CLINICAL TRIAL PATIENT TECHNOLOGY INSIGHTS
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Clinical Research Has System Sprawl Problem
Disconnected systems are strangling clinical trials. Here’s what’s causing the sprawl, why it keeps getting worse, and what needs to change.
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How Clinical Trial Sites Must Adapt To The Predictive Analytics Era
Clinical trial sites are now measured, ranked, and selected by predictive models. Learn how to perform and compete in this data-driven new era.
ECOA RESOURCES
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Examine the three reasons why simplifying your clinical data flow can increase operational oversight, shorten data management cycle times, and reduce the manual burdens on data management teams.
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Due to the global health impact of COVID-19, many aspects of daily life have been moved to a hybrid model, meaning a mix of in-person and technology-enabled interactions In this blog, learn why eCOAs are especially well-suited for hybrid clinical trials.
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Discover how forward- thinking life science companies are defining their vision and looking for like-minded partners to execute information technology.
ECONSENT RESOURCES
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Obtain a complete understanding of enrollment, screening, consent, and data collection by diving into this introductory handbook on decentralized clinical trials.
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Learn how eConsent digitalizes the trial participant consent process through increasingly simplified models designed to improve comprehension and boost engagement.
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EU Annex 11 lays out the European Union’s regulations for using computerized systems during clinical trials. Learn how sponsors and sites seeking treatment approval in the EU must follow Annex 11.
EPRO RESOURCES
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Patient-reported outcomes (PROs) are vital for clinical trials but can burden participants and providers. Discover strategies and practical solutions to ease these burdens and improve data quality.
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Learn how eConsent digitalizes the trial participant consent process through increasingly simplified models designed to improve comprehension and boost engagement.
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Patient-reported outcomes (PROs) assess patients' health without clinician interpretation. Traditional paper methods often result in missing data and quality issues, while electronic solutions enhance data accuracy and completeness.