Background/aims: Research focusing on the perspectives of healthcare managers, who are often key in devising strategies for the implementation of self-management solutions, is limited. This study aimed to investigate the ...

Editorial: Last year we launched the EBM Methods Verdicts as part of an attempt to keep on top of developments in statistics that will impact on the way we do research.1 2 We focused on statistical methods and in particular ...

There are a growing number of studies using mediation analysis to understand the mechanisms of health interventions and exposures. Recent work has shown that the reporting of these studies is heterogenous and incomplete. ...

Purpose Patient-reported outcome and experience measures (PROMs/PREMs) are well established in research for many health conditions, but barriers persist for implementing them in routine care. Implementation science (IS) ...

Integrated care has the potential to ease the increasing pressures faced by health and social care systems, however, challenges around measuring the benefits for providers, patients, and service users remain. This paper ...

Procuring and managing diagnostic services, such as laboratory medicine, is generally based on cost and activity. Improving productivity of laboratory services therefore tends to focus on reducing the cost per test. However, ...

Background: Several social and policy developments have led to research partnerships in mental health research, which depart from traditional research models. One form of such partnerships is among research institutions, ...

The innovation pathway by which a newly discovered biomarker is developed into a medical test and used in routine clinical practice comprises a number of different processes split between 2 phases. The first follows on ...

Background The innovation pathway by which a newly discovered biomarker is developed into a medical test and used in routine clinical practice comprises a number of different processes split between 2 phases. The first ...

The field of clinical natural language processing has been advanced significantly since the introduction of deep learning models. The self-supervised representation learning and the transfer learning paradigm became the ...