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

Using your EHR for Population Health Management

A Cross-reference Tool

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Health centers are interested in managing population health but may not have the budget needed to purchase specialty suites. This tool will guide health centers in leveraging the “built in” functionality of certified EHRs to perform PHM functions by mapping the native PHM functionality available in the common certified EHRs used by health centers.  The aim is to help health centers to understand where to start in implementing PHM using what they already have available to them.

Predictive Analytics: An Overview for Community Health Centers

from Capital Link

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Capital Link has published this overview of predictive analytics for community health centers.

Developed and made available by Capital Link and the National Association of Community Health Centers (NACHC), this overview provides health centers with a definition of predictive analytics, its history and development, the data and resources needed to predict a patient’s future behavior, and how health centers can begin utilizing it. It also includes specific examples of organizations that have successfully used predictive analytics. This study was supported by the Health Resources and Services Administration. 

Community Health Assessment for Population Health Improvement

from CDC

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Targeting care and effective planning for improving population health requires good information about current health status and the factors that will influence that health status.  This report identifies the metrics – the population health outcomes and important risk and protective factors – that, taken together, can describe the health of a community and drive action. Selection of these metrics is  based on a systematic review of professional and academic judgment over the past three decades.  

The Power of Demographic Data

From the Center for Care Innovations

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This features a presentation entitled “The Power of Demographic Data:  Leveraging Demographic Data to Increase Access in a Data-Driven Culture”,  and is one of five presenting use cases for analytics.  It was recorded during the Safety Net Analytics Program of 2015 that discusses real-world applications of analytics emerging under new payment models. The use cases presented are health-center specific and provide examples of validating and applying UDS data entities.  The discussion includes ways to gather demographic data from patients, how to collect usable data, extracting actionable data and the implications of demographic variation on care and information delivery.

In the Incubator: Using Social Determinants Data

From the Center for Care Innovations

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This mini-case study describes Petaluma Health Center, a Federally Qualified Health Center’s approach to incorporating social determinants data into their daily workflows.  They then used Tableau visualization to represent the data to enable them to target interventions in the community.  Petaluma’s lessons learned and next steps are discussed, and a link to the full, detailed case study is provided.

Ask & Code: Documenting Homelessness Throughout the Health Care System

A National Health Care for the Homeless Council Webinar

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This webinar complements our recent policy brief and will discuss how the ICD-10-CM code for homelessness (Z59.0) has been implemented at a Health Care for the Homeless grantee in Colorado, and how a hospital system has instituted a housing status screening tool in Pennsylvania. Finally, we’ll hear from a leading managed care entity about why Medicaid plans need to have this information and see preliminary results from a pilot project in Texas using the Z59.0 code to identify homelessness among Medicaid beneficiaries.



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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