Insights to Inspire 2022: The Journey Continues – Resources

Image
Informatics the Journey Continues logo showing the five areas that make up the series: Data Completeness, Data Quality, Data Standardization, Process Improvement, and Resources

Public Health Imperative Drives Research Consortium’s Shift to Critical COVID-19 Tool 

Images of Paul Drawz, MD, MHS, MS, and Steve Johnson, PhD

A consortium among Minnesota health-care providers, organizations, and the University of Minnesota designed to use electronic health record data for research and quality improvement quickly shifted into a vital surveillance tool in tracking the COVID-19 pandemic.  

The University, Hennepin Healthcare – a CTSI hub partner – and 11 health organizations created the consortium in March 2020 to use EHR (electronic health record) data for chronic kidney disease, diabetes, hypertension, cancer, and cardiovascular disease. With the pandemic’s arrival, though, it became a public health imperative that the group use its data to monitor COVID statewide.  

Since March 2020, the Minnesota EHR Consortium has conducted COVID syndromic surveillance along with vaccine-distribution and vaccine-effectiveness monitoring. The group’s statistics on COVID-19 testing, infections and hospitalizations aids the Minnesota Department of Health and health systems in improving their models to plan for infection surges and to appropriately allocate resources.  

Reports identify COVID hotspots, assess testing and treatment capacity, and fill gaps in state data. They also identify any marked differences in testing results by race, language and neighborhood income, as well as asymptomatic COVID positive rates. 

The EHR Consortium is vital to tracking COVID efforts of the state – and of the nation. As noted in a recent Politico article (Dec. 20, 2021), two years into the pandemic, the Centers for Disease Control continues to struggle with data collection and relies on data from state health departments across the country. 

What’s more, the group has achieved incredibly fast data-delivery turnaround times, as results are delivered from the prior week. The group has the capability to refresh its data daily in the future. 

The Keys to Success 
Central to the consortium’s successful collaboration is its decentralized structure based on a distributed data model in which each entity shares summary-level results but maintains control of its own data. Participation in the group is completely voluntary.  

The Consortium also spent time and effort building trust among the group through face-to-face teleconference meetings and by gaining group consensus before taking on projects. Results are presented to all the participating organizations during weekly meetings, where each entity is afforded a voice and a forum for discussion. 

 

​​​​Teal line“There's a sense that we are collaborating as equals, and the distributed data model made this possible.”

Paul Drawz, M.D., M.H.S., M.S., Associate Professor of Medicine, Division of Nephrology and Hypertension, University of Minnesota.  

 

Steve Johnson, Ph.D., Assistant Professor and Director of the Division for Informatics Innovation Dissemination in the Institute for Health Informatics at the University of Minnesota, said, “Previous efforts were, ‘if we build it, they will come.’ Prompted by COVID, we had to do something. Everybody was willing to take that first step and just start. Much attention was paid to making sure different sites had different responsibilities early on so that it truly could be seen as a shared effort.” 

From a COVID Data Model to a Common Data Model 
Within the next two years, the goal is to evolve from the current simple COVID-focused data model to a richer OMOP common data model, which will not only further enhance consortium ability to support research beyond COVID, but also fill in current statewide data gaps. Code provided to health systems will enable them to identify outliers, such as patients who are not getting guideline-recommended care or providers who are not performing optimal patient care.  

Going forward, following COVID, the Consortium’s work will include its original purpose of utilizing EHR data for research and for improving the care of other diseases. Utilizing the relationships developed through its COVID experience, the group will look at disparities and inequities across a range of diseases, such as kidney disease, diabetes, hypertension, cancer or the effects of long COVID. 

“The CDC has a map of the prevalence of chronic kidney disease and hypertension across the country,” added Drawz. “If you look at their estimate across the Twin cities, it is almost the same across the whole area. But if you look at the data we have, there are vast differences from one neighborhood to another. That is the type of data that we can provide – and that other people who collaborate like this could provide – that is not available anywhere else.” 

Lessons Learned 

  • To be successful, similar consortiums should focus on a specific issue or project, such as an inequity in a chronic condition – one that is viewed as a community’s public health imperative and not something that will benefit only one institution. 

  • To best foster collaboration, CTSAs should play a supportive role as opposed to a leading one. 

  • Building trust is essential, especially when working with often-competing entities. For example, health systems need to feel comfortable to serve as an active participant rather than simply a supporter of an effort through a Data Use Agreement.  

Paul Drawz and Steve Johnson will share a more in-depth description of their program during their webinar on Tuesday March 22nd at 3:00 PM  Eastern Time. Register for this webinar to hear how the University of Minnesota created a consortium that became a public health imperative to monitor COVID-19 statewide.