Shaping the Future of Health and Well-Being Through Evidence Generation

10 key takeaways from “Shaping the Future of Health and Well-Being Through Evidence Generation“:

1. Holistic Focus on Well-Being: The 2024 theme expands healthcare beyond treating diseases to encompass physical, mental, and social well-being, emphasizing patient-centered outcomes and quality of life.
2. Rising Importance of Real-World Evidence (RWE): RWE is becoming a cornerstone of healthcare decision-making, offering insights into how treatments perform in real-life settings and addressing the limitations of traditional clinical trials.
3. Patient-Reported Outcomes (PROs) as a Critical Data Source: PROs are essential for capturing the patient’s voice, providing valuable data on how treatments impact day-to-day life, and aligning healthcare decisions with patient preferences.
4. Collaborative Approaches Drive Comprehensive Evidence: Cross-sector collaboration between governments, industry, academia, and patient advocacy groups is vital to generating diverse and actionable evidence that addresses complex healthcare challenges.
5. Artificial Intelligence and Machine Learning Revolutionize Evidence Generation: AI and ML are key tools for analyzing large datasets, predicting health outcomes, and personalizing treatments, leading to more precise and real-time evidence generation.
6. Value-Based Healthcare Links Clinical and Economic Value: Value-based care models require evidence that demonstrates both clinical efficacy and economic value, focusing on patient outcomes that matter most and promoting long-term well-being.
7. Equity and Inclusion in Evidence Generation: Ensuring that diverse populations are included in evidence generation is critical for addressing health disparities and promoting equitable healthcare outcomes.
8. Addressing Global Health Disparities: The evidence generated at ISPOR Europe 2024 has implications for global health policies, helping to mitigate health disparities and ensure equitable access to healthcare worldwide.
9. Ethical Challenges in Data Privacy and Use: Robust data governance frameworks are necessary to protect patient privacy and ensure ethical use of health data in evidence generation, especially as data collection from wearables and social media increases.
10. Sustainability Through Evidence-Based Decisions: Evidence generation focused on cost-effectiveness and long-term outcomes supports the creation of sustainable healthcare systems that can continue to deliver high-quality care and improve well-being over time.

Generating Evidence Toward Health and Well-Being

The ISPOR Europe 2024 meeting is one of the most anticipated events in the global health economics and outcomes research (HEOR) landscape, attracting a diverse range of stakeholders from across the healthcare spectrum, including researchers, policymakers, healthcare providers, and industry leaders. As a platform for cutting-edge discussions on healthcare economics, policy shaping, and outcomes research, ISPOR Europe continues to play a pivotal role in setting the agenda for evidence-based decision-making in healthcare systems worldwide.

This year’s theme, “Generating Evidence Toward Health and Well-Being,” captures the core focus of the meeting—evidence generation. The significance of evidence in driving effective healthcare interventions, policies, and economic models cannot be understated, especially in an era where real-world evidence (RWE) is increasingly becoming the cornerstone of healthcare decisions. With healthcare systems under pressure to deliver high-quality care while managing costs, generating robust, relevant, and timely evidence is critical to ensuring that health interventions not only treat diseases but also enhance overall well-being.

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ISPOR Europe’s Impact on the Global HEOR Community

As one of the largest and most respected HEOR conferences globally, ISPOR Europe has continuously contributed to advancing methodologies, promoting collaborations, and setting standards in evidence generation. Each year, it brings together thousands of experts from more than 80 countries to exchange knowledge, share research findings, and engage in thought-provoking discussions that shape the future of healthcare. By focusing on health economics and outcomes research, ISPOR Europe creates a platform where new approaches to measuring value, effectiveness, and patient outcomes are presented and debated, influencing healthcare policies and practices at both national and international levels.

Please look at the Market Access & HEOR Resource category for more articles.

Theme Rationale: Why “Generating Evidence Toward Health and Well-Being” is Critical Now

The 2024 theme is particularly timely, given the global healthcare challenges that have emerged in recent years. With aging populations, rising healthcare costs, and the aftermath of the COVID-19 pandemic, there is a growing need for innovative healthcare solutions that prioritize both health and well-being. The traditional focus on disease treatment and management is expanding to include a more holistic view of patient health, emphasizing mental and social well-being as integral parts of healthcare.

At the core of this shift is the growing reliance on real-world evidence (RWE), which plays a vital role in supporting healthcare decisions that impact patient outcomes. Unlike traditional randomized controlled trials (RCTs), which often lack generalizability, RWE draws on data from everyday clinical settings, providing insights into how interventions perform in real-life scenarios. This makes RWE an invaluable tool for policymakers, payers, and healthcare providers seeking to implement evidence-based strategies that not only improve clinical outcomes but also enhance quality of life.

Moreover, with the increasing demand for patient-centric outcomes, healthcare decision-making is now prioritizing what matters most to patients—how treatments affect their day-to-day lives. The theme “Generating Evidence Toward Health and Well-Being” reflects this critical evolution in healthcare, where the success of treatments is measured not only by clinical efficacy but also by their ability to improve the overall well-being of patients. This patient-centered approach aligns with the broader global push toward value-based healthcare, which seeks to optimize the outcomes that matter most to patients while making the best use of available healthcare resources.

As the healthcare sector continues to evolve, the demand for comprehensive, high-quality evidence will only increase. ISPOR Europe 2024 will serve as a hub for exploring how new tools, methodologies, and frameworks can generate the type of evidence needed to navigate these challenges, driving innovations that contribute to health and well-being on a global scale.

I would like to dive deep into this article regarding the ISPOR Europe 2024`s meeting theme “Generating Evidence Toward Health and Well-Being”.

The Role of Evidence in Health and Well-Being

Evidence generation is at the heart of effective healthcare decision-making. In the context of health and well-being, evidence serves as the foundation upon which policies, treatment protocols, and healthcare delivery systems are built. As the healthcare landscape evolves, so does the understanding of what constitutes valid, actionable evidence. Traditionally, healthcare evidence has been derived from clinical trials, but in recent years, there has been a marked shift towards more comprehensive data sources, including real-world data (RWD), to ensure that the full spectrum of patient needs is addressed.

Defining Evidence: Clinical Trials and Real-World Data

Evidence in healthcare refers to the data and insights gathered from scientific research that informs healthcare decisions. Historically, randomized controlled trials (RCTs) have been the gold standard for generating evidence. RCTs are rigorous and controlled studies that evaluate the safety and efficacy of medical treatments by comparing them to a placebo or standard therapy in a randomized setting. These trials are highly valued for their ability to minimize bias and provide statistically significant outcomes, making them a cornerstone of regulatory approval for new therapies.

However, while RCTs are critical for establishing the clinical efficacy of interventions, they have limitations. Often, they are conducted under ideal conditions that do not reflect the complexities of real-world healthcare settings. Patients enrolled in RCTs tend to be a specific subset of the population, meaning the findings may not always be generalizable to the broader, more diverse patient groups encountered in routine clinical practice.

This is where real-world data (RWD) and real-world evidence (RWE) come into play. RWD refers to data collected outside of controlled clinical trials, including data from electronic health records (EHRs), insurance claims, patient registries, and even patient-reported outcomes (PROs). This type of evidence provides a broader, more inclusive view of how treatments perform in everyday settings, capturing patient experiences that RCTs may overlook.

RWE, derived from the analysis of RWD, is becoming increasingly important in healthcare decision-making. It complements the findings from RCTs by offering insights into long-term outcomes, treatment adherence, and the impact of interventions on different patient demographics. In addition, RWE can play a pivotal role in health technology assessment (HTA) and pricing and reimbursement decisions, providing payers and policymakers with critical data to make informed choices about resource allocation.

Health and Well-Being: Expanding the Scope of Evidence

The traditional view of healthcare has largely focused on physical health—treating diseases and conditions with the goal of prolonging life and reducing morbidity. However, in recent years, the concept of well-being has gained prominence, recognizing that health is more than just the absence of illness. Well-being encompasses mental, emotional, and social health, and evidence generation must now address this broader spectrum.

• Physical Health: At its core, health involves the prevention, diagnosis, and treatment of physical illnesses. Evidence for this aspect of health has typically come from RCTs and clinical trials that measure treatment efficacy in managing conditions such as diabetes, cancer, and cardiovascular diseases. However, even within physical health, there is a growing emphasis on using RWE to understand how patients manage chronic conditions over time in real-world settings.
• Mental Health: The inclusion of mental health in the definition of well-being reflects a more holistic approach to healthcare. Conditions such as depression, anxiety, and stress-related disorders are increasingly recognized as having a significant impact on overall health outcomes. Generating evidence for mental health interventions often requires a combination of clinical trial data and RWE, particularly because mental health outcomes are influenced by environmental and social factors. PROs, where patients report how they feel and function in their daily lives, are particularly valuable in assessing mental health interventions.
• Social Health: Social determinants of health, such as income, education, and social support, are critical components of well-being. Evidence must also address how social factors affect healthcare access, treatment adherence, and long-term outcomes. This is where patient-centered research and community-based studies can provide valuable insights into the social aspects of health. RWE is particularly useful here, as it captures data from diverse populations and settings, revealing disparities in health outcomes based on social factors.

In the context of ISPOR Europe 2024, the meeting’s focus on “Generating Evidence Toward Health and Well-Being” emphasizes the importance of using a variety of evidence types to inform healthcare decisions that improve not just health but also the broader well-being of individuals and communities. As the healthcare landscape evolves, the evidence must be robust, inclusive, and reflective of the many dimensions of well-being that affect patient outcomes.

In summary, the shift from a narrow focus on disease treatment to a broader understanding of health and well-being requires new approaches to evidence generation. Both RCTs and RWE have vital roles to play in ensuring that healthcare systems deliver value across physical, mental, and social health dimensions. By leveraging comprehensive evidence, healthcare providers, policymakers, and payers can make informed decisions that support the well-being of populations worldwide.

Types of Evidence Generation

The generation of robust evidence is essential for guiding healthcare decisions and policies. While randomized controlled trials (RCTs) have long been regarded as the gold standard for clinical evidence, modern healthcare systems increasingly rely on other forms of data, such as real-world evidence (RWE) and patient-reported outcomes (PROs), to address the evolving needs of patients and healthcare systems. These different types of evidence generation provide complementary insights that, together, offer a more comprehensive understanding of health outcomes and well-being.

Randomized Controlled Trials (RCTs)

RCTs have been the cornerstone of clinical research for decades, providing the highest level of clinical evidence through rigorous testing. In an RCT, participants are randomly assigned to either a treatment group or a control group (often receiving a placebo), ensuring that any differences in outcomes between the groups can be attributed to the intervention being studied. This level of control minimizes bias and ensures that the results are statistically significant, allowing healthcare providers to confidently adopt new treatments and interventions.

The strength of RCTs lies in their ability to establish causality—that is, whether a particular treatment directly causes the observed outcome. This makes RCTs particularly important for regulatory approval of new therapies, as they provide clear evidence of safety and efficacy. For example, many groundbreaking treatments for cancer, diabetes, and heart disease have been developed and approved based on RCT findings.

However, despite their advantages, RCTs have limitations when it comes to real-world applicability. Because RCTs are conducted under highly controlled conditions, the participants selected are often not fully representative of the general population. Trials may exclude older adults, individuals with comorbidities, or those with specific lifestyle factors, making it difficult to generalize the findings to more diverse patient populations.

Additionally, RCTs are expensive and time-consuming to conduct, often requiring years before meaningful results are obtained. As a result, there is a growing recognition that RCTs, while important, should be complemented with real-world evidence to provide a fuller picture of how treatments perform across different patient groups and in routine clinical practice.

Real-World Evidence (RWE)

In response to the limitations of RCTs, there has been an increasing reliance on real-world evidence (RWE) to understand the broader impact of treatments. RWE is derived from real-world data (RWD), which includes data collected outside the controlled environment of clinical trials. This data can come from electronic health records (EHRs), patient registries, insurance claims, wearable devices, and even social media. By analyzing RWD, healthcare professionals can gain insights into how treatments work in real-world settings, where patients are more diverse and conditions are less controlled.

RWE is particularly valuable for several reasons:

• Long-term health outcomes: RCTs are often limited in duration, providing insights into short-term efficacy and safety. RWE, on the other hand, can capture long-term outcomes, such as the sustainability of treatment benefits, the progression of diseases, and the potential long-term side effects of interventions.
• Medication adherence: In real-world settings, patient adherence to prescribed medications is a significant factor influencing health outcomes. RWE allows researchers to understand how patients adhere to treatments over time and the factors that affect adherence, such as side effects, costs, or lifestyle challenges.
• Health economics: RWE is also critical for understanding the economic impact of treatments. By examining real-world data, healthcare payers and policymakers can assess the cost-effectiveness of therapies and interventions, which informs pricing and reimbursement decisions. Additionally, RWE can reveal whether a treatment reduces hospitalizations, emergency room visits, or the overall burden on the healthcare system, contributing to value-based healthcare.

The use of RWE has become increasingly important for regulatory and reimbursement decisions. Agencies like the U.S. Food and Drug Administration (FDA) and the European Medicines Agency (EMA) are incorporating RWE into their evaluations of new therapies, especially in cases where traditional RCTs are not feasible or provide insufficient data. RWE offers a more holistic view of patient experiences, as it captures the complexities and variations in real-world healthcare settings, ensuring that treatment decisions are based on comprehensive, real-life evidence.

Patient-Reported Outcomes (PROs)

As the focus of healthcare shifts toward patient-centered care, patient-reported outcomes (PROs) have become a critical component of evidence generation. PROs are direct reports from patients about their health, without interpretation by healthcare providers or researchers. These outcomes often include information about symptoms, quality of life, functional status, and overall well-being, offering insights into how patients experience treatments and how those treatments affect their daily lives.

The importance of PROs lies in their ability to capture the subjective aspects of health that are often missed by clinical measures. For example, while an RCT might demonstrate that a drug effectively reduces blood pressure, it may not capture the impact of side effects on a patient’s quality of life, such as fatigue or dizziness. By integrating PROs into evidence generation, healthcare providers gain a deeper understanding of what patients value in their treatments and how healthcare interventions align with their preferences and goals.

PROs are particularly valuable in chronic disease management, mental health, and other areas where quality of life is a critical factor in determining the success of treatment. They also play a crucial role in shared decision-making, where patients and healthcare providers work together to choose treatments that best meet the patient’s needs and preferences. In this context, PROs help ensure that healthcare decisions are not only driven by clinical efficacy but also by patient priorities.

The integration of PROs into evidence generation has also expanded the role of patient-centric measures in health technology assessments (HTAs). Payers and regulatory bodies are increasingly looking at patient-reported data when assessing the value of new therapies. By capturing the voice of the patient, PROs provide a more complete picture of treatment effectiveness, supporting more personalized healthcare approaches.

Social Media as a Source of Evidence Generation

As healthcare evolves, social media has emerged as an innovative source for evidence generation, providing real-time insights into patient experiences, treatment outcomes, and health trends. Platforms like Twitter, Facebook, and patient forums offer a wealth of unfiltered data from millions of users discussing their health journeys, which healthcare professionals can analyze for actionable insights.

Social media allows for real-time data collection from large, diverse populations, offering perspectives that might be missed in traditional clinical studies. Patients share personal experiences about symptoms, side effects, and treatment efficacy, which help healthcare providers understand the real-world impact of treatments. This data is particularly valuable for monitoring medication adherence, tracking emerging disease trends, and capturing patient sentiment toward healthcare interventions.

While social media offers great potential, challenges such as data quality and privacy concerns need to be managed. Data mining techniques, including natural language processing (NLP) and machine learning, are essential for extracting meaningful insights from vast amounts of unstructured social media content.

The integration of social media data into evidence generation provides a patient-centric view of healthcare outcomes. It complements traditional forms of evidence, such as randomized controlled trials and real-world evidence, helping to create a more comprehensive understanding of health and well-being in modern healthcare systems.

Impact on Policy and Decision-Making

The generation of robust healthcare evidence plays a pivotal role in shaping policy and decision-making at various levels of the healthcare system. Whether it’s informing pricing and reimbursement strategies, guiding health technology assessments (HTAs), or determining patient access to care, evidence is the foundation upon which healthcare decisions are built. As healthcare systems face mounting pressures to provide high-quality care while controlling costs, decision-makers increasingly rely on comprehensive, data-driven insights to balance clinical efficacy, economic value, and patient well-being.

Healthcare Payers and Policymakers

Healthcare payers—which include public health systems, private insurers, and governmental agencies—are responsible for determining which treatments, therapies, and interventions will be covered and reimbursed. The decisions made by these payers directly influence patient access to healthcare. Evidence generation, particularly from randomized controlled trials (RCTs) and real-world evidence (RWE), provides critical data to help assess the safety, efficacy, and cost-effectiveness of medical interventions.

One of the primary tools used by healthcare payers is the health technology assessment (HTA). HTA is a systematic process that evaluates the medical, economic, social, and ethical implications of a new healthcare intervention. These assessments draw on evidence from clinical trials, observational studies, and patient-reported outcomes to determine whether a treatment provides value for money and is worth investing in. HTAs influence pricing, reimbursement, and ultimately, the availability of treatments within a healthcare system.

In pricing and reimbursement decisions, evidence helps payers assess whether the price of a drug or intervention is justified by its benefits. In value-based healthcare models, treatments that demonstrate superior outcomes or offer long-term savings (such as reducing hospitalizations) are more likely to receive favorable reimbursement terms. This approach is particularly important in the context of chronic diseases and innovative therapies, such as gene therapies, where upfront costs may be high, but long-term health outcomes could justify the investment.

Additionally, evidence is increasingly being used to address inequities in healthcare access. Policymakers utilize evidence to ensure that healthcare resources are allocated equitably and that vulnerable or underrepresented populations are not left behind. By incorporating real-world evidence and patient-reported outcomes into decision-making, payers can better understand how different populations respond to treatments and design policies that improve healthcare access and outcomes for all.

The Role of ISPOR

The International Society for Pharmacoeconomics and Outcomes Research (ISPOR) plays a crucial role in advancing the field of health economics and outcomes research (HEOR). As a global leader in promoting evidence-based decision-making, ISPOR brings together key stakeholders—academics, industry experts, healthcare providers, and policymakers—to discuss and disseminate best practices in evidence generation. Through its annual conferences, publications, and educational initiatives, ISPOR is instrumental in shaping the future of HEOR and influencing healthcare policy at a global scale.

One of ISPOR’s primary contributions is its focus on methodological advancements in evidence generation. By fostering the development of innovative techniques, ISPOR helps ensure that the healthcare industry remains at the cutting edge of data analysis, modeling, and evaluation. For example, ISPOR has been a driving force behind the adoption of real-world evidence and the use of health technology assessments (HTAs) to inform healthcare policy decisions. These methodologies enable policymakers to make informed choices about the allocation of healthcare resources, ensuring that they are directed toward treatments and interventions that offer the greatest value.

Moreover, ISPOR plays a key role in promoting health equity by encouraging evidence generation that accounts for diverse populations and global health disparities. Through its efforts, ISPOR advocates for the inclusion of underrepresented groups in clinical research and for the generation of evidence that reflects the experiences of people across different geographic, socioeconomic, and cultural backgrounds. By promoting equity in evidence generation, ISPOR helps healthcare systems create more inclusive and sustainable policies that improve health outcomes for all populations, not just those in wealthy or well-resourced regions.

In addition, ISPOR emphasizes the importance of sustainability in healthcare systems. As the global healthcare landscape faces challenges related to rising costs, aging populations, and resource constraints, ISPOR advocates for policies and decision-making frameworks that are both economically and socially sustainable. Evidence generation is key to these efforts, as it provides the data necessary to make long-term, strategic decisions about healthcare investments and resource allocation.

ISPOR Europe 2024, with its theme of “Generating Evidence Toward Health and Well-Being,” will continue to be a platform where these crucial discussions take place. The conference will focus on advancing evidence-generation practices that are not only scientifically rigorous but also patient-centered, cost-effective, and geared toward improving the overall well-being of populations. ISPOR’s leadership in fostering collaboration across sectors will ensure that healthcare systems worldwide are equipped with the evidence they need to create sustainable, equitable, and high-quality care for all.

Emerging Trends in Evidence Generation Toward Health and Well-Being

The pursuit of better health and well-being is driving significant innovations in how evidence is generated within healthcare. Three key trends are playing an increasingly important role: artificial intelligence (AI) and machine learning (ML), the rise of digital health tools, and the shift toward value-based healthcare. These trends not only enhance the precision and scope of evidence but also emphasize a holistic approach that integrates real-time, patient-centered data with a focus on health outcomes that matter most to individuals and communities.

Artificial Intelligence and Machine Learning: Enhancing Evidence Precision

Artificial intelligence (AI) and machine learning (ML) are transforming healthcare by providing advanced tools for analyzing large, complex datasets and generating evidence that is more precise and actionable. AI and ML are particularly valuable in identifying patterns, predicting health outcomes, and enabling personalized treatment plans.

The role of AI in generating evidence toward health and well-being includes:

• Analyzing Large Datasets: AI can process and analyze vast amounts of healthcare data, such as electronic health records (EHRs), genomic data, and real-world evidence (RWE). These technologies uncover patterns and correlations that would otherwise go unnoticed, offering valuable insights into patient outcomes and disease progression.
• Predictive Modeling for Health Outcomes: AI-driven predictive models can forecast health risks and outcomes, enabling earlier interventions. For example, AI can predict which patients are at higher risk of hospitalization or disease progression, empowering healthcare providers to take preventative measures.
• Supporting Personalized Medicine: AI enhances personalized medicine by tailoring treatments to individual patients based on their unique health profiles. This ensures that evidence generation focuses not just on general population trends but also on individual well-being, improving both clinical outcomes and patient satisfaction.

As AI and ML become more integrated into healthcare, they are enabling evidence generation that is not only more precise but also more aligned with improving health and well-being at both individual and population levels.

Digital Health Tools: Generating Real-Time Evidence for Well-Being

The rise of digital health tools, such as wearable devices, mobile apps, and telehealth platforms, is revolutionizing the way evidence is collected and applied to promote health and well-being. These tools provide real-time data on patient behaviors, health outcomes, and quality of life, offering new sources of real-world data (RWD) that reflect how patients manage their health in everyday settings.

Key contributions of digital health tools to generating evidence toward health and well-being include:

• Wearable Devices: Wearables like fitness trackers and smartwatches monitor vital signs, sleep patterns, physical activity, and other health metrics. This continuous stream of data offers insights into how lifestyle factors impact well-being and can be used to generate evidence on treatment adherence, disease management, and preventive health.
• Mobile Health Apps: Health apps enable patients to track symptoms, medications, and health goals. The data collected provides valuable evidence on patient engagement and self-management, contributing to a better understanding of how health interventions affect overall well-being.
• Telehealth and Remote Monitoring: Telehealth platforms expand access to care and generate evidence on how patients respond to remote interventions. Remote monitoring technologies allow healthcare providers to keep track of chronic conditions in real-time, generating evidence that informs more effective and personalized care strategies.

By integrating these digital tools, healthcare providers are able to generate more dynamic, patient-centered evidence that directly impacts the well-being of individuals by addressing both immediate health needs and long-term wellness goals.

Value-Based Healthcare: Linking Evidence to Health and Well-Being

The shift toward value-based healthcare emphasizes that evidence generation must go beyond clinical efficacy to also demonstrate the economic, social, and long-term value of healthcare interventions. In value-based models, healthcare providers are rewarded for improving patient outcomes and well-being, rather than the volume of services provided. This requires comprehensive evidence that captures not only the clinical impact of treatments but also their contributions to quality of life and health equity.

Key aspects of generating evidence in value-based healthcare toward health and well-being include:

• Patient-Centered Outcomes: Value-based healthcare models focus on measuring outcomes that matter most to patients, such as quality of life, functional status, and overall well-being. This requires integrating patient-reported outcomes (PROs) and real-world evidence (RWE) to generate evidence that reflects how treatments affect patients’ day-to-day lives.
• Economic and Social Value: Evidence generation must also demonstrate the cost-effectiveness of interventions. This includes assessing long-term benefits, such as reduced hospitalizations and improved disease management, which contribute to better health outcomes and long-term well-being. Additionally, treatments that address social determinants of health—such as access to care and health disparities—are increasingly important in value-based models.
• Sustainability and Equity: Value-based healthcare also prioritizes the long-term sustainability of healthcare systems. Evidence generation in this context must account for how treatments promote sustainable health outcomes across diverse populations, ensuring that care is equitable and accessible to all.

By focusing on the value of healthcare in terms of patient outcomes, cost-effectiveness, and health equity, value-based healthcare models are driving a more holistic approach to evidence generation—one that prioritizes the well-being of patients and populations.

Oznur Seyhun