Utilization of Artificial Intelligence By Health Technology Assessment Agencies to Improve Efficiency of Health Technology Appraisals

OBJECTIVES: The rising interest in advanced analytics, including artificial intelligence (AI), has generated a critical paradigm shift in the way data are collected and managed. In the healthcare sector, AI has been mainly used by pharmaceutical industries to accelerate and optimize drug discovery, precision medicine, and clinical trial set-up. However, patient access to new technologies can still be delayed due to the time-consuming evaluation processes undertaken by Health Technology Assessment (HTA) agencies. This research aims to identify whether AI is being used by HTA agencies to expedite technology review processes through automatization of routine tasks.

METHODS: A targeted gray literature search was conducted to explore if the potential applications of AI are being considered and whether AI-enhanced methods are being utilized by HTA agencies to improve efficiency of healthcare technology evaluations. Particularly, NICE, G-BA, PBAC, and CADTH/INESSS websites were investigated.

RESULTS: HTA agencies have identified AI’s potential to improve the efficiency of decision-making. However, AI is currently not being formally utilized to accelerate and automatize the technology appraisal process. Instead, HTA agencies focus on the utility of AI to improve healthcare delivery in clinical practice (eg, the PEAK project undertaken by the G-BA). Also, an international collaboration has been formed between HTA bodies in Australia, Canada, and the UK aiming to facilitate knowledge-sharing about developments in the evaluation of digital health technologies, including technologies that involve an AI component.

CONCLUSIONS: Despite the advent of novel AI-assisted methods that could automate and potentially expedite routine tasks (eg, systematic literature reviews), AI has not yet been formally incorporated in HTA processes to optimize efficiency of technology appraisals. Opportunity exists for AI-enhanced methods to be used by HTA agencies for integrating evidence from clinical trials and real-world data to support decision-making and accelerate patient access to innovative therapies.