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Resource Overview
Population Health Management requires aggregating patient data from a number of sources, and conducting analytics and modeling to derive actionable insights that translate to increased patient engagement and improved outcomes.  Resources in this section describe data sources that are available to health centers, how to access and integrate them, and ways to enrich them with patient-provided data through health risk assessments and patient engagement technologies.
Getting and Using PHM and SDH Data
Predictive Analytics: An Overview for Community Health Centers

Predictive Analytics: An Overview for Community Health Centers

from Capital Link

According to this resource, Capital Link's Predictive Analytics: An Overview for Community Health Centers, using data and technology, organizations can now move beyond simply tracking the past to anticipating the future. Although common in many industries for years, the use of predictive analytics is now becoming more applicable to health care. Data collection efforts currently utilized by Federally Qualified Health Centers are only a starting point for what is necessary to be effective in improving patient care, reducing costs, and negotiating favorable contracts with payers. The use of predictive analytics to make and support business decisions is essential as a Health Center’s payer mix evolves and it becomes responsible for all patients attributed to it by Managed Care and Accountable care organizations (regardless if they are treated or not). A Health Center’s ability to engage with payers and understand which patients are more likely to seek inappropriate care or have a higher risk of having a chronic condition, and assist them in avoiding expensive hospitalizations and readmissions has become critical.

The purpose of this overview is to do the following:

  • Define predictive analytics
  • Provide an overview of its history and development
  • Address the data and resources needed to predict a patient’s future behavior
  • Identify how a Health Center can begin utilizing it
  • Include specific examples of how it has been successfully used
  • Clarify Health Centers’ understanding and expectations of predictive analytics

Image from Capital Link.

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Acknowledgements

This resource collection was cultivated and developed by the HITEQ team with valuable contributions from the National Association of Community Health centers (NACHC) as well as HITEQ's Advisory Committee and many health centers who have graciously shared their experiences with HITEQ.

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The Quadruple Aim
Quadruple Aim

A Conceptual Framework

Improving the U.S. health care system requires four aims: improving the experience of care, improving the health of populations, reducing per capita costs and improving care team well-being. HITEQ Center resources seek to provide content and direction aligned with the goals of the Quadruple Aim

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