ISPOR 2024: Key Takeaways, Trends and Insights for HEOR

Takeaways from the premier conference for health economics and outcomes research (HEOR)

The International Society for Pharmacoeconomics and Outcomes Research (ISPOR) hosts an annual conference where experts from around the world share their latest research findings. The ISPOR 2024 conference, held May 5-8, 2024, brought together the brightest minds in HEOR for a stimulating and informative experience. This conference showcased the latest methodological advancements and the progressive role of HEOR in a healthcare landscape that is becoming more complex and data-driven. Experts from Maxis Clinical Sciences actively participated in the discussion, extracting important takeaways and trends that will impact future evidence-based decision-making.

This year’s conference highlighted a holistic approach to patient care, recognizing that health extends beyond the clinical setting. Future HEOR initiatives should take into account social determinants of health, patient-reported outcomes, and real-world evidence to make meaningful and lasting improvements in population health.

Data Integration Challenges and Opportunities

Real-world evidence (RWE) and large datasets hold immense potential to inform HEOR analyses, but the field encounters problems around data integration, standardization, and privacy. ISPOR 2024 featured discussions on innovative approaches to address these challenges, including the development of interoperable data platforms and robust data governance frameworks that maintain patient trust.

Artificial Intelligence (AI) & Machine Learning (ML)

AI and ML methods have proven to be powerful tools in healthcare decision-making, from analyzing vast and complex datasets to generating predictive models and facilitating personalized medicine approaches. However, concerns around data security, bias, and ethical implications continue to be major considerations in the adoption of these technologies.

With the growing recognition of the importance of patient-reported outcomes (PROs) in HEOR, we can expect a greater emphasis on developing and validating PRO measures that accurately capture the patient experience and align with their values and preferences.

Cost-Effectiveness in a Multi-Stakeholder Environment

Many successful healthcare interventions struggle with the “wrong pocket problem,” where different stakeholders bear the costs and benefits. ISPOR 2024 participants pointed out the need for innovative cost-benefit modeling approaches that account for the broader societal impact of healthcare interventions and facilitate collaboration between different sectors.

Transparent and reproducible AI models

Experts prioritize developing transparent and reproducible AI models, guaranteeing healthcare decision-making is based on sound, evidence-based insights, and builds trust in AI’s value in HEOR.

The event also covered additional key topics across the healthcare spectrum, including:

Healthcare Equity and Policy

Research and Evidence

Pharmaceuticals and Therapies

Data and Analytics

Patient-Centered Care

Evidence-Based Insights for Healthcare Transformation

Moving forward, the healthcare industry must reconsider how it utilizes evidence to create a tangible impact. A comprehensive approach to patient care, prioritizing effective treatments, and focusing on patient well-being can improve healthcare for everyone. Our team of experts is available to collaborate with you, sharing our expertise in HEOR, data analytics, and market access to help you make informed decisions. The question is, what steps will you take to join this effort and learn more about our collaborative approach?

What if the cure for a devastating disease wasn’t locked away in a lab, but hidden within mountains of existing data? Artificial intelligence (AI) has the power and is a rapidly growing area, with its significant role in RWE analytics and candidate drug identification. The use of AI and ML in drug R&D has been hailed as a revolutionary approach to cutting time, money, and resources. The global market for AI in drug development is rising, and as per Transparency Market Research, is projected to cross US$ 10.93 Bn by 2031. Pharmaceutical companies must proactively adopt this technology to stay competitive.