Harnessing clinical laboratory data in a way that allows health professionals to respond to health threats in real-time has long been a goal of the healthcare industry, but one that thus far has eluded its grasp.
Lack of standardization and interoperability has hindered efforts to share data in a way that improves clinical decision making in real-time. These shortfalls have been exacerbated during the COVID-19 pandemic as state and local health departments have scrambled to clean up and analyze laboratory data that are sometimes submitted by fax or even through the postal service.
Over the past year, a public-private partnership that was developed 6 years ago to improve data standardization and interoperability kicked into high gear, largely as a result of the pandemic. The Systemic Harmonization and Interoperability Enhancement for Lab Data (SHIELD) began with a series of government workshops and has since evolved into a 70-organization joint operation, involving federal agencies, IVD organizations, coding groups, and medical associations, including AACC.
“The impetus behind SHIELD first and foremost is to improve patient safety related to the laboratory and to improve data on COVID-19,” said Gregory Pappas, MD, PhD, associate director for national surveillance at the Food and Drug Administration’s Center for Biologics Evaluation and Research and a member of SHIELD. “We need to improve the data coming out of labs. Right now, there are subtle differences in coding and no standardized way to apply them. Currently, public health agencies must perform a lot of manual curation or clean up data to use it. This lack of interoperability is a major barrier to improving healthcare.”
While health data coding standards such as LOINC and SNOMED exist, there is no authoritative source for harmonization, application, and use of those codes. SHIELD hopes to fix that. According to Pappas, electronic health record (EHR) vendors do not generally offer terminology services as part of their package, which often means that healthcare staff must perform manual mapping to identify codes. Standardizing application of laboratory codes will remove that manual component and speed up analysis of lab data, which in turn can allow public health agencies to move quickly in response to an emerging health threat.
Evidence collected as part of routine clinical care (EHR, laboratory data, and claims data) – called real-world evidence (RWE) – can fulfill a wide array of evidentiary needs for medicine, from quality assurance to regulatory decision making, Pappas noted. Comprehensive interoperability, such as that used in international banking and online shopping, could have tremendous benefit for medicine, he said.
“But this vision has been elusive because of lack of interoperability,” Pappas said. “Clinical data is siloed, health IT systems are incompatible, and proprietary software makes health information difficult to exchange, analyze, and interpret.”
Barriers to interoperability include a lack of standardized test definitions, having unsynchronized test catalogs, not identifying test names using LOINC, not recognizing challenges and pitfalls associated with patient identifiers, and assuming that EHRs can properly depict complex reports. Laboratory data, which tends to be highly digitized, is a logical first target for interoperability, Pappas noted.
“Laboratory data represent highly valued information that can be considered low-hanging fruit and are squarely within the realm of semantic interoperability,” he said.
In May 2021, the SHIELD partnership began work on a 5-year strategic plan, which leaders expect to announce in November. The plan will define the project’s goals and the steps for accomplishing them. While SHIELD hopes to eventually have all 300,000 of the nation’s clinical laboratories on board with lab data interoperability, it will take some time to get there. This is another reason AACC is using its resources and influence to advance progress on SHIELD.
“We’ll start with pilot projects where we think we can have some early success,” Pappas said. “We need the government to use carrots and sticks, so we are hoping for some mandates from government agencies. We are also proposing a small grants program, along with training programs. We plan to take a multi-faceted approach to getting this done.”
AACC is working closely with SHIELD and its partners on the goal of achieving data interoperability, something that dovetails nicely with AACC’s position on data analytics and laboratory medicine. In a July 2021 position statement, AACC said it supports efforts within the healthcare community to better utilize the vast amounts of clinical data to improve patient care and lower healthcare costs. The statement further notes that the emergence of artificial intelligence and machine learning (AI/ML) technology has created new opportunities for clinical laboratories to more precisely interpret data that advance evidence-based medicine and personalized therapies.
“To fully realize the benefits of applying a big data approach to laboratory results, policymakers and the healthcare community must promote the adoption of analytics tools, incentivize data sharing between organizations, and simplify data aggregation by ensuring that test results are harmonized and reporting systems are interoperable,” AACC said in the statement.
A Tall Order
While Pappas acknowledged that achieving complete standardization and interoperability of laboratory data is a tall order, he stressed that the COVID-19 pandemic has shown just how critical this task is.
“Once we have SHIELD-compliant data, we will be able to make better decisions in the next pandemic,” he said. “Solving the semantic interoperability problem for laboratory data will reduce the time and cost of producing real-world solutions for future challenges.”