Improving ECG Data Quality and Availability: Automatic Transmission of Data from Devices into eSource Systems

The electrocardiogram (ECG) is one of the most frequently administered procedures in clinical trials. Historically, the ECG trace has been printed on paper for review, Investigators have hand written their analysis of the ECG, and technicians have transcribed the results onto paper or into eCRF systems. Manual analysis and transcription is less than ideal, however, has been perpetuated because without eSource data and an electronic platform for Investigators to work within, this is what must take place. The FDA’s final guidance on eSource data last year, however, strongly promotes capturing source data in electronic form.

ECG Core Laboratories have partially addressed the eSource issue by providing investigator sites with standardized devices capable of transmitting digital ECG data back to the ECG core lab through a LAN or a modem to a proprietary ECG data management system. While this addresses the results portion of the process, and allows the lab to measure and annotate the ECGs in an electronic environment, it does not address the biggest source of error in the acquisition of ECG data; demographic data entry. Sponsors report that 30% of the ECGs that are acquired within their trials contain demographic data entry errors, as sites must type Subject Initials, Subject ID numbers, Age, Gender, and Visit Codes, at a minimum into an electrocardiograph.

Modern ECG devices include the provision for bi-directional communication either directly from the device to an eSource system (direct data capture), or between the eSource system and an application produced by the device manufacturer. Since the eSource platform’s central database generally contains all of the information above for each subject, it is efficient for the site to select these pieces of data from the central database for population of demographic and visit information to the device or application, thereby removing any manual data entry and potential for error. The bi-directional nature of this communication also implies that instead of the resulting electronic source data being detoured from the eSource database to a proprietary ECG “silo” for measurement and annotation, these tools can be built or embedded within the eSource system, closing the loop on this important data point.

Join the presenters for a complementary webinar and learn how OmniComm and Mortara use the bi-directional communication between Mortara ECG devices and the TrialOne® eSource system to automatically transmit information between the two, and how the implementation of direct data capture is able to improve clinical trial data quality and availability.

Speakers

Mark Mentzer, Vice President of Strategic Partnerships, Mortara Instrument

Mark Mentzer is Vice President of Strategic Partnerships for Mortara Instrument. Mark has led the clinical research business for Mortara for more than 10 years, and has continually driven the Mortara ECG platform toward connected solutions within clinical research. By ensuring Mortara’s ECG devices are specifically designed to meet the unique needs of clinical research, Mark has secured Mortara’s leadership in cardiac safety and efficacy. This same commitment understanding our partner’s and our combined customer’s needs, will ensure we improve the quality of ECG data within trials moving forward.

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Michelle King, Director, Early Phase Consulting, OmniComm Systems, Inc.

Michelle King is Director, Early Phase Consulting for OmniComm Systems, Inc. Michelle has been involved in the implementation of various EDC systems for over 8 years and was previously involved in the management of early phase research sites. This combined experience allows Michelle to assist the OmniComm team in ensuring that their products exceed the needs and expectations of clinical trial sites and sponsors. Michelle’s colleagues at OmniComm have worked closely with the Mortara team to develop the ability to automatically transmit data from devices directly into the eSource system, thus improving trial data quality and availability.

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