Integrating patient-generated data into clinical research would improve the reliability of results, especially when longitudinal, chronic, home-based monitoring is needed. To this end, we designed, implemented, and tested a system that allows integrating patient-generated data into electronic case report form (eCRF), using a standards based architecture that ensured the fulfillment of the major requirements for digital data in clinical studies. The system was tested in a clinical investigation for the optimization of deep brain stimulation therapy in patients with Parkinson’s disease that required both the collection of patient-generated data and of clinical and neurophysiological data. The validation showed that the implemented system was able to provide a reliable solution for including the patient as direct digital data source, ensuring reliability, integrity, security, attributability, and auditability of data.

Point of Care Research: Integrating patient-generated data into electronic health records for clinical trials

Sara Marceglia
;
Pierluigi D’Antrassi;Marco Prenassi;
2017-01-01

Abstract

Integrating patient-generated data into clinical research would improve the reliability of results, especially when longitudinal, chronic, home-based monitoring is needed. To this end, we designed, implemented, and tested a system that allows integrating patient-generated data into electronic case report form (eCRF), using a standards based architecture that ensured the fulfillment of the major requirements for digital data in clinical studies. The system was tested in a clinical investigation for the optimization of deep brain stimulation therapy in patients with Parkinson’s disease that required both the collection of patient-generated data and of clinical and neurophysiological data. The validation showed that the implemented system was able to provide a reliable solution for including the patient as direct digital data source, ensuring reliability, integrity, security, attributability, and auditability of data.
2017
9781510853072
https://knowledge.amia.org/65881-amia-1.3897810/t003-1.3901461?qr=1
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AMIA 2017 Annual Symposium + toc.pdf

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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11368/2924604
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