Can an AI write your Plan of Correction? The short answer is yes – AI can write a POC. Several tools now exist that will generate one for you in minutes based on the deficiency tag and a brief description of what was cited. Whether that POC will get accepted by your State Survey Agency (SA), actually prevent repeat deficiencies and hold up on a revisit are entirely different questions. Here’s what to think about before you hit “generate.”
A Plan of Correction is a promise – and your survey agency knows the difference between a real one and a template. Don’t forget, regulators are increasingly using artificial intelligence to review data – what do you think will happen when they – or AI – catches the same generic POC over and over?
A POC isn’t a document you write to satisfy a checkbox. It’s a binding commitment on the part of the facility that describes exactly what went wrong, why it happened, what you’ve already done to fix the issue(s), how you’re going to make sure it doesn’t happen again and who is responsible for monitoring that over time. Your State Agency has read thousands of them. They know when a corrective action is realistic and specific to the identified issue and when it’s boilerplate. They know when a systemic fix reflects an actual understanding of the root cause and when someone’s just filled in the blanks.
An AI tool typically generates language based on the tag being cited. AI doesn’t know your building. AI doesn’t know your staff. It doesn’t know that this is the second time your facility has been cited in this area – which changes both the Root Cause Analysis and what the SA expects to see from your corrective action plan. AI doesn’t know that a cited deficiency stems from a staffing pattern issue on your evening shift rather than a policy gap – which means that the corrective action for your facility looks completely different from the corrective action for the facility down the street that was cited for the same tag.
That distinction matters enormously to your survey agency. And it’s the distinction an AI can’t make.
Root Cause Analysis (RCA) isn’t a Fill-in-the-Blanks Exercise
The most important part of a Plan of Correction – the part surveyors will scrutinize most carefully – is whether you actually understand why the deficiency occurred. A generic AI tool will produce generic root cause language because it has no access to what actually happened in your facility or the insights your staff provide as part of this exercise. “Staff weren’t aware of the policy” and “the policy was not consistently implemented” aren’t root cause analyses. They’re placeholders. Surveyors know the difference, and a POC built via fill-in-the-blanks is a Plan of Correction that’s at risk of rejection – or worse, acceptance followed by the same citation on your next survey.
The Revisit is Where a Weak POC Shows Up
A Plan of Correction that gets accepted is only half the battle – it means you’ve made a promise that you’ve got to follow through on. When surveyors return for a revisit, they’re evaluating whether you actually did what you said you would do and whether it worked. A POC that’s built on generic corrective actions is a difficult to implement POC because it wasn’t written based on your actual systems, your actual staff responsibilities and your actual building. The revisit finds the same deficiency again. The cycle continues.
A POC that’s built on generic corrective actions is a difficult-to-implement POC because it wasn’t written based on your actual systems, your actual staff responsibilities and your actual building.
So, What Does a Strong POC Actually Require?
- Someone who has read the citation carefully and understands what the surveyor actually observed – not just the tag number
- A genuine RCA that reflects what happened in your specific facility
- Corrective actions that are realistic given your staffing, your systems and your operational constraints
- Monitoring and auditing steps that your team can actually execute and document. Remember, during a revisit, you’ll need to provide POC-associated documentation to a surveyor. Hopefully, you’ve been able to capture everything your generic POC said you needed to do within the time constraints.
- Language and structure that reflects what your specific State Survey Agency expects to see. There’s often variation in expectations within a state – much less from state-to-state.
- A second set of eyes from someone who has submitted POCs to your agency before and know what gets accepted
None of that requires sophisticated technology. It requires experience, knowledge of your facility, knowledge of best practices for development of a POC and familiarity with State Agency expectations. Your favorite AI may generate a response, but it’s not responding with the knowledge of someone who has read hundreds of survey reports, worked with facilities through the POC process, and knows what your survey agency actually accepts. That’s what CMSCG brings to every Plan of Correction engagement – and it’s what no AI tool can replicate.
Whether your facility is facing a complex survey outcome, an Immediate Jeopardy, a directed Plan of Correction or a rejected POC, the stakes are too high for AI. Contact CMSCG to discuss your situation – we’re here to help.
