Factors leading to patient disengagement for unknown reasons in virtual collaborative care.

Introduction: Collaborative care (CoCM) has been utilized as one strategy for improving access to behavioral health treatment through the primary care setting. However, despite the increased prevalence rates, need for services, and expansion of behavioral health into primary care, there are patients who initiate treatment but disengage for unknown reasons and without communication with their care team. This study analyzes treatment factors by comparing patients who disengage from CoCM for known versus unknown reasons to identify factors that may enhance the ability of providers to implement strategies for retaining those who have initiated care.

Factors influencing virtual collaborative care outcomes for depression and anxiety.

Context And Aims: In the United States, access to evidence-based behavioral health treatment remains limited, contributing to inadequate treatment for individuals with depression and anxiety disorders. The Collaborative care model (CoCM), the integration of behavioral healthcare into primary care, has been shown to be effective in addressing this issue, particularly when delivered virtually through telehealth platforms. While collaborative care has been shown to be effective, little has been studied to understand the impact of patient treatment factors on patient improvement.

A non-invasive platform for functional characterization of stem-cell-derived cardiomyocytes with applications in cardiotoxicity testing.

We present a non-invasive method to characterize the function of pluripotent stem-cell-derived cardiomyocytes based on video microscopy and image analysis. The platform, called Pulse, generates automated measurements of beating frequency, beat duration, amplitude, and beat-to-beat variation based on motion analysis of phase-contrast images captured at a fast frame rate. Using Pulse, we demonstrate recapitulation of drug effects in stem-cell-derived cardiomyocytes without the use of exogenous labels and show that our platform can be used for high-throughput cardiotoxicity drug screening and studying physiologically relevant phenotypes.