Literature DB >> 29714600

Baseline Assessment of the Evolving 2017 eClinical Landscape.

Michael Wilkinson1, Richard Young2, Beth Harper3, Brittany Machion2, Ken Getz1.   

Abstract

The volume and diversity of data collected to support each clinical study has increased dramatically in response to the rising scope and complexity of global drug development programs. The Tufts Center for the Study of Drug Development conducted an online survey of 257 unique global companies-77% drug development sponsors and 23% contract service providers-to assess clinical data management practices and experiences. Study results indicate that companies are using an average of 6 different applications to support each clinical study and that companies are collecting a range of data types including that from case report forms, lab procedures, pharmacokinetics, biomarker, outcomes assessment, mobile health, and social media. Companies report that the primary electronic data capture (EDC) is capturing traditional data types but not many of the newer ones. Respondents report spending an average of 68.3 days to build and release a study database, 8.1 days between the patient visit and when that patient's data are entered into the EDC system, and 36.3 days on average to lock the database following the last patient last visit. Average cycle time durations are longer and more variable than those observed ten years ago. Subgroup differences (eg, by company size and company type) and factors contributing to data management cycle time and experience are discussed.

Entities:  

Keywords:  clinical data management; data lock; eClinical data; electronic data capture; study database

Mesh:

Year:  2018        PMID: 29714600     DOI: 10.1177/2168479018769292

Source DB:  PubMed          Journal:  Ther Innov Regul Sci        ISSN: 2168-4790            Impact factor:   1.778


  5 in total

Review 1.  Key components and IT assistance of participant management in clinical research: a scoping review.

Authors:  Johannes Pung; Otto Rienhoff
Journal:  JAMIA Open       Date:  2020-10-14

2.  Leveraging Informatics and Technology to Support Public Health Response: Framework and Illustrations using COVID-19.

Authors:  Jane L Snowdon; William Kassler; Hema Karunakaram; Brian E Dixon; Kyu Rhee
Journal:  Online J Public Health Inform       Date:  2021-03-21

3.  Characterizing Pain Points in Clinical Data Management and Assessing the Impact of Mid-Study Updates.

Authors:  Beth Harper; Zachary Smith; Jane Snowdon; Robert DiCicco; Rezzan Hekmat; Dilhan Weeraratne; Ken Getz
Journal:  Ther Innov Regul Sci       Date:  2021-05-07       Impact factor: 1.778

Review 4.  Artificial intelligence in clinical and translational science: Successes, challenges and opportunities.

Authors:  Elmer V Bernstam; Paula K Shireman; Funda Meric-Bernstam; Meredith N Zozus; Xiaoqian Jiang; Bradley B Brimhall; Ashley K Windham; Susanne Schmidt; Shyam Visweswaran; Ye Ye; Heath Goodrum; Yaobin Ling; Seemran Barapatre; Michael J Becich
Journal:  Clin Transl Sci       Date:  2021-10-30       Impact factor: 4.689

5.  Which decentralised trial activities are reported in clinical trial protocols of drug trials initiated in 2019-2020? A cross-sectional study in ClinicalTrials.gov.

Authors:  Amos J de Jong; Renske J Grupstra; Yared Santa-Ana-Tellez; Mira G P Zuidgeest; Anthonius de Boer; Helga Gardarsdottir
Journal:  BMJ Open       Date:  2022-08-29       Impact factor: 3.006

  5 in total

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