Using a Quality Improvement Priority Metric to Promote Uniformly High-Quality Care: An Illustrative Example Using...

Area of Science:

• Healthcare Quality Improvement
• Patient Experience Measurement
• Health Services Research

Background:

• Patient experience data are crucial for setting performance targets and monitoring quality improvement (QI) activities.
• Assessing and prioritizing areas for improvement from extensive patient experience data can be challenging.
• Current methods may struggle to synthesize information and identify clear priorities across multiple measures and patient groups.

Purpose of the Study:

• To introduce and evaluate a novel QI priority metric for assessing cross-sectional patient experience data.
• To examine how the metric identifies improvement priorities overall and within specific patient subgroups.
• To provide a tool for healthcare leaders to efficiently identify and address areas needing improvement.

Main Methods:

• Developed a QI priority metric combining case-mix-adjusted mean patient experience scores with partial correlations to an overall rating.
• Applied the metric to cross-sectional patient experience data.
• Analyzed metric performance for the overall patient population and stratified by race, ethnicity, and language preference.

Main Results:

• The QI priority metric successfully synthesized patient experience data into a single priority value.
• Identified two main areas for improvement for the entire patient population.
• Revealed additional, specific improvement priorities for distinct patient groups.

Conclusions:

• The QI priority metric offers an effective technique for assessing patient experience data and identifying improvement priorities.
• It facilitates the quick identification of critical areas for enhancement across diverse patient populations.
• This metric has the potential to promote uniformly high-quality care and enhance overall healthcare performance.