Newton workshop to build data management skills and network for early career researchers
by Aileen SheehyResponding to the growing mandate for researchers to share their clinical data, WWARN is joining with partners to host a 3-day workshop in January sponsored by the British Council’s Newton Researcher Links Programme in order to develop the skills and network needed to produce high quality data capable of maximising the impact of initial findings.
Scoping available resources and tools - WWARN survey
by Clifford BandaScoping available resources and tools used by investigators to set up and conduct malaria clinical trials in low and middle income countries within malaria endemic settings. Participate in the survey.
Epidemic curves are an important component of the public health and global health toolbox. Learn more about creating and interpretting them.
Become a Cochrane citizen scientist. Anyone can join their collaborative volunteer effort.
Around half of the clinical trials done on medicines we use today are not published; a tragic truth that needs to be changed.
PAPER - an assessment of how adverse events from clinical trials are reported in published papers
by Global PharmacovigilanceA recently published paper in PLOS Medicine has investigated how adverse event data from clinical trials are summarised and consequently reported in published papers.
Join us in Oxford on the 25th of April to mark World Malaria Day 2016 at a series of talks and a panel discussion. The speakers will present their latest projects and help us to understand the unique and interconnected findings of their research.
Recent calls have been made for rapid and responsible sharing of research data in public health emergencies and outbreaks.
Building on the concept of rapid learning health systems, Dr. Peek’s seminar focuses on the use of health information technology to address epidemiological and public health questions and to accelerate the translation of research findings to clinical practice.
Healthcare associated infections (HAI) are of important concern in patient care. This talk discusses Visual Analytics techniques which have been developed to help detect, monitor, analyse and understand trends, clusters and outbreaks of HAI.
New guidelines help researchers undertaking systematic reviews and IPD meta-analyses to report their findings in a full and transparent manner.
Anders Björkman is Professor of Infectious Disease at the Karolinska Institute. In this video, Anders talks about how the efficacy of antimalarials is a major obstacle in the path towards full malaria elimination.
Professor Mike English explains how KEMRI-Wellcome are ''working with government to generate patient level data from a network of Kenyan hospitals as a platform for research'.
In celebration of Global Health Trials' fifth birthday (May 11th 2015) Professor Trudie Lang, Principal Investigator of the programme, talks to us about why Global Health Trials was started, why people should share their experience, and what the future holds.
Bayesian Clinical Trials (Nature Reviews Article)
by Donald A. BerryAn introduction into and overview on the mathematics and practice of Bayesian (adaptive) clinical trials.
Technology issues for research in remote areas/developing regions
by Mike Workman - Senior ContributorResearchers can often be tripped up by issues they encounter in developing regions and remote areas. Although no definitive answers are provided (there are just too many options and unknowns), the following issues should be considered when planning such a trial.
Powerpoint slides representing a comprehensive overview of some issues surrounding data management, including an overview of data management, the issue of coding, and regulations and guidelines. NEW ADDITIONS AUGUST 2013: Code of Federal Regulations part 11 - Guidelines on how to implement
Research misconduct is a global problem as research is a global activity. Wherever there is human activity there is misconduct, but we lack reliable data on the extent and distribution of research misconduct. This PLoS paper seeks to illustrate some examples of researsch misconduct in LMICs.
In this article, the authors illustrate five basic statistical concepts that can significantly impact the interpretation of the medical literature and its application to the care of patients, drawing examples from the vaccine literature: (i) consider clinical and statistical significance separately, (ii) evaluate absolute risks rather than relative risks, (iii) examine confidence intervals rather than p values, (iv) use caution when considering isolated significant p values in the setting of multiple testing, and (v) keep in mind that statistically nonsignificant results may not exclude clinically important benefits or harms.
Electronic Source Data in Clinical Investigations by FDA
by Yves ClaeysThis is a nice guidance document on principles in electronic data capture from Industry perspective (FDA)
Transnational Working Group on Data management of the ECRIN, the European Clinical Research Infrastructures Network, present recommendations for quality and harmonisation for data management. In addition good data management practices in general are identified.
Clinical Data Management: Current status, challenges and future directions from industry perspectives.
by Harry van LoenCould an Open-Source Clinical Trial Data-Management System Be What We Have All Been Looking For?
by The Editorial TeamThis publication discsusses whether or not open-source clinical trial data management will improve the likelihood that good clinical trials are conducted in resource-constrained settings.
A range of downloadable templates and tools for Clinical Research, including monitoring checklists, budget spreadsheets, informed consent forms, SOPs and so on.
This article explains the process of data management operations within clinical trials from start to finish.
An example of a academic research centre resolving the issue of clinical trial data management Peer reviewed by members of the data management expert committee for this programme.
Good data management practices are essential to the success of a trial because they help to ensure that the data collected is complete and accurate. This article contains some tips to help you get started with data management.