As a science which focuses on evidence, the decision making process of evidence medicine encounters an opportunity for development in the big data era. The starting point is shifting forward from evidence to data. The big data technology is playing an active role in evidence's collection, process and utilization. Evidence is more objective, righteous, authentic, transparent and easier to collect. Thus, to initiate evidence-based medicine research in the big data era and to structure an evidence-based medicine intelligent service platform, a full-scaled strategy should be developed in order to improve the quality of evidence. To promote the complete publicity of clinical research data, structuralized clinical data standard should be constructed. To provide a pathway to patients' follow-up data, portable and wearable monitoring devices should be popularized. To avoid risks from utilization of clinical research big data, regulations of clinical data usage should be implemented.
With the encouragement of national policy on drug and medical device innovation, multi-center clinical trials and multi-regional clinical trials are facing an unprecedented opportunity in China. Trials with a multi-center design are far more common at present than before. However, it should be recognized there still exists shortcomings in current multi-center trials. In this paper, we summarize the problems and challenges and provide corresponding resolutions with the aim to reduce heterogeneity between study centers and avoid excessive center effects in treatment. It is urgent to develop design, implementation and reporting guidelines to improve the overall quality of multi-center clinical trials.
The concept of clinical trial transparency has been promoted for more than 40 years. The act of clinical trial registration, report guidelines development, and data sharing has has been strongly pushed forward and become a common practice. The clinical trial process being the key procedure of trial operation and quality control, determines the accuracy of the results. However, the process report of clinical trials is insufficient. In this article, we summarize the importance of clinical trial process report and provide corresponding suggestions. We propose that medical journals, reporting guidelines developers and clinical trial registration platforms should work together to strengthen the process report of clinical trials and promote full transparency of clinical trials.
Data integrity, accuracy, and traceability are key elements of high-quality clinical research, as well as weak links in the promotion of clinical research transparency. How to promote data quality has become a major concern to all clinical research stakeholders. In this article, we dissected and analyzed data generation and capturing process in clinical research, and identified a key aspect in improving data quality: to promote electronic source data, especially to break the barrier between electronic health records and clinical research systems. Additionally, we summarized the experiences regarding this issue in China and overseas to propose a solution suitable for China to improve data quality in clinical research: to strengthen clinical research source data management by building clinical research source data platform and adopt common source data management process in hospitals.
This paper analyzed clinical studies, systematic reviews and clinical practice guidelines on the treatment of COVID-19 with antiviral drugs. It elaborated on the evidence ecosystems in these studies following the "efficacy, evidence-based practice, effectiveness" (3E) model that considered five elements: research hypothesis, research evidence, big data from healthcare facilities, real-world data, and real-world evidence. Finally, this paper summarized the experience in the production, transformation and application of evidence. This paper could help clinicians conduct high-quality clinical research and provide good clinical practice based on the best currently available evidence.