Tech-Infused Care: Exploring the Rise of AI/ML in Patient Services

Industry leaders worldwide are harnessing the transformative power of artificial intelligence (AI) and machine learning (ML) to boost efficiency, accelerate processes, and elevate service quality. Leading pharmaceutical manufacturers, sharing these goals, are increasingly turning to their hub providers to incorporate cutting-edge technology into their patient services programs. In response, hubs like CareMetx are integrating AI and ML capabilities into their essential patient services, driving innovation and improving outcomes. 

Enhancing Therapy Outcomes Through Customized Patient Engagement 

One of the most important goals of any patient services program is to support the patient throughout their care journey. The more seamless the patient experience, the more likely they will initiate, adhere to, and persist on therapy.   

Manufacturers and hub providers have found that engaging with people in diverse ways throughout their patient journey significantly enhances their experience with therapy. However, patient engagement programs often adopt a one-size-fits-all approach, treating all patients the same by contacting them at the same frequency and using the same methods. This strategy overlooks the fact that each patient has unique support needs influenced by social determinants of health (SDOH) and other factors that can create barriers to starting and maintaining treatment. That’s why customizing engagement based on individual circumstances and preferences is crucial for optimal patient support. 

With the rise in AI and ML, leading patient services programs are evolving to take a more personalized approach to engaging with patients. These technologies can support hyper-personalization at scale, allowing a hub to deliver the right message to the right patient at the right time, even across large patient populations.  

Here are just three examples of how AI and ML can enhance engagement with patients on specialty medications.  

1. Tailoring financial assistance timing. If financial constraints are likely to keep a patient from affording their medication, it’s much more effective to deliver information about copay and other financial assistance programs early in the journey. But not all patients need that same support upfront. A proactive hub can use AI/ML to identify patients at risk of affordability challenges, automatically adjust their communication cadence, and remove cost as a hurdle to initiating therapy.  

1. Addressing SDOH. It’s well-documented that SDOH can greatly impact a patient’s care journey and health outcomes. Some hubs use AI/ML to assess how these factors impact each patient, identify those at risk of adherence challenges, and tailor the information and resources they receive and the delivery cadence. As the AI/ML gains more knowledge about each patient’s behaviors and risks, the technology can further inform and guide the patient engagement plan.  

1. Personalizing phone call delivery. To give one example, hubs can use technology to drill down into a patient population, segment those who are of working age, and schedule outbound calls to occur during a time of day when they’re not likely working and more likely to engage.   

By integrating AI and ML into their platforms and omnichannel programs, hubs like CareMetx enhance patient engagement, leading to improved drug initiation and adherence rates. What's more, by employing advanced data analytics capabilities, these hubs can track and report on key patient engagement metrics, allowing them to refine and optimize patient services for even better outcomes over time. 

Tech Improves Provider and FRM Engagement, Too  

Recognizing the critical role that healthcare providers (HCPs) and field reimbursement managers (FRMs) play in a drug’s commercial success, manufacturers now expect hubs to leverage technology for enhanced engagement with these stakeholders as well. 

Integrating AI and ML into patient services programs enables HCPs to gain greater visibility into a patient’s experience throughout their journey, allowing them to provide tailored support at each stage. For example, Dr. Brown can use these technologies to see that patient Linda is struggling to adhere to her treatment plan and has missed several doses due to affordability issues. By accessing this information through familiar digital channels, Dr. Brown can intervene promptly, providing Linda with information about copay assistance programs to help remove financial barriers. 

Similarly, AI and ML empower FRMs to pinpoint providers needing additional support and customize their approach. For instance, FRM Scott may identify that Dr. Brown’s practice requires more training on the benefits of a new therapy, enabling them to tailor their outreach and support efforts, thereby boosting HCP adoption and overall program success. 

Transforming Benefits Verification with Advanced Technology  

AI/ML is also changing how hubs verify a patient’s benefits to ensure access to a newly prescribed drug. Given the complexities and challenges around accessing specialty medications, infusing technology into the process can have significant advantages.  

When benefits verification (BV) is done manually, representatives may spend hours contacting the same payers over and over, making phone calls and submitting paperwork. It’s a major drain on productivity and can delay getting patients started on a new therapy.  

AI/ML is revolutionizing BV by automating routine tasks, which allows the hub to handle more volume efficiently, receive a faster response, and focus employees on more complicated work that requires their skills and expertise. As the system gathers more intelligence about each payer and benefits plan, it learns what to expect and can eventually avoid the need to contact the same payer repeatedly, further speeding the process. With faster and more reliable BVs, patients can initiate treatment sooner.      

As a leading Digital Hub known for designing and delivering effective patient services programs, CareMetx continues to incorporate AI/ML in ways that have measurable impact.  

For example, during the 2024 reverification season, AI/ML enabled CareMetx to automate about 10% more benefit verifications than we have traditionally. As a result, manufacturers that used CareMetx for annual reverification completed the process faster and eliminated treatment delays at the start of a new benefit year.  

As AI/ML evolves, CareMetx is leveraging these technologies for the benefit of the pharmaceutical manufacturers we serve, the patients who need their therapies, and the providers who prescribe them. We’re keeping pace with the rapid evolution of generative AI to ensure we’re making the right investments in technologies that can measurably improve the experience for patients and the bottom line for manufacturers. And we’re creating thoughtful data integration and management strategies that ensure our AI-powered processes obtain, deploy, and track data effectively.  

Contact CareMetx to learn how our tech-enabled patient services can drive better engagement and stronger results for your drug program.