Using Data to Support Medicaid Quality Improvement, Payment Reform, and Accountability
Tuesday, February 25, 2020
The data used in quality improvement (QI) activities are only as useful as they are predictive of the measures used for health outcomes, accountability, and payment. This relationship is sometimes referred to as "lead" and "lag" measures. In this Medicaid and CHIP mini-plenary session, presenters will share inspiring and innovative ways they are using data and selecting effective measures to drive improvements in care through quality improvement and value-based purchasing programs. Speakers will share how they use lead measures to evaluate whether quality improvement activities are having an impact on the lag measures they use for health outcomes, accountability, and payment. In particular, the presenters will discuss how the California Maternal Quality Care Collaborative uses near real-time hospital discharge data to drive reductions in maternal mortality; how the Maryland Department of Health uses data from the regional health information exchange, CRISP, to identify beneficiaries in need of additional asthma management services; and how the Minnesota Department of Human Services sends prescription drug data reports to providers and tracks "sentinel" measures to reduce the number of new chronic opioid users..
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