Quantitating and assessing interoperability between electronic health records

Author:

Bernstam Elmer V12,Warner Jeremy L3,Krauss John C4,Ambinder Edward5,Rubinstein Wendy S6,Komatsoulis George6,Miller Robert S6ORCID,Chen James L7

Affiliation:

1. School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, Texas, USA

2. Department of Internal Medicine, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, Texas, USA

3. Vanderbilt University Medical Center, Nashville, Tennessee, USA

4. University of Michigan Medical School, Ann Arbor, Michigan, USA

5. The Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, USA

6. CancerLinQ LLC, American Society of Clinical Oncology, Alexandria, Virginia, USA

7. Division of Medical Oncology and Department of Biomedical Informatics, The Ohio State University, Columbus, Ohio, USA

Abstract

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.

Funder

National Center for Advancing Translational Sciences

Cancer Prevention and Research Institute of Texas

Publisher

Oxford University Press (OUP)

Subject

Health Informatics

Reference13 articles.

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