Quantitating and assessing interoperability between electronic health records

Elmer V. Bernstam, Jeremy L. Warner, John C. Krauss, Edward Ambinder, Wendy S. Rubinstein, George Komatsoulis, Robert S. Miller, James L. Chen

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

Objectives: Electronic health records (EHRs) contain a large quantity of machine-readable data. However, institutions choose different EHR vendors, and the same product may be implemented differently at different sites. Our goal was to quantify the interoperability of real-world EHR implementations with respect to clinically relevant structured data. Materials and Methods: We analyzed de-identified and aggregated data from 68 oncology sites that implemented 1 of 5 EHR vendor products. Using 6 medications and 6 laboratory tests for which well-accepted standards exist, we calculated inter- and intra-EHR vendor interoperability scores. Results: The mean intra-EHR vendor interoperability score was 0.68 as compared to a mean of 0.22 for inter-system interoperability, when weighted by number of systems of each type, and 0.57 and 0.20 when not weighting by number of systems of each type. Discussion: In contrast to data elements required for successful billing, clinically relevant data elements are rarely standardized, even though applicable standards exist. We chose a representative sample of laboratory tests and medications for oncology practices, but our set of data elements should be seen as an example, rather than a definitive list. Conclusions: We defined and demonstrated a quantitative measure of interoperability between site EHR systems and within/between implemented vendor systems. Two sites that share the same vendor are, on average, more interoperable. However, even for implementation of the same EHR product, interoperability is not guaranteed. Our results can inform institutional EHR selection, analysis, and optimization for interoperability.

Original languageEnglish
Pages (from-to)753-760
Number of pages8
JournalJournal of the American Medical Informatics Association : JAMIA
Volume29
Issue number5
DOIs
StatePublished - 1 May 2022
Externally publishedYes

Keywords

  • common data elements
  • data aggregation
  • data management
  • data warehousing
  • electronic health records
  • information storage and retrieval

Fingerprint

Dive into the research topics of 'Quantitating and assessing interoperability between electronic health records'. Together they form a unique fingerprint.

Cite this