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Understanding how big data and AI will shape the market access and HEOR landscape

Key themes and takeaways from ISPOR 2023: Understanding how big data and AI will shape the market access and HEOR landscape This year, in addition to presenting our original research, the GPI team were also able to attend many of the breakout and plenary sessions at ISPOR 2023. In these, the hot topics were around…

    Key themes and takeaways from ISPOR 2023: Understanding how big data and AI will shape the market access and HEOR landscape

    This year, in addition to presenting our original research, the GPI team were also able to attend many of the breakout and plenary sessions at ISPOR 2023. In these, the hot topics were around the use of large real-world databases and how artificial intelligence (AI) and machine learning can be applied to many parts of HEOR and HTA.

    From our experience in data and analytics, data is at the heart of all these initiatives.

    The first plenary session focussed on the European Health Data Space (EHDS) and how this aims to capture real-world evidence (RWE) across Europe. Orphan drugs may particularly benefit from these data, where clinical trial data to support decision making are limited to a small sample. The different perspectives on the challenges and opportunities for these data all acknowledged that some markets, such as Denmark and Sweden, have more advanced data collection and registries than others. With this in mind, we question the ease of implementation of EHDS as a standardised and complete dataset representing multiple European markets, particularly where fragmented and regionalised infrastructure may present barriers. We know the complexities of capturing price and reimbursement data across multiple markets and know this scale of data collection and standardisation will be challenging.

    Numerous sessions focussed on the application of different AI and machine learning methodologies for different purposes.

    These included various predictive analytics, generative AI, and natural language processing. Although mostly successful, some limitations were identified including both methodological and data transparency. These limitations supported the conclusion that human oversight and augmentation are critical. Generally, it was determined that the application of these methodologies in HEOR and HTA are in their infancy, but it will be something to watch over the next few years. The adoption of these technologies moving forward is at the heart of what we do at GPI and formed a part of our research presented at ISPOR Europe 2023. It was great to discuss both the benefits and limitations around these exciting advancements with both payers and market access stakeholders and are excited to be involved in the evolution of this rapidly advancing field.

    Can machine learning accurately predict payer behaviour?

    As machine learning has gained popularity and excitement across many sectors, we investigated whether it could be applied to market access. In this research, we trained and tested the accuracy of machine learning models, when applied to our value-based pricing methodology, to determine the feasibility of predicting payer decisions and prices for a new orphan asset in France, Germany and the UK.

    Found this interesting? Download the full research here.

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