Cochrane Collaboration

The Cohrane Collaboration is an organised effort to establish a database for reviews in medical intervention to ascertain efficacy of those interventions. Interventions are specifically those measures that health care professionals take to alleviate illness and discomfort. The collaboration was initiated by Archie Cochrane. Cochrane’s Rock Carling Lecture, “Effectiveness and Efficiency", given in 1972, is recognised as the initial impetus for the Cochrane Collaboration. In his Rock Carling Lecture, Cochrane delineated the “importance of randomised controlled trials (RCTs) in assessing the effectiveness of treatments”. His work subsequently led to the establishment of the Cochrane Collaboration, a global effort locating, assessing and synthesising RCTs in all areas of medicine.

Cochrane’s rationale for this project can be summed up in this excerpt"

"It is surely a great criticism of our profession that we have not organised a critical summary, by specialty or subspecialty, adapted periodically, of all relevant randomised controlled trials".

Problem and Solution

Problem

The Collaboration database is designed to address the overwhelming amount of information that is being produced by clinics and research facilities. At the beginning of the second quarter of 2007, PubMed, one of the largest medical sciences databases on Earth, had more than 16 million citations for research journals dating back to the 1950s from 33,360 journals of which more than 7000 articles were indexed for ‘hemochromatosis’, 10,790 for ‘autism’, 47,418 for ‘spinal trauma, 575,965 for ‘virus’, and 1,059,081 for ‘gene’.

Reading, evaluating and incorporating best practices from this amount of material is unmanageable.

Solution

The Collaboration is designed allow the use of systematic reviews of the available research to:

• efficiently integrate valid information and provide a basis for rational decision making;
• establish where healthcare is consistent or varies significantly;
• allow the application of research results across populations, settings, and small differences in treatment;
• limit bias (systematic errors);
• reduce chance effects,
• provide more reliable results upon which to draw conclusions and make decisions;
• use Meta-analysis to summarise the results of independent studies for more precise estimates of the effects of healthcare (rather than those derived from the individual studies.