Blog from January, 2022

Hannah Nelson

Dell Medical School at UT is piloting an ONC-funded health IT implementation that aims to support interoperability for social services referrals. 

Dell Medical School at the University of Texas (UT) is piloting health IT that aims to enhance social services referral interoperability between clinics and service providers according to reporting from The Austin American Statesman.

The health IT seeks to help healthcare providers to make social services referrals within their EHR workflow. The agency can then notify the provider that the patient has been connected and is receiving services, or that it was unable to help the patient.

Austin nonprofit Integrated Care Collaboration is helping create the interoperability tool. People's Community Clinic, a federally qualified health center (FQHC) in Austin, and Integral Care, the mental health authority of Travis County, will pilot the technology at the beginning of 2022.

In 2023, Dell Medical School will roll out the health IT in El Paso and New Orleans to ensure it has a universal application rather than just working in Central Texas.

Anjum Khurshid, MD, PhD, associate professor and director of data integration in the department of population health at Dell Medical School, is leading the interoperability work.

"We're very excited to give our community a chance to address the needs of the underserved community," Khurshid told the news outlet. "We have to build this for those who need it the most: the underrepresented.”

On the patient side, Dell Medical School is building an app that will allow patients to log into all their patient portals in one place, officials said. This tool will allow patients to view all of their patient portal information, including social services referrals.

Officials noted that researchers are designing the health IT to minimize clinician burden by eliminating the need to fill out the same information on multiple forms repeatedly. The clinic will be able to send all of the patient's information to multiple social services providers.  

Khurshid said that ultimately, researchers want the tool to be scalable and standardized to any community that wants it.

The ONC funded the project with a $998,118 grant through its 2021 Leading Edge Acceleration Projects (LEAP) in Health IT program.

Erin McNemar

Data analytics can assist population health management in improving patient outcomes, enhancing care management, and address social determinants of health.

Population health management has become an important method for improving community health.  

As the population health management market continues to develop in the healthcare space, systems must gather data from multiple sources, apply analytics to the data, and manage the care for the population. 

The health management method relies on data analytics to identify populations in need of care, measure the care provided to those populations, and deliver care to the correct people.  

The process of population health management begins by gathering key demographic and clinical data about patients, often from electronic health records.  

Through data analytics and population health management, providers can improve patient outcomes, enhance care management, and address social determinants of health.  


To best serve a group of individuals, providers and physicians must utilize data. Big data is often used to address population health concerns to assist large communities of people.  

In a panel covered by HealthITAnalytics, Jefferson Health’s medical information officer Bracken Babula explained how understanding patient metrics and risk scores development is critical to the data collection process.  

“Some of the things that we’re trying to start figuring out how to use are risk scores that might pull a number of different metrics from all over the system. Basics like age, gender, insurance, and more complicated things like certain past medical history and lab values. We can then pull that all into a broader overview of the patient, with the idea being that you can then target your outreach,” Babula said. 

Through data analytics, medical professionals can gain insights into patient needs and allocate resources to those who may need them more, improving care management. 


By implementing population health management strategies and data analytics, providers are replacing the “one size fits all” care mentality to deliver value-based care

The purpose of value-based care is to standardize the healthcare process by enhancing the patient experience, the health of patient populations, and the cost of care. Through data analytics, providers can assess which processes are the most effective methods for wellness and prevention within value-based care models.   

According to Cleveland Clinic, “Prevention of health (through quitting smoking, dietary and lifestyle changes, exercise, etc.) reduces the need for expensive tests, procedures, and medications. You’re staying well cuts healthcare costs for everyone.”  

With population health management, organizations can consider physical and social determinants of health that may impact individuals and focus on “well care” rather than waiting for a patient to become ill.   


Increasingly, data analytics and population health management are being used in work with social determinants of health. At Stanford Children’s, researchers are collecting data from patients to better understand environmental factors that could influence an individual’s health. 

“The one huge aspect of this that we’re looking at Stanford Children’s is around the social determinants of health. Understanding what are the conditions, beyond just the typical things you collect in a physician visit. Is there domestic violence or food insecurities, or things like that, that really would ultimately affect the patient’s health down the road and may have different interventions than a typical physician visit?” revealed Stanford Children’s chief analytics officer Brendan Watkins. 

Jefferson Hospital also studied social determinants of health regarding the COVID-19 vaccine. The hospital used metrics called the social vulnerability index and the community need index to assess and target where the vaccines should go. 


As data analytics continues to grow in the population health management space, Geisinger director of machine learning Abdul Tariq told HealthITAnalytics that she envisions consumer health informatics expanding not only in healthcare but also in the tech and provider world. 

“As more and more people get these wearable devices like Fitbit, Apple Watch, that data will start getting captured, then there will be a market that will open up where technology companies will start providing some of these insights that traditional health systems have provided,” Tariq said. 

“With that regulation, I’m sure there will be policy enactments that will change how providers deliver care. Then, eventually, the policy will shift how providers, systems, get into this space, and what that means.” 

With wearable devices, there is an opportunity for providers to access that data to improve patient outcomes. Through data analytics and population health management, systems can identify populations in need, stratify risk, and track patient progress.