Population Health IT Gaining Momentum

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Source: JHU-CPHIT-Team-2013.jpg - Johns Hopkins’ Center for Population Health IT Team
Jonathan Weiner, DrPH (center) and his core team at the Johns Hopkins’ Center for Population Health IT.

The shifting landscape of healthcare reimbursement means providers must prepare for a time when they are rewarded for meeting quality objectives for their entire patient population—not just those in a clinical setting.

Payers, accountable care organizations (ACOs), integrated delivery systems, government agencies, IT companies and consumer groups all are putting the pressure on for better tools to manage population health.

Population health technologies are still in their infancy, but the industry always follows the payments, says Grace Terrell, MD, CEO and president of Cornerstone Health Care, a North Carolina-based multispecialty group that became a Medicare Shared Savings Program (MSSP) in 2012. As more providers share risk with payers, these tools will grow in sophistication and use.

A Multi-pronged Approach

As a renowned research center, Johns Hopkins University launched its Center for Population Health IT (CPHIT, pronounced “see-fit”) to meet the demand for technologies that support value-based payment models. The center focuses on the application of EHRs, mobile health and health IT tools targeted at communities and populations.

“Population health is now in vogue,” says Jonathan Weiner, DrPH, director of CPHIT, “but most [providers] have not done population health. They have focused on their patients but not their denominator.

“We’re fairly unique as we view our target as an entire community, including people without access to healthcare and technology,” he adds.

Housed in the Johns Hopkins Bloomberg School of Public Health, CPHIT brings together expertise from the school’s engineering, medicine, nursing, applied physics laboratory units and its health system. Through interdisciplinary research and industry collaboration, CPHIT hopes to build viable population health IT for the greater good. “The nexus of population health, healthcare delivery and health IT really depends on successes at CPHIT and organizations like it.”

Cutting-Edge Research

Working with four large integrated delivery systems, all of which have had EHR systems for more than a decade, CPHIT is developing real-time integrated decision support using predictive modeling analytics. The project’s goal is advancing the state-of-the-art of EHR-based, advanced predictive modeling tools for high-risk case detection and management for populations actively engaged in outpatient care, as well as populations with select chronic conditions.

The initiative expands upon the Johns Hopkins ACG [Adjusted Clinical Group] System, which has been performing risk measurement and case-mix categorization for more than 25 years, and measures accuracy and fairness in evaluating provider performance, identifying patients at high risk, forecasting healthcare utilization and setting equitable payment rates. 

The new project, known as the “e-ACG” project, is a collaboration between Johns Hopkins School of Medicine and the Department of Computer Science. It incorporates EHR elements such as vital signs, lab values, cardiovascular data, clinical notes and patient reports such as health risk assessment and functional status surveys. 

“We are trying to blend clinical data with the claims-based predictive modeling environment. It’s an exciting project in the next couple of years,” Weiner says.

In other research, CPHIT is partnering with CRISP (Chesapeake Regional Information System for our Patients), Maryland’s state health information exchange (HIE), to develop real-time predictive modeling to identify patients at high risk of readmission. The HIE returns the organization’s data, allowing them to develop warnings about who is most likely to be readmitted.

The center also is pursuing computer science methodologies to advance the application of non-structured data and big data to population health interventions. More than half of the information within an EHR is unstructured, Weiner says, so better methods for capturing and sorting data will make it more actionable.

Johns Hopkins engineers, who primarily work on Department of Defense technologies, are transferring their knowledge of natural language processing for use in the school’s health system. The engineers are mining clinical notes to help the obstetrics department, health plans and public health agencies do a better job of identifying high-risk mothers early in their pregnancy. “It’s classic population health, sending out nurses to moms who are at higher risk than others,” Weiner says.

ACO Forerunners

While CPHIT seeks to