Frank Capra’s 1946 film, It’s a Wonderful Life, portrayed a common theme: George Bailey, like many of us, didn’t realize how fortunate he was to be living the life that he was. If you are a CRA fortunate enough to be using EDC to conduct clinical research, you too can have a fortunate life.

Hard to believe, since you are a busy CRA who is monitoring multiple sites for multiple trials, all at the same time? If you are “e-enabled”, your life consists of: 1) using the capabilities of EDC to make better use of your time; 2) enjoying increased flexibility as to when and where you do certain tasks; 3) allowing the computer to do mundane tasks for you; and 4) exploiting the EDC data to isolate potential problems before they can cause you trouble.

Let’s see how this works by looking at the wonderful life of Mike Monitor, a regional CRA, who is: 1) monitoring several sites for Study A; 2) completing and locking one site for Study B; and 3) initiating a new site for Study C. We’ll follow Mike for a week and see how he uses EDC to cope with his workload and optimize his life/work balance. (Note: If this week in Mike’s life doesn’t sound much like one of yours, it may be time to voice your concerns about how your company is using EDC.)

Monday, 9 A.M.

Cleaning data remotely. Mike’s company allocates regular office time for regional monitors, so they can review and clean data before the next site visit. Mike’s office day for this week is Monday. Mike begins by filtering the data in the EDC system to isolate all new data entered since his last cleaning session. He works his way through the data review items per his monitoring plan and raises several manual queries. He also checks for open queries and sees that nine out of ten from his last session have been answered. He reviews the answers on the nine and closes those queries. At the same time, he makes a note in the comment field of the data item with the open query, so that he can discuss this query with the site at his next visit.

Tracking site performance. Mike has set an expectation with the site that they will catch up on all data entry at least once a week. This expectation has been set during the training session and, beginning this year, is also expressed as an incentive clause in the site contracts for all new studies. Mike runs a standard report that shows the average time between a patient’s visit and the day on which the data for that visit are entered into the EDC system. An average time for each of his sites, as well as an overall average for each study, are displayed in the report. Two of his sites currently qualify for the incentive, while a third site is close to doing so. Mike makes a note in the system to discuss the incentive with this site at his next visit.

Anticipating problems. Mike also examines a list of all his queries, sorting them by eCRF form and then by data item. By doing this, he can see the number of queries that have been issued for a single data item. He notices that he has generated a query on the same primary efficacy endpoint for 12 patients across all his sites for Study A. As this study still has two years to run, he puts a comment on that data item to retrain his sites on the data completion guidelines for that item.

He also runs a separate report on the percentage of missing items and sees that one site has twice the percentage of his other sites. He composes an email to the coordinator for that location, citing several examples of missing data elements and offering to discuss with the site how to avoid this going forward.

Finally, he filters his query list to display only queries that have fired automatically. He examines and closes most of them, but notices that his largest site in Study A has a habit of insisting on the original entry and providing rather weak explanations for why the data value, in spite of the query message, should be considered to be correct. Mike is particularly concerned with this trend, as this site has three times the enrollment of the other sites and is the leading enroller across the entire study. He considers what this means as far as the suitability of these patients and spends additional time reviewing the five enrollment waivers that have been granted to this site. He also makes a note to reexamine the inclusion/exclusion data in the source documents at his next visit. Mike knows that this high enroller will most likely be the target of a pre-approval inspection by Bioresearch Monitoring auditors and he wants to be proactive in addressing potential concerns that may arise then.

Tuesday, 7 P.M.

On Tuesday evening, Mike hops a plane for a two-day road trip: one day for a monitoring visit at a site in Study A, and a second day for an initiation visit at the first site for Study C.

Wednesday, 9 A.M.

Doing SDV. This morning, Mike is at the site for Study A. The site coordinator provides Mike with the patient files and Mike logs in to the EDC system with his own laptop and verifies the data against the source. Since he is not using the site’s computer, he can work freely without interruptions. Having cleaned these data on Monday, Mike’s activity is focused on checking for transcription errors against the source and also looking for unrecorded AE’s. Only one transcription error is found and Mike chooses to raise a query about this within the system, as the site coordinator is unavailable for consultation at that moment. While in the EDC system, Mike also sees the note he created on Monday about the unanswered, open query. He finds the answer himself in the source documents and closes the open query.

Mike is done with his work by 1 P.M. This early finish is consistent across all of his EDC studies, where he finds that he spends about 50% less time working through patient files compared to a paper trial. Regularly viewing and querying these data prior to the site visit has made this acceleration possible.

Thursday, 6 P.M.

Catching the LPLV. On Thursday, Mike has traveled to a different site for an initiation visit for Study C. At the same time, Mike is anticipating the last visit of the last patient that afternoon for Study B. Fortunately, Mike has worked out an agreement with that site’s coordinator to expedite the entry of these data into the EDC system. Now Mike is at the airport on his way home, and he is able to log into the EDC system and view and clean these LPLV data. He also source verifies this final visit, using three, anonymized source documents that the site has agreed to send via e-mail. Just before boarding the plane, Mike is able to flag this visit in the EDC system as SDVed and clean. He also sends an email to the data manager for the trial indicating that, from a monitoring perspective, the trial data are ready for locking.

Friday, 9 A.M.

Checking enrollment. On Friday morning, Mike logs in to the EDC system for each of his studies. He knows that enrollment updates are due in the corporate CTMS on Fridays. He also knows that the IVRS/EDC interface has done its weekly update overnight on Thursday and that all randomized patients now have an entry in the EDC system. He runs an online report showing the total enrollment for every study and the progress status for each patient. He has to update the CTMS data with these data, but has figured out how to copy and paste the results from the online EDC report, so that he doesn’t have to retype them in the CTMS. He also knows that even this will eventually go away, as an EDC/CTMS interface will arrive in 2008 to complement the IVRS/EDC interface.

Having finished his EDC work for the week, Mike spends the rest of Friday on his many other duties, including writing trip reports, reviewing the protocol for Study C and participating via conference call on the project team for the new EDC/CTMS interface. At 5 P.M. on the dot, Mike is off into a restful weekend.

The Rest of the Story

In case you think this is sounding more like Sir Thomas More’s Utopia, let me quickly remind you of the rest of the story. EDC doesn’t mean that your sites will never make irritating mistakes; that site responses to your queries will never be confusing; or that the technology will never have its negative moments. EDC will also require, at least initially, more focus on training and a new perspective on defining and testing the EDC system from the site’s perspective, requirements that may involve you in activities you didn’t have to do in paper trials.

But good use of EDC will also always mean: 1) that you are more in control than ever; 2) that you now have new and flexible ways to do your work on your terms and according to your own schedule; and 3) that mundane tasks like query generation and resolution will be easier than ever, leaving more time for true clinical research and building positive site relationships.

A key part of our movie, It’s a Wonderful Life, is our hero George being shown what life in his hometown would have been like if he had never been born. Review Mike Monitor’s week and imagine it without EDC. Recall what it is like to do a paper trial: the mountains of binders; the queries coming from headquarters six months later; the forced timing of site visits to pick up CRFs; the pressure to finish your work at a site before they closed for the day; and the many data “surprises” that arise as you tried to lock the database. The good news is you don’t have to jump off the bridge: EDC is here to stay, and you really can have a relatively wonderful life – not in the movies, but working as an “e-enabled” monitor.