How technology will take patient support programs (PSPs) to greater levels of effectiveness and efficiency
Patients have fast become healthcare consumers, with the freedom and responsibility to make decisions about their health journeys, and in turn, how, where, and when they spend their money when it comes to their healthcare choices. Patients want solutions and healthcare options that directly speak to them in more personalized, tailored ways.
With that said, this presents a great opportunity for patient support programs (PSPs) to maximize their personalized outreach strategies and omni-channel communications – especially as the industry is moving towards this as a whole. Through the use of new technological solutions such as artificial intelligence (AI), there is great opportunity for improving medication initiation and adherence rates by connecting with patients on a one-to-one level.
In this blog, we’ll dive into three major predictions for PSPs in the near term, and how you can elevate patient engagement and program performance and efficiency as a result.
1. Personalized Interventions Become a Necessity
Every year, the pharma industry spends nearly $31B to get to the moment of prescription, yet 20-30 percent of patients abandon their script and never start the prescribed therapy. Additionally, the industry spends $5B annually developing patient resources, such as education and support programs, but only three percent of patients ever access them, and more than half of patients drop off therapy within 6 months.
It’s clear that personalization is a key component of any effective PSP, traditional methods like persona segments can only go so far as they are still inherently 1-many mass communications. Patients have fast become active healthcare consumers, at the same time the volume of health information has grown exponentially, so in order to deliver the personalized support they deserve and cut through the noise, AI is a necessity.
AI technologies can take countless demographic variables, challenges, and pieces of data, and reveal exactly how to best deliver optimal patient interventions that drive engagement, next-best-action, and outcomes.
On paper, two patients who are between the ages of 27-35, live in a home with two other adults, and work a full-time job may appear similar, but there are a myriad of personal variables that can affect their behaviors and potential for medication adherence; an SMS text nudge may work well for one individual, whereas a phone call and email combination may work better for another.
Because these small nuances can be predicted for each individual patient with AI, unlike with traditional persona segments, this allows for a greater impact of timely interventions, more targeted strategies, and more robust personalized PSPs.
2. Continuous Learning in Real-Time
There are millions of datapoints when it comes to analyzing patient intent: household size, location, education, age, gender, income, consumer purchasing behavior, and so much more. All of these datapoints can be tricky to keep track of on an individual basis, but that’s where AI can be leveraged. AI takes all of these datapoints, analyzes them, and then determines the next-best-action suited for engaging with individual patients.
This gives PSPs the power to more accurately predict what personalized message a patient will respond best to – including the content, channels, timing, and cadence.
AI is capable of continuously learning and improving based on ongoing results from interventions, updated patient data, and patient behaviors after outreach – enabling you to quickly and easily optimize performance without costly or time-consuming A/B testing. This is especially important because consumer preferences and life stages change over time. Additionally, you can better identify future program improvement opportunities through analyzing patients not well-supported by current communications.
When you use AI to measure and demonstrate the impact on patient engagement, this paves the way for continually improving and refining your outreach and engagement strategies, delivering overall greater engagement, initiation, adherence, and outcomes.
3. Patient Prioritization Will Improve Performance and Efficiency
Thanks to the predictive capabilities of AI, case managers or PSP team members doing outreach can better allocate resources where they will have the most impact, as well as removing extraneous outreach efforts from patients that don’t benefit from them. This ensures that all resources are being used as effectively as possible, which also boosts efficiency since costly interventions, such as phone calls, are prioritized for only individuals who need them.
Because AI technology can decide what is the most important priority to do today versus tomorrow or the next day, it ensures that any high-priority actions and patients are handled sooner rather than later – and in the way that is going to be most beneficial for all stakeholders involved.
An example of this is if a PSP case manager is on vacation for an extended period of time, which places their caseload on other team members. AI can weigh the priorities of the caseload and distribute it among the present members in a way that is resourceful and effective, ensuring that the PSP can focus its resources on the right patients at the right time.
Elevate Patient Engagement and Outcomes with AI
The rise of technology has resulted in a great deal of opportunity for patient support programs, and in order to stay ahead of the curve, it’s advantageous to leverage tools such as AI. A truly personalized approach allows pharmaceutical and other healthcare organizations to provide targeted education, support programs, and interventions that improve patient engagement, outcomes, and performance – and your PSP could be next.
Learn how you can use AllazoHealth’s award winning AI to bolster patient engagement and medication adherence, improving patient outcomes and enhancing performance in the process.