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Tuesday, July 16, 2013
Care coordination relies on timely data about individual patients, while effective population health management requires viewing each patient in the context of an overall population. Typical patient registries offer a view of all patients with a particular condition, such as diabetes. They identify patients who need intervention by comparing data on current status from the EHR against fixed protocols or guidelines.
As provider groups begin to assume financial risk for population health, they need to determine priorities for care by viewing patients in the context of comparative data. Groups are also taking advantage of predictive models built using large databases that stratify patients by risk of some outcome, e.g., estimating the risk of hospital admission over the next six months for a patient with heart failure. As interactive analytical applications are deployed to multiple regions or sites across a large heath system, the ability to tailor queries to a site’s specific interests enhances the use of data to optimize care coordination. But this flexibility and ease of use can be a double-edged sword. Ensuring standardization of reporting and end-user understanding are critical in assuring provider acceptance of data. As sites apply different inclusion and exclusion criteria, “different versions of the truth” can emerge. Upon completion, participants will be able to cite the advantages of governance for data and analytics to support care coordination and improved performance across health systems.