In this guest post, Stacey explores how artificial intelligence (AI) is helping life sciences organizations move beyond fragmented support models to deliver more integrated and personalized patient engagement. She outlines three distinct approaches to structuring patient support programs and discusses how AI-driven tools—such as AllazoHealth—can help tailor interventions across the entire treatment journey.
To learn more, see the AssistRx case study: Sophisticated Patient Engagement Programs that Improve Experiences and Outcomes.
Read on for Stacey’s insights.
The AI Advantage: Evolving Patient Engagement Strategies to Improve Outcomes
By Stacey Little, Chief Growth Officer, AssistRx
Too often, the specialty pharmaceutical industry draws a false line between therapy initiation and adherence—treating them as separate phases managed by separate teams.
From the patient’s perspective, that distinction doesn’t exist. Patients experience the treatment journey as one continuous process, so when support is fragmented across access, marketing and patient services, organizations risk creating suboptimal patient experiences and outcomes.
With the advancement of artificial intelligence (AI), life sciences organizations can close these gaps and rethink how the industry approaches patient adherence—advancing beyond adherence to comprehensive patient engagement. As healthcare becomes increasingly personalized, adherence programs must evolve from standard, one-size-fits-all or stratification models to sophisticated solutions that drive decisions and support for each individual patient.
Advancing Patient Engagement and Adherence
Today, life sciences organizations can choose from a spectrum of approaches, ranging from standard adherence to comprehensive patient engagement strategies that deliver meaningful patient support:
1. Standard Approach (One-Size-Fits-All).
2. Stratified Approach (One-to-Many).
3. Personalized Approach (One-to-One).
Key Considerations for Life Sciences Organizations
Once you have determined your program's patient engagement approach, choosing the right vendor to support your strategy is critical. Before launching a patient engagement program, ask your vendor these questions:
The Future of Personalized Patient Engagement Programs
As data and technology advances, patient support programs must transition from standard interventions to iterative systems that deliver true patient engagement. Predictive insights, real-time adaptation and empathetic human support will form the backbone of next-generation programs.
By leveraging the right mix of tech and talent, organizations will ultimately improve patient engagement and deliver on the promise of better, more patient-centered care throughout the therapy journey.
Learn how AssistRx delivers improved patient engagement outcomes in our case study, Sophisticated Patient Engagement Programs that Improve Experiences and Outcome.
Sponsored guest posts are bylined articles that are screened by Drug Channels to ensure a topical relevance to our exclusive audience. The content of Sponsored Posts does not necessarily reflect the views of HMP Omnimedia, LLC, Drug Channels Institute, its parent company, or any of its employees. To find out how you can publish a guest post on Drug Channels, please contact Paula Fein (paula@DrugChannels.net).
From the patient’s perspective, that distinction doesn’t exist. Patients experience the treatment journey as one continuous process, so when support is fragmented across access, marketing and patient services, organizations risk creating suboptimal patient experiences and outcomes.
With the advancement of artificial intelligence (AI), life sciences organizations can close these gaps and rethink how the industry approaches patient adherence—advancing beyond adherence to comprehensive patient engagement. As healthcare becomes increasingly personalized, adherence programs must evolve from standard, one-size-fits-all or stratification models to sophisticated solutions that drive decisions and support for each individual patient.
Advancing Patient Engagement and Adherence
Today, life sciences organizations can choose from a spectrum of approaches, ranging from standard adherence to comprehensive patient engagement strategies that deliver meaningful patient support:
1. Standard Approach (One-Size-Fits-All).
Traditional adherence programs rely heavily on pharmacy data, such as medication possession ratios and refill patterns, and patient self-reported behavior. Outreach follows a standard, “cookie cutter” communication schedule, delivering the same content through the same channel regardless of patient profile or preference. While offering some insight into patient activity, this approach often assumes that consistent refill behavior equates to adherence and fails to uncover or adjust to underlying factors driving nonadherence.
2. Stratified Approach (One-to-Many).
More advanced than the standard model, stratified programs segment patients into groups based on characteristics, such as medication compliance history, social determinants of health, quality of life scoring and more. While this approach facilitates more targeted messaging and support strategies through segmentation, one-to-many programs often miss critical distinctions that can affect experiences and outcomes, such as consumer behavior, mobile/web usage habits, and rich social determinants of health data. Without these data points, the stratified approach cannot deliver on meaningful patient engagement.
3. Personalized Approach (One-to-One).
The most sophisticated adherence programs use AI and advanced analytics to extend patient engagement throughout the treatment journey using individualized support touchpoints. Rather than placing patients into static groups, these programs develop dynamic profiles using hundreds of data points.
AllazoHealth, an AssistRx solution, is an AI-driven, omnichannel patient engagement solution that securely and compliantly uses an unmatched dataset of program data sources and a database of more than 29 million patient records to determine the optimal content, channels, timing and cadence for each and every patient.
From program design to ongoing execution, AI enables real-time, continuous learning about patients’ evolving communication preferences, adherence patterns, side effect management, lifestyle triggers and more to anticipate what each patient needs to initiate—and thrive—on therapy. As the program evolves, ongoing aggregation of data points from the program allow for further sophistication of patient engagement strategies. This level of personalization goes far beyond the standard therapy initiation and adherence programs and is especially critical in complex or specialty therapies where drop-off risks are high.
AI enables patient engagement programs to:
AllazoHealth, an AssistRx solution, is an AI-driven, omnichannel patient engagement solution that securely and compliantly uses an unmatched dataset of program data sources and a database of more than 29 million patient records to determine the optimal content, channels, timing and cadence for each and every patient.
From program design to ongoing execution, AI enables real-time, continuous learning about patients’ evolving communication preferences, adherence patterns, side effect management, lifestyle triggers and more to anticipate what each patient needs to initiate—and thrive—on therapy. As the program evolves, ongoing aggregation of data points from the program allow for further sophistication of patient engagement strategies. This level of personalization goes far beyond the standard therapy initiation and adherence programs and is especially critical in complex or specialty therapies where drop-off risks are high.
AI enables patient engagement programs to:
- Identify the most at-risk patients based on demographics, therapy complexity, prescription history and behavioral patterns.
- Tailor outreach by determining the best message, delivery channel, timing and frequency.
- Optimize operational efficiency and create more meaningful, effective patient interactions throughout the therapy journey.
Key Considerations for Life Sciences Organizations
Once you have determined your program's patient engagement approach, choosing the right vendor to support your strategy is critical. Before launching a patient engagement program, ask your vendor these questions:
- Can they deliver what they claim? Ask for evidence of performance and details of core capabilities. This can include case studies, references or validated data.
- What will they need from you? Clarify what inputs they require. This may include clinical considerations, titration schedules, patient journey insights and therapy-specific content.
- How are communication guardrails established? Ensure they can define when and how patients will be contacted, especially around sensitive touchpoints like side effects, forced titration, time-critical clinical events or healthcare provider interactions.
- Is their model scalable and adaptable? Your patient engagement strategy must evolve as your brand or population grows. Ask whether their solution can scale in sophistication and personalize support in real time.
The Future of Personalized Patient Engagement Programs
As data and technology advances, patient support programs must transition from standard interventions to iterative systems that deliver true patient engagement. Predictive insights, real-time adaptation and empathetic human support will form the backbone of next-generation programs.
By leveraging the right mix of tech and talent, organizations will ultimately improve patient engagement and deliver on the promise of better, more patient-centered care throughout the therapy journey.
Learn how AssistRx delivers improved patient engagement outcomes in our case study, Sophisticated Patient Engagement Programs that Improve Experiences and Outcome.
Sponsored guest posts are bylined articles that are screened by Drug Channels to ensure a topical relevance to our exclusive audience. The content of Sponsored Posts does not necessarily reflect the views of HMP Omnimedia, LLC, Drug Channels Institute, its parent company, or any of its employees. To find out how you can publish a guest post on Drug Channels, please contact Paula Fein (paula@DrugChannels.net).
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