Background and Significance: Pragmatic approaches to the conduct of clinical trials would markedly reduce the burden on patients and the clinical research ecosystem. Centralized capture and ascertainment of events is a major pragmatic approach to replace local event capture and event adjudication by independent committees. An ongoing phase 4 clinical trial sponsored by the National Heart, Lung, and Blood Institute, INfluenza Vaccine to Effectively Stop CardioThoracic Events and Decompensated heart failure (INVESTED), in which the Veterans Affairs (VA) Network of 34 sites led by the PI is participating, offers an ideal opportunity to develop appropriate methodology to improve electronic medical record (EMR)-based centralized strategies for endpoint capture and to compare central versus traditional event capture methodology.
We aim to test the hypothesis that centralized endpoint capture strategies are comparable to traditional methods of event ascertainment utilizing the following specific aims:
Specific Aim 1. Develop algorithms for capture of major clinical trial endpoints. We will develop methodology to capture following clinical trial endpoints from the national VA databases: all- cause mortality, cardiovascular (CV) death, cardiopulmonary hospitalizations (CV -heart failure, cerebrovascular events, myocardial infarction/acute coronary syndrome, arrhythmias; and pulmonary - pneumonia, chronic obstructive pulmonary disease/chronic bronchitis, pulmonary embolism, asthma, acute respiratory failure), and adverse reaction to vaccine (Guillain-Barre syndrome, Bell's palsy, encephalitis/myelitis, optic neuritis, Steven-Johnson syndrome, toxic epidermal necrolysis), of enrolled veterans by central methods. For event capture, we will identify endpoints from multiple VA and non-VA data sources and use an iterative method to refine algorithms and will test validity of algorithms by independent physician review and adjudication of medical records.
Specific Aim 2. Compare the event capture rate between central and traditional methods of endpoint capture and ascertainment. Outcomes (projected) and Anticipated impact: We will compare event capture rates of central and traditional methods for each of the major clinical trial endpoints described in Specific Aim 1 at the event level during each consecutive influenza season and over the entire trial period. We will develop methods to accurately capture major clinical trial endpoints using algorithms that will be easily applicable to any EMR system. We also expect to find that EMR based event capture strategies are non- inferior to traditional methods. This project will also provide significant new data about how to streamline central approaches to achieve real-time capture and ascertainment of endpoints in clinical trials. This project is highly significant since it will develop centralized event capture methods that will reduce the costs of conducting clinical trials as well as the burden on patients, investigators, and the clinical research ecosystem, and make the VA a world leader in innovative approaches to clinical trials.
A major opportunity to reduce the burden on veterans participating in clinical research and the clinical research ecosystem is to develop methods to capture events during the course of a clinical trial using electronic medical record (EMR)-based central approaches, which could replace the costly, time-consuming and burdensome traditional approach involving local capture by personal and telephone contact with participants and event adjudication by independent committees. In this project, we will develop algorithms that will enable timely, accurate, and complete capture of events from EMR and then compare the strategy of EMR-based event capture to the traditional methods employed, in an ongoing clinical trial. If EMR-based approaches to event capture and ascertainment are comparable to traditional methods, the results of this project will enable a paradigm shift in the approach to clinical trials and make the Veterans Affairs Healthcare System a world leader in innovative clinical research.
