Answers are grounded in this paper and cite their sources.
Health Technology Assessment (HTA) evaluations play a crucial role in informing decisions related to the adoption, reimbursement, and utilization of healthcare technologies. To ensure robust and reliable outcomes, HTA requires a diverse range of evidence, which may vary depending on the specific technology under evaluation, the questions to be answered, and the available data sources. It is imperative to design and conduct studies that generate high-quality and pertinent evidence to facilitate effective HTA evaluations. Furthermore, sophisticated and appropriate statistical methodologies are often necessary to analyze and interpret the collected data in HTA assessments. Recognizing the lack of discussion and best practice recommendations to fulfill the HTA needs, the American Statistical Association (ASA) Biopharmaceutical Section (BIOP) Health Technology Assessment (HTA) Scientific Working Group (SWG) has undertaken an initiative to assess the HTA landscape in major global markets. We aim to offer strategic considerations for evidence planning related to HTA, alongside specific statistical methodologies commonly used in delivering clinical evidence and demonstrating value. Our targeted audience includes statisticians working in clinical development who may not be familiar with the intricacies and specific needs of HTA. This paper focuses specifically on study designs and statistical methods. This paper sheds light on the challenges that persist in study design and analytic approaches concerning HTA evidence requirements and discusses potential opportunities and mitigations. By bridging the knowledge gap in HTA needs and offering practical guidance on study designs and statistical methods, this research advances the field of statistics within HTA.
No takes yet. Share an insight, caveat, or question.
Dunger‐Baldauf et al. (2025) studied this question.
Synapse has enriched 10 related papers. Consider them for comparative context: