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Clinical Pipe and EHR-to-EDC

by William Aldridge, on Feb 25, 2019 1:42:57 PM

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The world we live in is constantly being disrupted and improved by technology, automation, and innovation. At a pace we never thought possible. Imagine telling an assembly line worker in a 1930s car factory, that in 70 years their jobs would be obsolete. It would be unfathomable to them. Uber, Amazon, and Spotify are now staples of modern day life, but inconceivable 20 years ago.

History is riddled with companies that failed to embrace change. Blockbuster could have bought Netflix in the early 2000s. Kodak invented the digital camera but suppressed the product out of fear it would hurt its film sales. Now, VHS tapes collect dust and film photography is a niche hobby.

Life science companies have historically been slow to adopt new technologies in their clinical trial operations. It took about 15 years for EDC to truly become mainstream, even though the benefits are clear.

Solutions which deliver higher quality data, shorten timelines AND lower costs seem too good to be true. Non-tech solutions can typically only improve two of the below, at the expense of the third.

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Innovative solutions powered by technology can now do all three… and sometimes more. Netflix delivers high-quality content, is cheap, fast and it removes commercials too. Clinical Pipe improves data quality, reduces costs, delivers data to EDC faster and reduces site burden as well.

Today’s clinical trials are far more data-heavy than those of yesteryear. For the past two decades, before the advent of Clinical Pipe, manual transcription was the go-to procedure for getting data from the Electronic Health Records (EHR) into the Electronic Data Capture (EDC). Every day, sites perform double data entry on thousands of data elements - an error-prone, costly and time-intensive process.

Clinical Pipe is an innovative tech solution, built to automate double data entry. It’s live on industry-sponsored trials, is scalable, and maps 30-70% of EHR data directly to EDC, via a proprietary mapping algorithm. This not only eliminates data entry errors and relieves site burden, but also drastically reduces the amount of Source Data Verification (SDV) needed. The result is accurate, reviewable data, faster and for less.

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Topics:EHRedcClinical Studies