5 Tips For Better CAPAs

Consistently one of the FDAs top three cited issues in 483, Corrective and Preventive Actions (CAPA) is likely your organization’s biggest enforcement risks. Check out some of our tips to keep your CAPAs out of inspection reports

  1. Do yourself a favor. Spend the time to define the problem correctly.

    Many a CAPA (and several man months) have been wasted chasing the root cause, and measuring effectivity of the wrong problem statement. Take some time at the front end to make sure you're 1) solving the right problem, and 2) not trying to solve world hunger.

    Some tips to do this well:

      1. Use a tool to more accurately refine your problem statement (e.g. is/is not).

      2. Have a cross-functional team confirm their shared understanding of the problem.

      3. Gather objective evidence to confirm the problem statement as written.

      4. Can you reproduce the problem?

      5. Are there other similar issues going on that you may have missed that should be included in your investigation?

  2. Contain the problem!

    While not an expressly required part of the CAPA process, containment is a foundational principle of quality systems. We therefore recommend containment, and correction plans for issues that present in the field and may impact patients or users.

  3. As with crossing the street, be sure to look left and right

    Perhaps one of the most commonly missed steps of Preventive Actions is seeing where else in your system or product portfolio this issue might recur. It differs from the look for similar issues conducted at the front end of the process by taking into account all we know from the investigation and Root Cause Analysis phases.

    Let's say we determined our spec was incorrect because we didn't realize the product was intended for pediatric use, and we use adult anatomy to determine our spec. We'd want to check which other specs in our product may have been incorrectly generated this way. We would also want to see if we had any other products that made similar adjustments to intended use where sources for specs had not been changed accordingly.

  4. Don’t miss the CA/PA forest for the trees

    Perhaps an offshoot of not following tip #1 well, We often see CAPAs that at a detail level make sense, but miss the proverbial forest for the trees. It’s critical at the CA/PA definition phase to step back from the detail Root Cause Analysis and Investigation and look at your proposed actions relative to the initial problem/NC/Complaint. This will help you identify holes in your CAPA you may have missed during particularly drawn out, or deeply technical CAPAs where you have gotten lost in the details.
    To avoid this, ensure each action ties back to the originating issue accordingly, and will be ultimately measurable. Does your CA flow logically from your identified Root Cause and would resolve the problem as defined in the problem statement? Does your PA flow from your left and right look? If I reread the originating issue and investigation, have I somehow missed an important loose thread?
    These steps will help you when measuring your CAPAs effectiveness

  5. Now when you’re verifying Effectiveness…

    Probably one of the most troublesome areas of a CAPA (and where I write some of the most findings) is defining a good effectiveness check. Note we are measuring the EFFECTIVENESS of your actions, and not verifying the completion of your actions.

    I’ve seen many a CAPA where the effectiveness check did little else than verify that a code change was implemented and that it passed Verification and Validation again. Implementing a change, and passing the same Verification and Validation the initial problem escaped through does pretty much nothing to demonstrate you’ve eliminated the problem.

Khalil Thomas

Khalil Thomas is a Health Equity expert and President of TRCG, a boutique Digital Health consulting group that leverages regulatory compliance expertise to bring solutions to market, manage algorithm bias, and improve quality for an expanded patient demographic. He specializes in topics at the intersection of AI, Health Tech, and Health Equity; highlighting pathways for innovation enabled equity.

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