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Understanding feasibility for faster clinical trials

Friday, January 1, 2016

Do you hate to be late? Most people do, but CenterWatch surveys of investigative sites show the majority have delays. A root cause is increasing eligibility cri­teria (up 58% in the last decade). It is no wonder that sites say recruit­ment is the biggest cause of delay; with more criteria, fewer patients qualify.

The fastest and most efficient sponsors are simplifying design procedures to reduce protocol complexity. One way to better study feasibility is to understand patient availability for the inclu­sion/exclusion criteria. Sponsors attempt to do so with question­naires sent to sites. Unfortunately, answers can be inaccurate. A bet­ter solution is to base feasibility on national patient counts; the data­bases are from insurance claims and electronic health records (EHR).

Insurance claims and EHR da­tabases can identify how many patients exist. The databases begin with a de-identified sample of pa­tients who have the targeted con­dition; they show the percentage of patients lost for each specification. For instance, according to Optum insurance-claims data, a sponsor would exclude 76% of adult dia­betics from a trial if it excluded all forms of hypertension. The spon­sor can then determine if that percentage is too high. EHR can assess things in a medical record not found in claims. Next, this method shows the net percentage of patients who meet all criteria; it therefore predicts if recruitment will be easy or hard, making it possible to plan resources.

An added benefit of insurance claims is that the information can be used to locate patients—or “fish where the fish are.” Claims can rank physicians and investigators on patient count. (See more in my Action Items article planned for April.)

Does your company embrace quantitative methods when deter­mining feasibility and site identi­fication? If not, these approaches are the wave of the future, and the future is now.


Written by Guest Writer Bill Gwinn. Gwinn is vice president of clinical informatics solutions at Optum, a subsidiary of United Health Group, a diversified managed healthcare company. He supports the clinical trials of new drugs with medical statistics. His expertise lies in quantitative analysis for site selection and finding patients. His prior experience includes positions at Medstat Group at Thomson Reuters, IMS Health, Schering-Plough, and Procter & Gamble. Gwinn holds an M.B.A. degree from the University of Chicago and a B.A. degree from Vanderbilt University.

This article was reprinted from Volume 22, Issue 12, of The CenterWatch Monthly, an industry leading publication providing hard-hitting, authoritative business and financial coverage of the clinical research space. The Action Items section features short columns  focusing on actionable or how-to advice from clinical trial professionals. To submit an Action Item, please contact editorial@centerwatch.comSubscribe >>

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