AI, can facilitate real-time verification and eligibility for programs. These and other AI-fueled solutions push the world of patient support closer to its ideals of tailored affordability offerings and customized financial programs that consider individual patient needs.

NAVIGATING PAYER RESTRICTIONS AND PRIOR AUTHORIZATIONS

AI tools and procedures can similarly be deployed to ease workflows for healthcare providers, especially in the often-frustrating arena of managing payer restrictions and prior authorizations. To diminish such concerns, the life sciences ecosystem needs easy and broad access to the existing wealth of payer data and any/all tools that analyze payer policies, including prior authorization submission tools that can reduce healthcare provider workload and improve approval rates.

Mercalis is deploying AI technology that can help bring needed transparency to a series of reimbursement support activities that have long been opaque. It might also offer new — and much needed — capabilities for more accurately assessing the probability of payer approvals.

IMPROVING ACCESS AND ADMINISTRATIVE EFFICIENCY

There’s immense potential in using AI tools and processes to accelerate speed to therapy for new patients. Much has been made about simplifying the path from prescribing to dispensing, and AI can now be deployed in healthcare provider systems to suggest appropriate medications based on a patient’s medical history and payer coverage. But without connectivity to a robust patient access data source, all such efforts are destined to fall short.

When solutions are creatively architected, the possibilities are limitless. Think AI chatbots and virtual assistants programmed to provide more personalized options for initial screenings and financial assistance, or natural-language-driven prompts that point patients toward a more streamlined experience. Similarly, AI-enabled policy search can drive better understanding of payer coverage, while AI-enabled electronic prior authorization (ePA) tools can aid in predicting coverage approvals. With the help of AI technology, ePA platforms are evolving to allow the pre-population of data from existing patient health platforms and can offer a green/yellow/red light scheme for likelihood of approval.

Some of those gains tend to be around the margins and exist in places — such as back-end processes — invisible to most biopharma stakeholders. At the same time, many smaller, less obtrusive improvements directly facilitate the customer-centricity that healthcare-adjacent organizations have long sought to provide — and foster both an improved overall experience and cost savings.

PREPARING FOR THE AI BOOM

Mercalis has invested in predictive analytics (which can identify high-risk patients or patients likely to be non-compliant) and large language models (especially natural language processing, which analyze huge volumes of medical research and patient records). It has committed to developing AI-infused offerings that help get more patients on therapy and stay on therapy. It has also taken necessary steps to ensure that its use of AI in and around its patient support programs is medically and ethically responsible. This comes in the form of making sure patients are aware of — and consent to — the role AI plays in their care and extending access to AI-related technologies in an equitable manner.

Industry-wide, next steps include fostering better collaboration between patient support hubs and technologists, and more effectively using insights derived from AI to personalize patient experiences and refine support programs to allow agents to focus on more complex and impactful patient engagements. Human oversight in deploying AI solutions will remain pivotal.

The AI era in healthcare is upon us. Mercalis looks forward to embracing everything that comes with it to better support patients in need. To learn more, contact Mercalis or join us for an upcoming webinar on Modernizing Patient Support: Harnessing Advanced Automation, Artificial Intelligence and Machine Learning to Improve Efficiency and Performance of PSPs.

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