Patient experience data are used to set performance targets and monitor effectiveness of quality improvement (QI) activities. However, assessing and determining areas that need improvement can be challenging, especially when there are many measures, making it harder to synthesize and identify clear priorities. We describe a QI priority metric and technique for assessing cross-sectional patient experience data that explicitly examine subgroup performance and priorities. The QI priority metric combines 2 patient experience metrics (case-mix-adjusted mean for a patient experience measure and partial correlation of that measure with an overall rating) into a single priority value, allowing leaders to quickly identify improvement areas across multiple measures and patient groups. We examined the priority metric overall and by patient groups (ie, by race, ethnicity, and language preference). We found the priority metric synthesized and identified 2 priority areas for improvement for the entire patient population and revealed several additional improvement priorities specific to patient groups. This metric has the potential to be an informative and self-educating technique for promoting uniformly high-quality care and enhancing performance.
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