Evaluating the Quality of Virtual Urgent Care: Barriers, Motivations, and Implementation of Quality Measures.

BACKGROUND: Experts estimate virtual urgent care programs could replace approximately 20% of current emergency department visits. In the absence of widespread quality guidance to programs or quality reporting from these programs, little is known about the state of virtual urgent care quality monitoring initiatives. OBJECTIVE: We sought to characterize ongoing quality monitoring initiatives among virtual urgent care programs. APPROACH: Semi-structured interviews of virtual health and health system leaders were conducted using a pilot-tested interview guide to assess quality metrics captured related to care effectiveness and equity as well as programs' motivations for and barriers to quality measurement. We classified quality metrics according to the National Quality Forum Telehealth Measurement Framework. We developed a codebook from interview transcripts for qualitative analysis to classify motivations for and barriers to quality measurement. KEY RESULTS: We contacted 13 individuals, and ultimately interviewed eight (response rate, 61.5%), representing eight unique virtual urgent care programs at primarily academic (6/8) and urban institutions (5/8). Most programs used quality metrics related to clinical and operational effectiveness (7/8). Only one program reported measuring a metric related to equity. Limited resources were most commonly cited by participants (6/8) as a barrier to quality monitoring. CONCLUSIONS: We identified variation in quality measurement use and content by virtual urgent care programs. With the rapid growth in this approach to care delivery, more work is needed to identify optimal quality metrics. A standardized approach to quality measurement will be key to identifying variation in care and help focus quality improvement by virtual urgent care programs.

Clinical Features vs CT Findings to Estimate Need for Surgery in Small Bowel Obstruction.

This comparative effectiveness research compares the ability of clinical features vs clinical features with computed tomography (CT) to estimate the need for small bowel obstruction surgery.