Imagine that you are a researcher trying to identify the number of people receiving a certain treatment for a medical condition. As you explore the available data, you quickly discover that there are many data sources to choose from. The two most commonly used types of data are electronic health record data and claims data. Electronic health record data can tell you what happened when patients visited their doctors, such as what conditions they were tested for, the results of those tests, and what medications were prescribed. Claims data, however, can tell you what an insurance provider actually paid for, which can tell you whether the patient filled their prescription after his or her diagnosis of the specific medical condition. Both data sources are critical to research, but neither, on its own, offers a complete picture of the patient history. To increase the likelihood of identifying the appropriate people and answer your question, you need both.
PCORnet + Sentinel: What’s the Value of a Linkage Infrastructure?
Unfortunately, due to differences in how claims data and electronic health record data are categorized and coded, it is difficult to combine these data for clinical research. Two pilot projects funded through a public-private partnership with the Patient-Centered Outcomes Research Institute (PCORI), the U.S. Food and Drug Administration (FDA), and the Regan-Udall Foundation (participating in an advisory capacity) tried to solve this challenge by creating an infrastructure that links PCORnet—one of PCORI’s most innovative initiatives—and the FDA’s Sentinel program. This article, the first in a two-part series, will focus on one of those pilots, which was an effort to better understand and monitor the natural progression of the Zika virus.
Although PCORnet and Sentinel are both large distributed research networks, PCORnet mostly contains the clinical data that comes from electronic health records generated when people visit their doctor, while Sentinel mostly uses the claims data produced by the billing and paying for health services to monitor the safety of regulated medical products. As we noted above, clinical and claims data offer different, but equally valuable insights that, when combined, can offer a more complete picture of patient care.
Congenital Zika Project with OneFlorida
Researchers used this partnership to better understand the natural progression of the mosquito-borne Zika virus across Florida last year.
The challenge: While most people infected with the Zika virus will only experience mild or even nonexistent symptoms, women who are infected with Zika during pregnancy are at risk of having babies that suffer from a birth defect of the brain called microcephaly and other severe brain and birth defects. While Sentinel had been tracking Zika surveillance for some time, researchers believed that linking to the PCORnet infrastructure could enhance those efforts. The project team worked to develop a strategy for tracking the number of babies born with microcephaly within the OneFlorida partner network. Its specific aim was to not only detect outbreaks, but also to understand the natural progression of congenital Zika syndrome.
The process: The study team started by identifying available electronic health record data elements in the PCORnet Common Data Model that can contribute to Zika surveillance. Then they coordinated with Sentinel to develop a shared set of diagnosis and procedure codes that would allow them to identify infants with microcephaly who have signs or symptoms consistent with congenital Zika syndrome.
“By coordinating our coding,
we were able to help Sentinel
and PCORnet speak the same language.
Bill Hogan – Co-Principal Investigator, OneFlorida
“By coordinating our coding, we were able to help Sentinel and PCORnet speak the same language,” said Bill Hogan, co-principal investigator for OneFlorida. “The idea was for the public health data from Sentinel and the electronic health record data from PCORnet to work seamlessly together.”
The result: The team found that many, but not all, data elements needed for enhanced congenital Zika syndrome surveillance are available and easily extracted from electronic health records. The data review also found that head circumference, a standard data point found in electronic health records, can indicate microcephaly with 70 percent accuracy.
“There is every indication that this model has great potential to bridge health care and public health systems to serve as a much-needed source of more complete public health information,” said Hogan.
This article is first in a two-part series on PCORnet’s data linkage projects. Learn more in Part 2.
PCORnet, the National Patient-Centered Clinical Research Network, is an innovative initiative of the Patient-Centered Outcomes Research Institute (PCORI). The goal of PCORnet is to improve the nation’s capacity to conduct clinical research by creating a large, highly representative network that directly involves patients in the development and execution of research. More information is available at www.pcornet.org.
The Patient-Centered Outcomes Research Institute (PCORI) is an independent nonprofit organization authorized by Congress in 2010. Its mission is to fund research that will provide patients, their caregivers, and clinicians with the evidence-based information needed to make better-informed healthcare decisions. PCORI is committed to continuously seeking input from a broad range of stakeholders to guide its work. More information is available at www.pcori.org.