There are over 8 million central venous access devices inserted each year, many in patients with chronic conditions who rely on central access for life-preserving therapies. Central venous access device-related complications can be life-threatening and add tens of billions of dollars to health care costs, while their incidence is most likely grossly mis- or underreported by medical institutions. In this communication, we review the challenges that impair retention, exchange, and analysis of data necessary for a meaningful understanding of critical events and outcomes in this clinical domain. The difficulty is not only with data extraction and harmonization from electronic health records, national surveillance systems, or other health information repositories where data might be stored. The problem is that reliable and appropriate data are not recorded, or falsely recorded, at least in part because policy, payment, penalties, proprietary concerns, and workflow burdens discourage completeness and accuracy. We provide a roadmap for the development of health care information systems and infrastructure that address these challenges, framed within the context of research studies that build a framework of standardized terminology, decision support, data capture, and information exchange necessary for the task. This roadmap is embedded in a broader Coordinated Registry Network Learning Community, and facilitated by the Medical Device Epidemiology Network, a Public-Private Partnership sponsored by the US Food and Drug Administration, with the scope of advancing methods, national and international infrastructure, and partnerships needed for the evaluation of medical devices throughout their total life cycle.
Keywords: CLABSI; CRBSI; catheter; central venous access devices; clinical; development; life-threatening; medical device; patient; patient-reported outcomes; policy; registry; reliable; system; therapy.
©Andrea Iorga, Marti J Velezis, Danica Marinac-Dabic, Robert F Lario, Stanley M Huff, Beth Gore, Leonard A Mermel, L Charles Bailey, Julia Skapik, Debi Willis, Robert E Lee, Frank P Hurst, Laura E Gressler, Terrie L Reed, Richard Towbin, Kevin M Baskin. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 24.11.2023.