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Good Documentation Practices (GDP)

According to federal regulations (45 CFR 46), by definition, research is ‘a systematic investigation, including research development, testing, and evaluation, designed to develop or contribute to generalizable knowledge’. The ability to meet that aim depends on multiple factors, one of which is the ability to collect ‘good’ data (meaning, the data is accurate, reliable and reproducible).

In order end up with a ‘good’ dataset at the end of a project, study teams must be cognizant of maintaining accurate records/documentation throughout the entire course of the research.

 

GDP definition

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.

Key attributes of ‘good’ documentation

Key attributes of ‘good’ documentation, often referred to as the ALCOAC standard, and include documentation that is:

Attributable

Study documentation should identify who recorded the data/information; the information should be traceable to a person, date and time (as appropriate).

Legible

Study documentation, including signatures, should be easy to read, understandable, and identifiable.

Contemporaneous

Information should be recorded as it happens and the information recorded within study documentation should flow in a correct and appropriate timeframe.

Original

Study documentation should be the original source document. Alternately, an exact/certified copy of the original (as appropriate) should be maintained, with notation referencing the original source.

Accurate

Study documentation should be correct, free from errors, consistent and a real representation of facts.

Complete

Study documentation should be all-inclusive and comprehensive.

More attributes

Other key attributes

Additional key GDP attributes include:

  • Enduring
  • Available
  • Accessible
  • Consistent
  • Credible
  • Corroborated

Putting GDP into practice

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 12th while in Europe it’s December 7th).  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.
Recorded training sessions

Archived UR-HRPP Educational Forums are available. To access recordings listed below, follow our Blackboard Self-Enrollment Instructions and enroll in the course titled ‘UR-HRPP Educational Materials’:

  • 12/9/2021: Essential Study Documentation – Part 1
  • 1/21/2022: Essential Study Documentation – Part 2