Efficiency of eSource Direct Data Capture in Investigator-Initiated Clinical Trials in Oncology

Author:

YAEGASHI Hiroko1ORCID,HAYASHI Yukikazu2,TAKEDA Makoto2,CHIU Shih-Wei1,NAKAYAMA Haruhiko3,ITO Hiroyuki4,TAKANO Atsushi5,TSUBOI Masahiro6,TERAMOTO Koji7,SUZUKI Hiroyuki8,KATO Tatsuya9,YASUI Hiroshi5,NAGAMURA Fumitaka5,DAIGO Yataro5,Yamaguchi Takuhiro1

Affiliation:

1. Tohoku University Graduate School of Medicine

2. A2 Healthcare Corporation

3. Kanagawa Prefectural Hospital Organization

4. Kanagawa Cancer Center: Kanagawa Kenritsu Gan Center

5. The Institute of Medical Science The University of Tokyo: Tokyo Daigaku Ikagaku Kenkyujo

6. National Cancer Center-Hospital East: Kokuritsu Gan Center Higashi Byoin

7. Shiga University of Medical Science: Shiga Ika Daigaku

8. Fukushima Medical University: Fukushima Kenritsu Ika Daigaku

9. Hokkaido University Hospital: Hokkaido Daigaku Byoin

Abstract

Abstract Background Clinical trials have become larger and more complex. Thus, eSource should be used to enhance efficiency. This study aimed to investigate the impact of using direct data capture (eSource DDC) using electronic case report forms as source data on the efficiency of a late-phase, multicenter, investigator-initiated clinical trial in oncology. Methods Source data identification list, electronic data capture (EDC) database structure specifications, audit trails output from EDC, and monitoring reports were used to analyze varying collection items of DDC at each site, time from data occurrence to data entry and data finalization, and number of visits to the site and time spent at the site by clinical research associates (CRAs). Additionally, simulations were performed on the change in hours at the clinical sites during the implementation of eSource DDC. Results The percentage of fields with DDC was 61.9–84.5%, indicating variations across sites. The forms commonly defined as DDC for all sites tended to be initially entered by clinical research coordinators. No difference in time from data occurrence to data entry was observed between the DDC and the transcribed data fields. However, the DDC fields could be finalized 4 days earlier than the non-DDC fields. Additionally, although no difference was observed in the number of visits for source data verification (SDV) by CRAs, a comparison between sites that introduced eSource DDC and those that did not showed that the time spent at the site for SDV was reduced. Furthermore, the simulation results indicated that even a small amount of data to be collected or a small percentage of DDC-capable items may lead to greater efficiency when the number of subjects per site is significant. Conclusions The implementation of eSource DDC may enhance efficiency, depending on the study framework and the type and number of items to be collected.

Publisher

Research Square Platform LLC

Reference7 articles.

1. International Council for Harmonization. Integrated addendum to ICH E6(R. 1): Guideline for good clinical practice E6(R2); 2016. https://database.ich.org/sites/default/files/E6_R2_Addendum.pdf. Accessed September 2023.

2. New Benchmarks Characterizing Growth in Protocol Design Complexity;Getz KA;Ther Innov Regul Sci,2018

3. Optimizing the Use of Electronic Data Sources in Clinical Trials: The Landscape, Part 1;Kellar E;Ther Innov Regul Sci,2016

4. Optimizing the Use of Electronic Data Sources in Clinical Trials: The Technology Landscape;Kellar E;Ther Innov Regul Sci,2017

5. European Medicines Agency. Qualification opinion on eSource Direct Data Capture (DDC). https://www.ema.europa.eu/documents/regulatory-procedural-guideline/qualification-opinion-esource-direct-data-capture-ddc_en.pdf. Accessed September 2023.

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