The 2024 International Society for Pharmacoeconomics and Outcomes Research (ISPOR) Conference was a dynamic health economics and outcomes research (HEOR) forum. Life science and HEOR leaders came together to showcase cutting-edge technologies and methodologies set to redefine their research. From my perspective, it’s easy to be excited about breakthrough innovation happening in the space, but with that comes many hurdles. Here are my top five takeaways and trends from the conference:
A recurring theme throughout the conference was the pervasive issue of poor data quality, including missing data, duplications, and challenges associated with tokenized or linked patient information. During the plenary session on Day 2, among other topics, panelists shared personal feelings of distrust in current data methods that have led to some of these issues yet expressed optimism in how trust can be reinstilled. One area mentioned was improving transparency in vendor relationships, but also internally across teams, as Life Science and HEOR organizations break down data silos and unify their data strategies.
Artificial Intelligence (AI) dominated discussions and presentations. According to several of my research colleagues in attendance, posters and published studies were also much more AI-focused than in years past. This reflects AI’s growing influence and utilization potential in Life Sciences and HEOR. As organizations identify effective AI models and applications for HEOR and drug discovery, session leaders stressed the importance of setting expectations on productivity and accuracy, in addition to addressing foundational gaps in data analysis. There were many theories on where the industry lies in the current AI hype cycle, but further adoption and efficacy are likely dependent on confidence in foundational components such as data quality itself.
The use of open claims data is gaining traction from many organizations due to advantages in latency and patient sample sizes. Still, issues persist as data teams often face challenges getting open claims data to regulatory-grade quality, resulting in delayed project timelines. In general, conference dialogues underscored the necessity for better data quality to support more reliable healthcare research and decision-making.
Our partner, Columbia Data Analytics, presented a poster at ISPOR 2023 analyzing the effectiveness of open vs. closed claims in HEOR studies and finding that open claims have significant advantages for health outcomes studies.
Life Science and HEOR leaders are embracing the trend to unlock the impact of supplemental data types, e.g., Social Determinants of Health (SDoH), that add greater dimension and granularity to patient journey analyses. However, accurately and actionably constructing the patient journey is a challenge for many ISPOR-attendee organizations, prioritizing the value of data quality and richness, e.g., fill rates, over acquiring massive datasets alone. It is clear that pharmaceutical companies are focused on refining their data analysis capabilities by seeking out and exploring the full potential of datasets that may be small but deliver an integrated and more complete view of a patient’s care continuum.
The Annual ISPOR Conference was not just a showcase of industry progress but also a forum for considering the future directions of HEOR. How the industry evolves with new tools and ideas will significantly influence therapeutic development, healthcare delivery, and policy-making.
Reflecting on the conference, it's clear that as we advance, the combination of high-quality data, innovative technology, and collaborative effort will be essential in navigating the complexities of modern HEOR studies. Kythera Labs remains committed to leading this charge, ensuring our solutions and insights continue to empower healthcare professionals and improve patient outcomes. Connect with me on LinkedIn or reach out to continue the conversation on the impact of data quality and new technologies on HEOR.
