Improving patient-reported measures in oncology: A payer call to action

Despite rising interest in integrating the patient voice in value-based payment (VBP) models for oncology, barriers persist to implementing patient-reported measures (PRMs), including patient-reported performance measures (PR-PMs). This article describes the landscape of oncology PRMs and PR-PMs, identifies implementation barriers, and recommends solutions for public and private payers to accelerate the appropriate use of PRMs in oncology VBP programs. Our research used a multimethod approach that included a literature review, landscape scan, stakeholder interviews and survey, and a multistakeholder roundtable. The literature review and landscape scan found that limited oncology-specific PR-PMs are available and some are already used in VBP programs. Diverse stakeholder perspectives provided insight into filling current gaps in measurement and removing implementation barriers, such as limited relevance of existing PRMs and PR-PMs for oncology; methodological challenges; patient burden and survey fatigue; and provider burden from resource constraints, competing priorities, and insufficient incentives. Key recommendations include: (a) identify or develop meaningful measures that fill gaps, engaging patients throughout measure and program development and evaluation; (b) design programs that include scientifically sound measures standardized to reduce patient and provider burden while supporting care; and (c) engage providers using a stepwise approach that offers resources and incentives to support implementation

Reconstructing 3D genomes from chromosomal contact maps

International audienceA computational challenge raised by chromosome conformation capture (3C) experiments is to reconstruct spatial distances and three-dimensional genome structures from observed contacts between genomic loci. We propose a two-step algorithm, ShRec3D, and assess its accuracy using both in silico data and human genome-wide 3C (Hi-C) data. This algorithm avoids convergence issues, accommodates sparse and noisy contact maps, and is orders of magnitude faster than existing methods