TY - JOUR
T1 - Future of evidence ecosystem series
T2 - 2. current opportunities and need for better tools and methods
AU - Créquit, Perrine
AU - Boutron, Isabelle
AU - Meerpohl, Joerg
AU - Williams, Hywel C.
AU - Craig, Jonathan
AU - Ravaud, Philippe
PY - 2020/7
Y1 - 2020/7
N2 - To become user driven and more useful for decision-making, the current evidence synthesis ecosystem requires significant changes (Paper 1. Future of evidence ecosystem series). Reviewers have access to new sources of data (clinical trial registries, protocols, and clinical study reports from regulatory agencies or pharmaceutical companies) for more information on randomized control trials. With all these newly available data, the management of multiple and scattered trial reports is even more challenging. New types of data are also becoming available: individual patient data and routinely collected data. With the increasing number of diverse sources to be searched and the amount of data to be extracted, the process needs to be rethought. New approaches and tools, such as automation technologies and crowdsourcing, should help accelerate the process. The implementation of these new approaches and methods requires a substantial rethinking and redesign of the current evidence synthesis ecosystem. The concept of a “living” evidence synthesis enterprise, with living systematic review and living network meta-analysis, has recently emerged. Such an evidence synthesis ecosystem implies conceptualizing evidence synthesis as a continuous process built around a clinical question of interest and no longer as a small team independently answering a specific clinical question at a single point in time.
AB - To become user driven and more useful for decision-making, the current evidence synthesis ecosystem requires significant changes (Paper 1. Future of evidence ecosystem series). Reviewers have access to new sources of data (clinical trial registries, protocols, and clinical study reports from regulatory agencies or pharmaceutical companies) for more information on randomized control trials. With all these newly available data, the management of multiple and scattered trial reports is even more challenging. New types of data are also becoming available: individual patient data and routinely collected data. With the increasing number of diverse sources to be searched and the amount of data to be extracted, the process needs to be rethought. New approaches and tools, such as automation technologies and crowdsourcing, should help accelerate the process. The implementation of these new approaches and methods requires a substantial rethinking and redesign of the current evidence synthesis ecosystem. The concept of a “living” evidence synthesis enterprise, with living systematic review and living network meta-analysis, has recently emerged. Such an evidence synthesis ecosystem implies conceptualizing evidence synthesis as a continuous process built around a clinical question of interest and no longer as a small team independently answering a specific clinical question at a single point in time.
KW - Automation
KW - Clinical study report
KW - Crowdsourcing
KW - Evidence synthesis
KW - Living network meta-analysis
KW - Systematic review
UR - http://www.scopus.com/inward/record.url?scp=85082524732&partnerID=8YFLogxK
U2 - 10.1016/j.jclinepi.2020.01.023
DO - 10.1016/j.jclinepi.2020.01.023
M3 - Article
C2 - 32145369
AN - SCOPUS:85082524732
VL - 123
SP - 143
EP - 152
JO - Journal of Clinical Epidemiology
JF - Journal of Clinical Epidemiology
SN - 0895-4356
ER -