Good Documentation Practices (GDP)

Good Documentation Practices (GDP) is a term used by the pharmaceutical, laboratory and manufacturing industries to describe best practices surrounding the creation and maintenance of documentation (in both paper and electronic format).

While there is not one specific regulation or policy that defines GDP, components of GDP are cited by federal and international agencies, including the Food & Drug Administration (FDA), the International Council for Harmonization of Technical Requirements for Pharmaceuticals for Human Use (ICH), and the World Health Organization (WHO), as well as institutional policy.

GDP is essentially good recordkeeping practices to help ensure the quality and integrity of the data collected. This is applicable to all types of research, both biomedical and social/behavioral/educational, and includes records and documentation of study observations, activities and data.

To put the key attributes described above into practice, consider the following GDPs:

• When developing data collection forms, add initial/signature and date lines to indicate who recorded the data.
• Only use wet ink (blue or black pen) on paper documentation to ensure permanency; do not use pencil, crayon, or marker. Do not use signature stamps in lieu of a handwritten signature, for example on a consent form or signature log.
• Write dates, minimally, with the first 3 letters of the month instead of a numerical representation of the month to accurately/clearly document the date. This is particularly important for multi-site and international trials as local customs vary (7/12 in the US is July 12^th while in Europe it’s December 7^th).  Best practice is to use a day-month-year format (i.e. 11APR2022 or 11APR22). Similarly, time should be recorded using a 24-hour clock or military time (i.e. 17:00 as opposed to 5:00pm). Use consistent date and time formats throughout all documentation to decrease confusion.
• Do not pre- or back-fill dates, time, data, initials or signatures; never sign anyone else’s name on study documentation. Data (including signatures and dates) should be recorded in real time, by the originator.
• Ensure units of measure are identified, as appropriate.
• When errors are made, an audit trail of edits should be maintained. The change should not obscure the original entry; do not white-out, cross out or otherwise redact the original entry.  Draw a single line through the error, note the correction, including a reason for the revision (as appropriate) and sign and date the correction.
• Ensure all missing data points are noted and explained in the study documentation (e.g., was the procedure missed inadvertently, skipped on account of time constraints or refused by the subject).
• Conduct independent quality checks (i.e., second person verification) on critical or pivotal entries, minimally, to ensure ALCOAC standards are met.