Your coders identify a diagnosis that needs to be captured. Diabetes with complications. CKD stage 4. CHF with reduced ejection fraction. But the documentation doesn’t quite have adequate MEAT criteria.
You send a provider query. The provider ignores it. Or they respond with something vague that doesn’t actually help. Your query process is supposed to solve MEAT criteria gaps, but it’s not working.
Here’s why most provider queries fail and what actually gets providers to document MEAT criteria properly.
The Problem with Generic Queries
Most organizations send queries that sound like this: “Please provide additional documentation to support the diagnosis of congestive heart failure for this encounter.”
What is the provider supposed to do with that? It doesn’t tell them what’s missing. It doesn’t explain what MEAT criteria requires. It makes them guess what you need.
So they either ignore the query (too vague to know how to respond) or they write something generic like “Patient has CHF” (which doesn’t add any MEAT criteria value).
The query failed because it didn’t give the provider clear, actionable guidance.
The Specific Query Approach
Effective MEAT criteria queries are surgical, not general. They identify exactly what’s missing and exactly what the provider needs to add.
Instead of: “Please provide additional documentation to support CHF diagnosis.”
Try this: “Your note indicates patient has CHF (mentions leg edema and dyspnea). To support this diagnosis for risk adjustment, please document: (1) Current volume status or functional capacity, (2) Current medications being used to manage CHF, or (3) Any CHF-related treatment adjustments made during this visit.”
That’s a query the provider can actually respond to. They know exactly what you need. They can look at the patient’s chart and add the specific information requested.
I’ve seen query response rates jump from 30% to 75% just by making queries more specific and actionable.
The Education-First Approach
The best provider query isn’t a query at all. It’s education that prevents the documentation gap from occurring in the first place.
When you identify that a provider consistently under-documents MEAT criteria for certain conditions, don’t just keep querying them. Educate them.
Show them actual examples from their own charts. “Here’s a CHF patient where your documentation had adequate MEAT criteria: you noted volume status, current medications, and functional limitations. Here’s a CHF patient where MEAT criteria was missing: you listed CHF in the assessment but didn’t document any of those elements.”
Providers learn faster from their own examples than from generic training. When they see the difference between adequate and inadequate documentation in their own notes, they get it.
Some organizations have reduced query volumes by 60% through targeted provider education. You fix the root cause (inadequate documentation) instead of constantly fixing symptoms (querying for missing information).
The Timing Problem
You review a chart from three months ago. Documentation is inadequate. You send a query.
The provider doesn’t remember the encounter. They can’t add meaningful detail three months later. The query either gets ignored or gets a useless response like “patient has this condition.”
Concurrent or near-concurrent queries get dramatically better response rates. Query within 7-14 days of the encounter while the visit is still somewhat fresh in the provider’s memory.
If you’re running fully retrospective programs that don’t review charts until months later, your query effectiveness will always be limited. The provider can’t document what they don’t remember.
The Query Template Trap
Many organizations create query templates to save time. “Template A for diabetes queries. Template B for CKD queries.”
Templates are efficient for coders. They’re terrible for providers.
Providers can tell when they’re getting template queries. The query doesn’t reference the specific patient or clinical situation. It uses coding terminology (HCC, MEAT criteria, RAF) that means nothing to clinicians.
Template queries feel like administrative busywork. Customized queries feel like genuine clinical communication.
You don’t need to write every query from scratch. But you need to customize queries enough that they reference the specific patient, the specific clinical situation, and use language providers actually understand.
The Multiple Query Problem
Some organizations batch queries. They review 50 charts from Dr. Johnson, identify 30 documentation gaps, and send Dr. Johnson 30 queries at once.
Dr. Johnson opens her email, sees 30 queries, and thinks “I don’t have time for this.” She ignores all of them.
Throttle your queries. Send no more than 5-7 queries per provider per week. Yes, this means your documentation completion takes longer. But 75% response rate on queries sent over three weeks is far better than 20% response rate on queries sent all at once.
The Incentive Reality
Providers have limited time. They prioritize clinical work over administrative tasks. Responding to coding queries is administrative work.
Organizations that get high query response rates have created provider incentives. Some tie query response to performance evaluations. Some include it in compensation metrics. Some provide quarterly feedback showing each provider’s query response rate compared to peers.
Financial incentives work best, but require organizational support. If you can’t implement financial incentives, at least provide regular feedback and recognition. Acknowledge providers who respond quickly and thoroughly. Create social pressure through peer comparison.
The EHR Integration Solution
Email queries sit in crowded inboxes and get ignored. Queries sent through the EHR as tasks get much higher visibility and response rates.
If your EHR supports it, send queries as tasks that appear in the provider’s workflow. They see the query when they’re already working in the EHR. The query shows up in their task list. They can respond without leaving their normal workflow.
This requires technical integration between your coding platform and provider EHRs. Not every organization can do it. But when it’s possible, EHR-integrated queries get response rates 40-50% higher than email queries.
The Query Follow-Up Process
When providers don’t respond to queries, what happens? In most organizations, nothing. The query sits unanswered until you hit submission deadlines.
Better approach: systematic follow-up after 5-7 days. Not with another copy of the same query, but with a personal check-in. “Dr. Johnson, I sent you a query about Mrs. Smith’s CKD documentation from last Tuesday. Do you need any clarification on what information would be helpful?”
Follow-up shows that queries matter. It also catches providers who intended to respond but forgot. A gentle reminder gets them to actually do it.
What Actually Works
Effective provider queries require more effort than generic templates. They require specificity, timing, customization, throttling, incentives, integration, and follow-up.
Organizations that treat queries as “send and hope” get 25-35% response rates. Organizations that implement these best practices get 70-80% response rates.
That difference directly impacts your capture rates and coding quality. Fix your query process and you’ll fix a significant portion of your MEAT criteria gaps.
