Progress Towards Interoperability of Health Data?

I know I’m not alone in saying it can be a hassle to transfer healthcare information between providers, even within the same system — formats differ, critical records are incomplete, and many times a fax machine is used. The emergence of artificial intelligence and machine learning (AI/ML), cloud computing, and other technological advancements in the last few decades creates opportunities to address those issues and leverage data in new and innovative ways that advance medical breakthroughs.

To realize those benefits, though, it’s imperative that data — whether deployed in a clinical setting, used to inform public health policy, or to develop next-generation therapeutics — are not only easy to transmit but arrive in a form that’s platform agnostic. Any hiccup in that transfer means breakthroughs are more costly; care is delayed; and, worse still, may result in negative health outcomes for patients. We’ve made tremendous progress in the U.S. toward interoperability of health data, but more can be done.

 I’m thrilled and proud to share that the Deloitte Federal Health – U.S. Food and Drug Administration (FDA) SHIELD Lab Interoperability team’s co-authored article assessing the interoperability of laboratory data as it moves between systems was recently published in the Journal of American Medical Informatics Association (JAMIA) (read article here: https://academic.oup.com/jamia/article/29/8/1372/6592172)

The team worked with our colleagues at FDA to conduct an evaluation of five healthcare systems, finding that when data were moved from a laboratory analyzer to a laboratory information system, they maintained only slightly more than half (59%) of their integrity. Patient outcomes depend on accurate and timely data, and the team’s findings drive home the clear need to redouble efforts in the public- and private-sectors to ensure healthcare data can be shared seamlessly. SHIELD, a public-private collaborative, aims to build, implement, and support a comprehensive solution that addresses the interoperability of laboratory health data across the nation.

Congratulations to the entire team! Success for the publication was led by Raja Cholan and supported by, Andrew Sills, Liz Korte, Khalil Appleton, Natalie Scott, Peyton Marion, Alicia Bracco, Taima Gomez, John Stinn, Cynthia Kossally, and Greg Rehwoldt.

Source: Raja A Cholan, Gregory Pappas, Greg Rehwoldt, Andrew K Sills, Elizabeth D Korte, I Khalil Appleton, Natalie M Scott, Wendy S Rubinstein, Sara A Brenner, Riki Merrick, Wilbur C Hadden, Keith E Campbell, Michael S Waters, Encoding laboratory testing data: case studies of the national implementation of HHS requirements and related standards in five laboratories, Journal of the American Medical Informatics Association, Volume 29, Issue 8, August 2022, Pages 1372–1380, https://doi.org/10.1093/jamia/ocac072