Navigating Uncertainty in Health Technology Assessment and Regulatory Decision Making

by Odelle Technology

In the fast-paced landscape of healthcare, the evaluation and approval of new drugs are a complex and multifaceted endeavour. Regulatory bodies and health technology assessment (HTA) organisations are tasked with making critical decisions that affect patient care, public health, and healthcare expenditure. However, these decisions are often shrouded in uncertainty, stemming from a myriad of sources such as incomplete clinical data, methodological limitations, and evolving medical paradigms. Recognising the need for a structured approach to managing uncertainty, the HTAi-DIA Working Group has developed comprehensive guidance aimed at navigating the intricacies of uncertainty in regulatory and HTA decision-making.

Understanding the Spectrum of Uncertainty

Uncertainty pervades every stage of the drug evaluation process, presenting a formidable challenge to decision-makers (Han et al., 2011). From the early stages of preclinical research to post-market surveillance, uncertainties manifest in various forms, including statistical variation, data gaps, and unforeseen shifts in clinical practice (Hogervorst et al., 2022). By comprehensively understanding the spectrum of uncertainty, stakeholders can adopt initiative-taking measures to mitigate risks and perfect decision-making processes.

A Systematic Approach to Uncertainty Management

At the heart of the guidance is a systematic approach to uncertainty management, underpinned by rigorous methodologies and structured frameworks (EMA Regulatory Science, 2018). The document advocates for the systematic identification, categorization, and mitigation of uncertainties throughout the decision-making continuum (Tuffaha et al., 2021). By employing standardized processes and tools, regulatory bodies and HTA organizations can enhance transparency, consistency, and stakeholder alignment in their evaluations.

Key Building Blocks of Uncertainty

Central to the guidance are the key building blocks of uncertainty, which serve as foundational elements for decision-making (Janiaud et al., 2021). These building blocks encompass a wide range of factors, including clinical evidence gaps, methodological challenges, and societal values (Hogervorst et al., 2022). By deconstructing uncertainty into its constituent parts, decision-makers gain deeper insights into the underlying complexities of drug evaluation, enabling more informed and nuanced decision-making.

Illustrative Case Studies

The guidance is enriched with illustrative case studies that illuminate the real-world implications of uncertainty in drug development and regulatory decision-making (Bloem et al., 2021). These case studies offer compelling narratives, highlighting the dynamic interplay between scientific evidence, regulatory standards, and clinical practice (Agrawal et al., 2022). Through in-depth analysis and reflection on these case studies, stakeholders can glean valuable lessons and best practices for navigating uncertainty effectively.

Proactive Mitigation Strategies

A cornerstone of the guidance is the exploration of proactive mitigation strategies aimed at managing uncertainty throughout the drug lifecycle (EMA Regulatory Science, 2018). From adaptive trial designs and real-world evidence generation to post-market surveillance initiatives, stakeholders are encouraged to adopt a multifaceted approach to uncertainty management (Bloem et al., 2021). By integrating mitigation strategies into decision-making processes, regulatory bodies and HTA organizations can mitigate risks, minimize decision errors, and perfect patient outcomes.

Facilitating Multistakeholder Collaboration

Recognizing the inherent complexity of uncertainty management, the guidance emphasizes the importance of multistakeholder collaboration (Hogervorst et al., 2022). By fostering dialogue and knowledge exchange among regulators, industry stakeholders, healthcare providers, and patient advocates, decision-makers can harness collective ability to address uncertainty more effectively (Trowman et al., 2021). Through collaborative efforts, stakeholders can find shared goals, navigate divergent perspectives, and achieve consensus on complex issues related to drug evaluation.


In conclusion, the guidance provided by the HTAi-DIA Working Group is a significant milestone in the field of uncertainty management in regulatory and HTA decision making. By embracing a systematic approach, using key building blocks, and fostering multistakeholder collaboration, regulatory bodies and HTA organizations can navigate uncertainty with greater confidence and clarity. In doing so, they can uphold the highest standards of patient safety, promote evidence-based decision-making, and advance the goal of improving healthcare outcomes for all.


– Agrawal, S., Arora, S., Amiri-Kordestani, L., et al. (2022). Use of single-arm trials for US Food and Drug Administration Drug approval in oncology, 2002 – 2021. JAMA Oncol, 9: 266-272.

– Bloem, L.T., Bot, R.E., Mantel-Teeuwisse, A., et al. (2021). Pre-approval and post-approval availability of evidence and clinical benefit of conditionally approved cancer drugs in Europe: A comparison with standard approved cancer drugs.

– EMA Regulatory Science (2018). European Medicines Agency. Retrieved from

– Han, P.K.J., Klein, W.M.P., Arora, N.K. (2011). Varieties of uncertainty in health care: A conceptual taxonomy. Med Decis Mak Int J Soc Med Decis Mak, 31(6): 828-838.

– Hogervorst, M.A., Vreman, R.A., Mantel-Teeuwisse, A.K., Goettsch, W.G. (2022). Reported challenges in health technology assessment of complex health technologies. Value Health J Int Soc Pharmacoeconomics Outcomes Res, 25(6): 992-1001.

– Janiaud, P., Irony, T., Russek-Cohen, E., Goodman, S.N. (2021). U.S. Food and Drug Administration reasoning in approval decisions when efficacy evidence is borderline, 2013 – 2018. Ann Intern Med, 174(11): 1603-1611.

– Tuffaha, H., Powers, A., Ollendorf, D.A. (2021). Considering and communicating uncertainty in health technology assessment. Int J Technol Assess Health Care, 37(1): e74.

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