Objectives: The sandbox approach, developed in the financial technologies sector, creates an environment to collaboratively develop and test innovative new products, methods and regulatory approaches, separated from business as usual. It has been used in health care to encourage innovation in response to emerging challenges, but, until recently, has not been used in health technology assessment (HTA). This article summarizes our learnings from using the sandbox approach to address three challenges facing HTA organizations and to identify implications for the use of this approach in HTA.
Methods: We identified three challenging contemporary HTA-related topics to explore in a sandbox environment, away from the pressures and interests of "live" assessments. We convened a pool of 120 stakeholders and experts to participate in various sandbox activities and ultimately co-develop solutions to help HTA organizations respond to the identified challenges.
Results: Important general learnings about the potential benefits and implementation of a sandbox approach in HTA were identified. Consequently, we developed recommendations to guide its use, including how to implement an HTA sandbox in an effective way and the types of challenges for which it may be best suited.
Conclusions: For many HTA organizations, it is difficult to carefully consider emerging challenges and innovate their processes due to risks associated with decision errors and resource limitations. The sandbox approach could reduce these barriers. The potential benefits of addressing HTA challenges in a collaborative "safe space" are considerable.
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http://dx.doi.org/10.1017/S0266462324000412 | DOI Listing |
J Chem Theory Comput
November 2024
Department of Chemical Sciences, University of Padua, via Marzolo 1, Padova I-35131, Italy.
Recently, a stochastic version of the quantum-classical Liouville equation has been proposed [Campeggio, J.; Cortivo, R.; Zerbetto, M.
View Article and Find Full Text PDFDrug Alcohol Rev
November 2024
Shore & Whariki Research Centre, College of Health, Massey University, Auckland, New Zealand.
Introduction: The study aims are to: (i) explore methods for identifying alcohol company marketing in metaverses; (ii) identify current types of alcohol marketing in metaverses; and (iii) identify dominant portrayals and meanings of alcohol marketing in these settings.
Methods: Our design was exploratory, employing various approaches to identify alcohol company marketing across multiple metaverses. In stage one, we systematically navigated through metaverses as an avatar, documenting and coding all instances of alcohol company marketing.
Int J Technol Assess Health Care
November 2024
Science Evidence and Analytics Directorate, National Institute for Health and Care Excellence, UK.
Objectives: The sandbox approach, developed in the financial technologies sector, creates an environment to collaboratively develop and test innovative new products, methods and regulatory approaches, separated from business as usual. It has been used in health care to encourage innovation in response to emerging challenges, but, until recently, has not been used in health technology assessment (HTA). This article summarizes our learnings from using the sandbox approach to address three challenges facing HTA organizations and to identify implications for the use of this approach in HTA.
View Article and Find Full Text PDFBrief Bioinform
July 2024
National Institute of General Medical Sciences, National Institutes of Health, 9000 Rockville Pike, Bethesda, Marylnd 20892, USA.
Biomedical data are growing exponentially in both volume and levels of complexity, due to the rapid advancement of technologies and research methodologies. Analyzing these large datasets, referred to collectively as "big data," has become an integral component of research that guides experimentation-driven discovery and a new engine of discovery itself as it uncovers previously unknown connections through mining of existing data. To fully realize the potential of big data, biomedical researchers need access to high-performance-computing (HPC) resources.
View Article and Find Full Text PDFJMIR Form Res
October 2024
Human-Computer Interaction Institute, Carnegie Mellon University, Pittsburgh, PA, United States.
Background: Online mental health communities (OMHCs) are an effective and accessible channel to give and receive social support for individuals with mental and emotional issues. However, a key challenge on these platforms is finding suitable partners to interact with given that mechanisms to match users are currently underdeveloped or highly naive.
Objective: In this study, we collaborated with one of the world's largest OMHCs; our contribution is to show the application of agent-based modeling for the design of online community matching algorithms.
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