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You Don’t Know if You Don’t Ask

by Hope Cullen

Paper and pencil are so passé. Technology is being used in all types of studies to collect patient data in a myriad of ways. But even the simplest piece of technology is not without its challenges.

Take the humble iPad, for example. Or, in this case, take 100 iPads.

Asking, “What if?”

Using computers to collect patient data for a study can get complicated. Collecting data at 100 different sites across the U.S. and Canada can get really complicated. From study design, to ancillary supplies needed, clinical studies have countless moving parts, which can easily become a logistical nightmare if you don’t ask those “what if” questions regarding:

  • Device security and integrity
  • Patient confidentiality
  • Data breaches or compromised data
  • Shipping and receiving of data collection devices
  • Patients’ computer literacy

It was Benjamin Franklin who said, “By failing to prepare, you are preparing to fail.” Of course, he wasn’t speaking of iPads, but the gist remains the same.

Simple Steps Lead to Successful Data Collection

Imagine two iPads, each set to factory settings. One is going to a study site in California in the United States, the other is going to a study site in Québec, Canada. Vastly different time zones and languages (American English and French Canadian.) Each one has to be checked to see that it is running the latest version of the operating software. Each one must be password-protected to ensure patient confidentiality. And each one has to have the data collection software installed. Now repeat the process 98 more times. There’s lots of room for error.

Planning Up Front

When those “what if?” scenarios (no matter how obvious or outrageous they may seem) are taken into account during the planning stages, it saves countless hours of troubleshooting, problem solving, device failure and other unforeseen possible pitfalls.

Check out our latest free case study to learn how upfront planning and consideration of all possible scenarios can lead to successful data collection.

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