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Can Data and AI Deliver Whole-Person Health?


Executives in the life sciences and medical device industries see promise in artificial intelligence (AI) and medical technologies, but must also navigate the changing healthcare ecosystem, varied stakeholder needs, and the impact of AI on market access and commercialization strategies.

Jon Koch, CEO, Avalere Health.

Jon Koch, CEO, Avalere Health.

Recently, more than 4,000 people from across the globe gathered in Atlanta to address the latest methodologies, data analytics, and evidence-based approaches that drive transformative change. The conference was held by ISPOR—The Professional Society for Health Economics and Outcomes Research (HEOR). One organization in attendance was Avalere Health, a global commercialization firm that partners with stakeholders across the healthcare ecosystem to provide a variety of services, including market access and HEOR. The following is Avalere Health’s global CEO’s perspective on the event and discusses what is needed to turn the concept of whole-person health into reality.

We are living during a time in which the promise of science and medicine has never been greater. Advances in artificial intelligence (AI) and medical technologies are fueling innovations in new therapies, improving how we approach health technology assessments (HTAs) and providing diverse communities greater access to needed medicines.

As CEO of a global healthcare commercialization firm, I hear executives in the life sciences and medical device industries express optimism around innovative treatments and better outcomes. However, they are also navigating the changing healthcare ecosystem, varied stakeholder needs, and the impact of AI on market access and commercialization strategies.

Conferences such as ISPOR 2024 offer insights into these developments. This year, there were three themes that emerged in addressing the continuing challenges life sciences and medical device companies face:

  • The shift from patient-centric health to whole-person health.
  • The need to collate, collect, integrate longitudinal data for better outcomes.
  • The AI headwinds and tailwinds that are driving change.

The shift from patient to whole person

For some years now, the biopharma industry and wider healthcare ecosystem have been executing new methodologies to place patients at the center of everything we do—from research and development to market access and commercialization.

Whole-person health takes the patient voice several steps further. It aims to balance the body, mind, and spirit, focusing on every attribute of a patient's lived experience. It's a holistic view of how patients would characterize their health and how healthcare professionals and communities see it. Executed successfully, whole-person health:

  • Addresses inequities, prevents disease, and restores health.
  • Helps enable, empower, and equip patients to take charge of their health and live life to the fullest.
  • Ensures patient needs are fully understood and therapies are optimized around their wants and priorities.

Part of building this understanding of the whole person is involving patients in every stage of the product lifecycle, including data generation and clinical trial design, to ensure their challenges and needs are fully understood and medicines are optimized around their wants and priorities.

Shifting our thinking from patient to whole person requires a more complex approach and the need for accurate, longitudinal data. It is important to think early and proactively about the path to identifying the best way to generate, procure, and analyze data in an efficient manner.

To capture a person’s whole health throughout a lifetime means collating, collecting, and analyzing information from physicals, immunizations, claims, behavioral, mental health, spiritual, cultural, and even socioeconomic status. These data points are incorporated along with data we are now collecting, such as age, gender, diseases, and comorbidities.

Right now, the ability to link, share, and collaborate using data across multiple sources, partners, and service providers is limited and costly—key barriers to achieving whole-person health. Successfully creating seamless data sharing requires organizations to adopt cross-functional collaboration and leverage technologies, including AI.

Establishing a strategy to access whole-person data

The numerous discussions on whole-person health at ISPOR 2024 were encouraging but putting it into practice poses significant challenges to life sciences and device companies. The market for acquiring and accessing data has become increasingly crowded, characterized by high fragmentation and multiple vendors offering diverse types of information.

This has led companies to procure data from multiple sources, often resulting in the acquisition of redundant and overlapping information. Consequently, manufacturers are spending substantial sums annually on redundant data.

In a recent project, for example, Avalere Health identified that a client’s data purchase resulted in having 100% medical claim data overlaps between two vendors. To reduce redundancy risks, choose an external partner to help facilitate collaboration across an organization. This approach can also help companies free up resources that can be put to better use.

Another challenge is to understand all the data assets the organization has access to and how those different datasets can be linked together to illustrate the patient journey from end to end. A holistic view of the patient journey requires connections across a variety of datasets that might be owned and managed by different parts of the organization—claims data for all payer markets, formulary and benefit-design data, clinical data, and data on social determinants of health, as well as patient programs, digital interactions, devices, market data, and more.

Understanding all the data assets your organization has access to is a significant undertaking, and that’s only the first step. As an organization starts to piece together different aspects of the patient journey, you’re likely to identify areas in which there are gaps. Evaluate the costs and benefits of purchasing additional datasets, which will differ for each organization.

In some therapeutic areas or for products still in early development, a smaller portion of the patient population may provide sufficient visibility into the patient experience to inform key decisions. But a company’s need for more complete datasets might be very different for rare diseases, where each added patient in the dataset can translate into very high-value insights.

The next step is to ensure those different datasets can be linked together to illustrate the patient journey from beginning to end through a sound tokenization strategy. Tokenization allows for interoperability across multiple datasets, especially if multiple vendors are involved.

It helps to have a centralized partner to identify linkages between various patient records and ensure personal health information is properly encrypted. Strong internal communication and coordination, with a role from procurement, can provide structure and guardrails to reduce redundancies and ensure the ethical and equitable use of data—critical components toward achieving whole-person health. 

How AI can impede headwinds and boost tailwinds

We cannot talk about data without discussing the application of AI in tackling many of the challenges that life sciences and medical device companies face. AI technologies are opening new avenues for data collection, analyses, and connections. When AI is used to augment human expertise, we can dig deeper, think bigger, and deliver more powerfully together.

Machine learning is being used to break through bottlenecks and deliver efficiencies in analyzing volumes of data. Connectivity across data sources is enabling companies to monitor and track patients more easily.

In health economics and outcomes research, AI can organize and structure large amounts of data to identify patterns, yielding insights that can help fine-tune healthcare decisions. AI can also augment real-world evidence, assisting researchers and payers to better understand the safety and effectiveness of specific treatments.

It’s clear that AI has the potential to help improve the future of healthcare from how we leverage, develop, and execute data. However, we also need to consciously prevent the unconscious integration of bias, which can hinder progress and lead to disparity.

For example, biased data can bolster current social, cultural, and economic prejudices that exist. Additional biases also can be embedded into the analytics if the data collected are not validated in a real-world setting.

Until we see more organizations become adept at recognizing and mitigating biases—from drug discovery through research and development and at the commercialization process—we are still quite a distance away from applying AI to whole-person health and importantly, removing bias embedded into the systems that can hinder our progress.

Is whole-person health attainable?

It is possible to achieve whole-person health, but it would require alignment from various groups, including payers, prescribers, patients, policymakers, and investors. Leading organizations can play a central role in guiding, educating, and inspiring stakeholders. Data experts can deliver insights on how to best integrate various types of information from patients’ lived experience to build longitudinal data.

Service partners can provide clarity, help reduce the noise, and increase profitability to succeed in this dynamic environment. Choosing the right partner can make a significant difference in accelerating the path to whole-person health.

Seek out companies that offer integrated service offerings to simplify the process and deliver efficiencies. Select one with significant expertise in collaborating with various data providers and with expertise in AI and data collation, collection, and analyses. Global companies that market outside the United States are invaluable partners because they can review data from various countries and look for synergies.

Several presenters at ISPOR US 2024 said the movement toward whole-person health is inevitable. It is just a matter of time before accurate longitudinal data is available to collect, link together, and analyze. By building an environment where all stakeholders are strategically aligned toward better care, we improve patient outcomes through research and development, increase access to new therapies, address inequities, and importantly, restore health and wellness.

About the Author

Jon Koch is CEO of Avalere Health, a purposefully built, global commercialization partner for the biopharmaceutical, medical technology, and wellness industries. As CEO, he is responsible for leading more than 1,500 experts across the globe, including cultivating the company’s vision, driving strategic and operational direction, building the company's capabilities and culture, and developing senior client relationships and business growth.

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