Approaches to Incorporation of Preferences into Health Economic Models of Genomic Medicine: A Critical Interpretive Synthesis and Conceptual Framework.

Introduction: Genomic medicine has features that make it preference sensitive and amenable to model-based health economic evaluation. Preferences of patients, caregivers, and clinicians related to the uptake and delivery of genomic medicine technologies and services that are not captured in health state utility weights can affect the intervention's cost-effectiveness and budget impact. However, there is currently no established or agreed-on approach for integrating preference information into economic evaluations.

Toward value-based care using cost mining: cost aggregation and visualization across the entire colorectal cancer patient pathway.

Background: The aim of this study is to develop a method we call "cost mining" to unravel cost variation and identify cost drivers by modelling integrated patient pathways from primary care to the palliative care setting. This approach fills an urgent need to quantify financial strains on healthcare systems, particularly for colorectal cancer, which is the most expensive cancer in Australia, and the second most expensive cancer globally.

Methods: We developed and published a customized algorithm that dynamically estimates and visualizes the mean, minimum, and total costs of care at the patient level, by aggregating activity-based healthcare system costs (e.

Analysis of risk factors for immune-related adverse events induced by immune checkpoint inhibitor treatment in cancer: A comprehensive systematic review.

Background: Immune-related adverse events (irAE) pose challenges to the use of immune checkpoint inhibitors (ICI). While risk factors for irAE are emerging, most studies are small, retrospective analyses that seldom report on diverse cancers or rare irAE. This paper reports a systematic review that summarises literature on irAE risk factors across cancers and proposes a categorisation approach.

ESR Essentials: how to get to valuable radiology AI: the role of early health technology assessment-practice recommendations by the European Society of Medical Imaging Informatics.

AI tools in radiology are revolutionising the diagnosis, evaluation, and management of patients. However, there is a major gap between the large number of developed AI tools and those translated into daily clinical practice, which can be primarily attributed to limited usefulness and trust in current AI tools. Instead of technically driven development, little effort has been put into value-based development to ensure AI tools will have a clinically relevant impact on patient care.