Feasibility of capturing real-world data from health information technology systems at multiple centers to assess cardiac ablation device outcomes: A fit-for-purpose informatics analysis report

Author:

Jiang Guoqian1,Dhruva Sanket S2ORCID,Chen Jiajing3,Schulz Wade L45,Doshi Amit A6,Noseworthy Peter A7,Zhang Shumin8,Yu Yue9,Patrick Young H10ORCID,Brandt Eric3,Ervin Keondae R11,Shah Nilay D12,Ross Joseph S510,Coplan Paul1314,Drozda Joseph P3ORCID

Affiliation:

1. Department of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, Minnesota, USA

2. School of Medicine, University of California, San Francisco, and San Francisco Veterans Affairs Medical Center, San Francisco, California, USA

3. Mercy Research, Mercy, Chesterfield, Missouri, USA

4. Department of Laboratory Medicine, Yale University School of Medicine, New Haven, Connecticut, USA

5. Center for Outcomes Research and Evaluation, Yale New Haven Hospital, New Haven, Connecticut, USA

6. Mercy Clinic, Mercy, St. Louis, Missouri, USA

7. Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota, USA

8. Medical Device Epidemiology and Real-World Data Science, Office of the Chief Medical Officer, Johnson & Johnson, New Brunswick, New Jersey, USA

9. Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota, USA

10. Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, USA

11. National Evaluation System for Health Technology Coordinating Center, Medical Device Innovation Consortium, Arlington, Virginia, USA

12. Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, Minnesota, USA

13. Medical Device Epidemiology and RWD Science, Office of the Chief Medical Officer, Johnson & Johnson, New Brunswick, New Jersey, USA

14. Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA

Abstract

Abstract Objective The study sought to conduct an informatics analysis on the National Evaluation System for Health Technology Coordinating Center test case of cardiac ablation catheters and to demonstrate the role of informatics approaches in the feasibility assessment of capturing real-world data using unique device identifiers (UDIs) that are fit for purpose for label extensions for 2 cardiac ablation catheters from the electronic health records and other health information technology systems in a multicenter evaluation. Materials and Methods We focused on data capture and transformation and data quality maturity model specified in the National Evaluation System for Health Technology Coordinating Center data quality framework. The informatics analysis included 4 elements: the use of UDIs for identifying device exposure data, the use of standardized codes for defining computable phenotypes, the use of natural language processing for capturing unstructured data elements from clinical data systems, and the use of common data models for standardizing data collection and analyses. Results We found that, with the UDI implementation at 3 health systems, the target device exposure data could be effectively identified, particularly for brand-specific devices. Computable phenotypes for study outcomes could be defined using codes; however, ablation registries, natural language processing tools, and chart reviews were required for validating data quality of the phenotypes. The common data model implementation status varied across sites. The maturity level of the key informatics technologies was highly aligned with the data quality maturity model. Conclusions We demonstrated that the informatics approaches can be feasibly used to capture safety and effectiveness outcomes in real-world data for use in medical device studies supporting label extensions.

Funder

Medical Device Innovation Consortium as part of the National Evaluation System for Health Technology

U.S. Food and Drug Administration

Department of Health and Human Services or the FDA

Medical Device Innovation Consortium

FDA

Publisher

Oxford University Press (OUP)

Subject

Health Informatics

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