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. Author manuscript; available in PMC: 2023 Jun 12.
Published in final edited form as: J Biopharm Stat. 2022 Jun 12;32(3):496–510. doi: 10.1080/10543406.2022.2080698

Table 1.

Comprehensive recommendations for data management of the digital clinical trial building on the CTTI guidelines*.

Category CTTI Recommendation Enhanced Recommendation
1.General N/A Consider whether data storage needs to be FDA 21 CFR Part 11 Compliant as this will inform the structure of the electronic database platform
Proactively address and map data flow, data storage, and associated procedures Proactively address and map data flow, data storage, and associated procedures
Plan appropriately for the statistical analysis of data captured using digital technologies (Moved from Section 4) Plan appropriately for the processing and analysis of all data in the digital clinical trial including but not limited to data captured using digital technologies where all primary, secondary, and sensitivity analyses are prespecified including how to handle missing data
N/A Plan to obtain time stamps using Coordinated Universal Time on each piece of data deemed necessary to address study goals while understanding sources of variation in the time stamp variable
Collect the minimum data set necessary to address the study endpoints Collect the minimum data set necessary to address the study goals, recognizing that time stamp data should always be considered necessary even if not part of the endpoint definition
Identify acceptable ranges and mitigate variability in endpoint values collected via mobile technologies Identify acceptable ranges and mitigate variability in endpoint values collected via mobile technologies including the timing of when the data are obtained, as battery life of the device may impact the variation in data obtained for example
2.Access to Data Optimize data accessibility while preventing data access from unauthorized users Optimize data accessibility while preventing data access from unauthorized users
Ensure that access to data meets your needs prior to contracting an electronic service vendor Ensure that access to data meets your needs prior to contracting an electronic service vendor
Address data attribution proactively with patient input Address data attribution proactively with patient input
Ensure that site investigators have access to data generated by their participants Ensure that site investigators have access to data generated by their participants
Return value to participants throughout the trial, including return of outcomes data collected by digital technologies Return value to participants throughout the trial, including return of outcomes data collected by digital technologies, when appropriate interpretation is possible and can be provided
Let data sharing decisions be driven by safety and trial integrity Let data sharing decisions be driven by safety and trial integrity
3.Security & Confidentiality Apply an end-to-end, risk-based approach to data security Apply an end-to-end, risk-based approach to data security
Ensure the authenticity, integrity, and confidentiality of data over its entire lifecycle Ensure the authenticity, integrity, and confidentiality of data over its entire lifecycle
Be prepared to collaboratively identify and evaluate privacy risks Be prepared to collaboratively identify and evaluate privacy risks
Ensure that participants understand the privacy and confidentiality implications of using digital technologies Ensure that participants understand the privacy and confidentiality implications of the particular digital tool(s) involved in the study of interest
4.Monitoring for Safety & Quality N/A Consider a novel composition of Data & Safety Monitoring Board members that includes members of the community (e.g., participant stakeholders critical for discussions on sharing and interpretation of data) and multiple quantitative experts who can speak to the data integrity of the trial including software engineers familiar with the device/platform and sources of variation in data generated, information technology experts familiar with data flow, clinicians with expertise in the relevant disease area, and biostatisticians familiar with trial monitoring and analysis of the key endpoints
N/A Include data scientists with diverse background in the study leadership who will shape and oversee the monitoring plans including biostatisticians analyzing the data, information technology experts facilitating data flow and secure data capture, and software engineers well versed in data generation from the digital tools
Include appropriate strategies for monitoring and optimizing data quality Pre-specify appropriate strategies for early and frequent monitoring of data quality that involve consideration of relevant joint relationships among variables as described in Statistical Analysis Plan.
N/A Consider a deduplication process to ensure mapping and linkage of data to unique individuals (e.g., if relying on an app or an electronic health care system in enrollment plan) employed in real-time (e.g., as participants are enrolled) that includes a plan to refine and evaluate updated algorithm’s ability to identify duplications
Set clear expectations with participants about safety monitoring during the trial Set clear expectations with participants about safety monitoring during the trial and about sharing clinical findings during and after the trial
Monitor data quality centrally through automated processes Monitor data quality centrally through automated processes
Minimize missing data Minimize missing data
N/A Design a pilot study prior to launch that collects data from participants within the target population if possible to test the data flow beyond end-to-end testing, and that executes the prespecified analysis plan and data quality monitoring plan so that data are processed, endpoints derived, missing data are observed and joint relationships evaluated in order to identify potential issues with the database and data integrity with an emphasis on ability to identify non-unique participants