Value-Based Healthcare in Practice: IDEATE, a Collaboration to Design and Test an Outcomes-Based Agreement for a Medicine in Wales.

Objective: To develop a sustainable, scalable methodology for the design of outcome-based agreements (OBAs) that works on the ground and dynamically overcomes historical challenges.

Methods: Project IDEATE co-created solutions to known (and emergent) challenges via iterative workshops and real-world data analysis to develop and refine a hypothetical model for an OBA in a trusted research environment. A cross-disciplinary collaboration between National Health Service (NHS) Wales, industry and academia was developed.

Revisiting Dynamics of Quantum Causal Structures-When Causal Order Evolve?

Recently, there has been substantial interest in studying the dynamics of quantum theory beyond that of states, in particular, the dynamics of channels, measurements, and higher-order transformations. Castro-Ruiz et al. pursues this using the process-matrix formalism, together with a definition of the possible dynamics of such process matrices, and focusing especially on the question of evolution of causal structures.

Impact of the PATH Statement on Analysis and Reporting of Heterogeneity of Treatment Effect in Clinical Trials: A Scoping Review.

Background: The Predictive Approaches to Treatment Effect Heterogeneity (PATH) Statement provides guidance for using predictive modeling to identify differences (i.e., heterogeneity) in treatment effects (benefits and harms) among participants in randomized clinical trials (RCTs).

Measurement of the Optical Constants of Sand Samples Using Ellipsometry on Sand-Adhesive Composites.

In order to model the propagation of light through a sand cloud, it is critical to have accurate data for the optical constants of the sand particles that comprise it. The same holds true for modeling propagation through particles of any type suspended in a medium. Few methods exist, however, to measure these quantities with high accuracy.

Linear Program for Testing Nonclassicality and an Open-Source Implementation.

A well-motivated method for demonstrating that an experiment resists any classical explanation is to show that its statistics violate generalized noncontextuality. We here formulate this problem as a linear program and provide an open-source implementation of it which tests whether or not any given prepare-measure experiment is classically explainable in this sense. The input to the program is simply an arbitrary set of quantum states and an arbitrary set of quantum effects; the program then determines if the Born rule statistics generated by all pairs of these can be explained by a classical (noncontextual) model.