Background The Centers for Disease Control and Prevention (CDC) produced a 72-page document titled “U.S. Selective Practice Recommendations for Contraceptive Use” in 2016. This document contains the medical eligibility criteria (MEC) for contraceptive initiation or continuation based on a patient's current health status. Notations such as Business Process Model and Notation (BPMN) and Decision Model and Notation (DMN) might be useful to model such recommendations. Objective Our objective was to use BPMN and DMN to model and standardize the processes and decisions involved in initiating birth control according to the CDC's MEC for birth control initiation. This model could then be incorporated into an electronic health records system or other digital platform. Methods Medical terminology, processes, and decisions were modeled in coordination with the CDC to ensure correctness. Challenges in terminology bindings were identified and categorized. Results A model was successfully produced. Integration of clearly defined data elements proved to be the biggest challenge. Conclusion BPMN and DMN have strengths and weaknesses when modeling medical processes; however, they can be used to successfully create models for clinical pathways.

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UNSTRUCTURED There are over 8 million central venous access devices (CVAD) inserted each year, many of which in patients with chronic conditions who rely on central access for life-preserving therapies. CVAD-related complications can be life-threatening and add tens of billions of dollars to healthcare costs, while their incidence is most likely grossly mis- or under-reported by medical institutions. In this communication, we review the challenges that impair retention, exchange, and analysis of data necessary for meaningful understanding of critical events and outcomes in this clinical domain. The difficulty is not with data extraction 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 is not recorded, or falsely recorded, at least in part because policy, payment, penalties, and workflow burden discourage completeness and accuracy. We provide a roadmap for development of healthcare 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 U.S. 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 lifecycle.

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.