Guide

Good documentation practices (GDP) for medical device teams

Good documentation practices are the habits that make a record usable as evidence: contemporaneous, accurate, attributable and complete. Auditors rarely fault a company for a weak process it can explain — they fault records that cannot be trusted, which is what GDP prevents.

The principles

What a good record looks like

Attributable and contemporaneous

Every entry shows who made it and is made when the activity happens — not reconstructed at the end of the week from memory. In electronic systems this comes from named accounts and audit trails.

Accurate and complete

The record reflects what actually occurred, including deviations. Corrections keep the original visible — a single line through a paper entry, or a tracked change — with a reason and the corrector's identity.

Consistent and legible

Formats follow the controlled form or template. Free-text fields say something specific: 'as per procedure' tells a reviewer nothing; what was done, by whom, and against which document does.

Data integrity (ALCOA+)

The widely used ALCOA+ shorthand — attributable, legible, contemporaneous, original, accurate, plus complete, consistent, enduring and available — is a practical checklist for judging any record.

Building the habit

Practices that hold up in an audit

  1. 1Use controlled templates and forms, so reviewers know where each piece of information belongs.
  2. 2Ban pencil, white-out and unsigned corrections on paper; use the correction method the record defines.
  3. 3Never sign for someone else, and never backdate — both turn a weak record into a data-integrity finding.
  4. 4Write entries as if the reader knows nothing about the task: what, who, when, against which procedure.
  5. 5Review records as you go — a supervisor's timely review catches gaps while the work is still fresh.

Where Qevatrix fits

Documentation discipline by design

QualityOS makes good documentation the default: controlled templates, named-account entries, full audit trails and signature rules, so records stay attributable and complete without relying on memory or after-the-fact reconstruction.

This guide is an orientation, not regulatory advice. Data-integrity expectations appear in FDA inspection practice, EU guidance and ISO 13485 records requirements; confirm specifics with your quality team.