How can a simple, systemwide framework empower 20,000 frontline staff and leaders across Scripps Health to boost retention, ...

Effective board governance in complex health systems requires structured approaches that cascade quality and safety ...

How can we blend traditional telehealth sessions with smartphone applications while addressing digital literacy barriers to create more accessible and effective mental health treatment for all pati ...

Some common medical services vary greatly in cost depending on the facility or specialist. This study examines ways to incentivize physicians to refer to sites that offer lower cost and equivalent ...

The global health care sector faces unprecedented financial strain from increasing complexity and the drive for better care. In response, health care systems are increasingly adopting value-based ...

Can the future of behavioral health care be improved with patient-centeredness, integrated practice units, and value-based care?

A survey of the NEJM Catalyst Insights Council finds strong support for caregivers who voluntarily care for family, friends, and neighbors.

How can virtual treatment models address the critical gaps in the U.S. mental health system while providing personalized, evidence-based care for those with serious mental health needs, when over 1 ...

Many patients with serious illness prioritize comfort over the prolongation of life in the final days and weeks prior to death. Goals-of-care discussions (GOCDs) can provide patients with the ...

An economic model for a population health initiative focused on reducing cardiovascular disease risk, in order to examine the cost and revenue factors that influence financial sustainability.

This issue of NEJM Catalyst Innovations in Care Delivery includes articles, case studies, and research reports on improving stroke management, incenting high-value referrals, modeling the financial ...

The initiative across multiple hospitals of BJC HealthCare to improve goals-of-care discussion efforts included enhanced mortality risk prediction using machine learning, efficient clinical workflows ...