Seven EVV Numbers MN Agency Owners Should Check Monthly

Most agency owners see one EVV number a month: the compliance rate. It’s the number DHS watches, so it’s the number that gets reported up. The trouble is that a compliance rate on its own tells you almost nothing about why it’s where it is, whether it’s about to move, or what it’s costing you in delayed claims. An agency sitting at 86% can be in perfectly good shape or one bad month away from a corrective action plan, and the compliance rate alone won’t tell you which.

The seven numbers below take about thirty minutes to pull once your reports are set up, and together they answer the questions the compliance rate can’t. None of them require new software. Most EVV systems and HHAeXchange exports already contain the data; it’s a matter of looking at it the same way every month.

1. Electronic Verification Rate, Not Just Compliance Rate

Start with the share of visits verified electronically at the time of service, without any manual edit. This is different from the compliance rate many agencies track, which in some reports counts manually entered visits with an acceptable reason as compliant.

The gap between the two numbers is the most useful thing on this list. If your compliance rate is 91% but only 74% of visits were verified electronically, you’re relying on manual entries to stay above threshold. That works until the state tightens how it treats manual entries, or until an auditor samples enough of them to find weak documentation. We wrote about why that tightening is more likely than not in our post on federal Medicaid funding pressure and EVV compliance.

What to look for: a gap of more than ten points between compliance rate and electronic verification rate deserves a closer look. A gap that’s growing month over month is the more urgent signal.

2. Manual Entry Rate by Reason Code

Next, break manual entries down by reason code. The total number matters less than the mix.

A spread across several reasons (a forgotten clock-out, a dead phone, a connectivity problem at one rural client) is what normal operations look like. A single reason accounting for most of your manual entries means something specific is broken. If “caregiver forgot to clock out” is 60% of manual entries, you have a training or habit problem. If “device or connectivity issue” dominates, look at specific clients and phones. Our guide to MN manual entry reason codes explains which reasons auditors tend to read as routine and which ones draw questions.

What to look for: any single reason code climbing for two months in a row, and any reason code used much more often by one caregiver than by everyone else.

3. Exception Aging

Count the open exceptions and sort them by age: under three days, three to fourteen days, fifteen to thirty days, and over thirty days.

This is the number that most directly predicts billing trouble. An exception resolved the same week rarely costs anything. An exception that’s thirty days old is a claim that hasn’t been submitted, a caregiver who may not remember the visit anymore, and a timely filing window that’s quietly shrinking. Our post on moving manual entries to a paid claim walks through a timeline where a slow exception eats three months of a filing window before anyone notices.

What to look for: anything over thirty days should be close to zero. If the fifteen-to-thirty bucket is growing, exception review doesn’t have a clear owner, or that owner doesn’t have the time.

4. Median Time to Resolve an Exception

Aging tells you where the backlog sits right now. Time to resolve tells you how fast the queue is moving. Track the median number of days between when an exception is created and when it’s cleared.

Use the median instead of the average. One exception that took ninety days because a caregiver left the agency will drag an average up and hide the fact that everything else clears in two days. The median shows you what usually happens.

What to look for: a median of one to three business days is a well-run queue. A median over a week usually means exceptions get handled in a batch before billing instead of daily, which is the pattern that tends to break down when volume grows.

5. Authorized Hours Used

For each client, compare hours delivered and verified through EVV against hours authorized in the service agreement for the period. Then look at the distribution across your client list.

This number catches problems on both sides. Clients who consistently use less than 70% of their hours may have unfilled shifts, a caregiver who’s cutting visits short, or a care plan that no longer matches what the client needs. Clients at or over 100% are a billing risk, since hours delivered beyond the authorization generally can’t be billed, and a visit billed against an exhausted authorization is a denial waiting to happen. Our post on DHS service agreements and authorized hours covers how reassessments change those limits mid-year.

What to look for: clients over 95% with time left in the authorization period, and clients whose hours used dropped sharply from the previous month.

6. Caregiver-Level Outliers

Run the first three numbers again, this time by caregiver instead of agency-wide. The agency average hides individuals. A 10% manual entry rate across the agency might mean every caregiver has a few manual entries a month, or it might mean three caregivers account for most of them.

Outliers aren’t automatically a performance problem. A caregiver with a high manual entry rate may be the one who covers your most rural clients, or the one who takes the most clients to appointments. But you can’t tell the difference until you look, and an auditor sampling visits will find those caregivers whether you’ve looked or not.

What to look for: any caregiver whose manual entry rate is more than double the agency median, and any caregiver whose exceptions consistently take longer than everyone else’s to resolve. New caregivers in their first thirty days deserve their own view; a spike there points to an onboarding gap rather than a person.

7. Days From Visit to Billable Claim

The last number connects EVV to cash. For visits completed in the month, measure the median number of days between the visit date and the date the visit was ready to bill (cleared in the aggregator and included in a claim batch). Track it separately for electronically verified visits and for manual entries.

Electronic visits should move quickly and predictably. Manual entries will always lag, but the size of the lag tells you how much revenue is sitting in limbo at any given time. If manual entries take an average of nineteen days to reach a claim and you have sixty of them a month, that’s a meaningful amount of earned revenue that’s always nineteen days late.

What to look for: a manual entry lag that’s growing, and the total dollar value of visits that have been ready to bill for more than two weeks but haven’t gone out.

A Monthly Scorecard You Can Copy

Put the seven numbers on a single page and compare them to last month and to the same month last year if you have it. A simple layout:

Metric	This month	Last month	Healthy range
Electronic verification rate			Within 10 points of compliance rate
Manual entries by top reason			No single reason above 40%
Exceptions over 30 days			Near zero
Median days to resolve			1 to 3 business days
Clients over 95% of authorized hours			Reviewed individually
Caregivers above 2x median manual rate			Each one has a known reason
Median days to billable (manual entries)			Stable or falling

The healthy ranges here are working benchmarks, not DHS standards. Every agency’s mix of clients, geography, and service types is different, and the trend in your own numbers matters more than how you compare to a figure in a blog post. A rural agency will have a higher connectivity-related manual entry rate than a metro one. That’s fine, as long as it’s stable and documented.

Turning the Numbers Into a Monthly Meeting

Numbers that nobody discusses don’t change anything. The agencies that get the most out of a scorecard like this hold a short monthly review, usually thirty minutes, with whoever owns scheduling, whoever owns billing, and whoever clears exceptions. In a small agency that might be two people. The format that works:

1. Start with what moved: Skip the numbers that are stable and in range. Spend the time on anything that changed by more than a few points.
2. Name one cause per change: “Manual entries went up” isn’t a cause. “Two new caregivers started on the Duluth route and neither was shown how offline clock-in works” is.
3. Assign one action per cause, with a name and a date. Retrain a caregiver, call a client about their landline, fix a service plan, chase down a batch of old exceptions.
4. Check last month’s actions first: Did they happen? Did the number move?

This is also the meeting where the EVV audit checklist stops being a document you pull out once a year and becomes something you’re already doing. An agency that reviews these seven numbers monthly can answer most audit questions on the spot, because it has been asking itself the same questions all along.

What These Numbers Won’t Tell You

These metrics measure how well visits are captured and billed. They don’t measure care quality, client satisfaction, or caregiver retention, and an agency can score well on all seven while losing caregivers to a competitor every month. They’re one part of running an agency, specifically the part where small, quiet problems tend to grow into audit findings or cash flow gaps if nobody is watching.

They also depend on clean data. If caregivers are assigned to the wrong clients in your EVV system, or authorizations aren’t updated after reassessments, the numbers will be off in ways that are hard to spot. A quarterly check that client records, authorizations, and caregiver assignments match what’s actually happening is worth adding alongside the monthly review.

Questions About Tracking EVV Metrics

Does DHS require agencies to track anything beyond the compliance rate? DHS monitors aggregate compliance, and agencies are responsible for maintaining accurate EVV records and supporting documentation. The other metrics here aren’t state requirements. They’re the internal numbers that keep the required ones in good shape.

How long does it take to set this up? The first month usually takes a few hours to figure out which reports and exports contain each number. After that, most agencies pull all seven in under thirty minutes.

What’s the single most important number if we only track one more? Exception aging. It’s the earliest warning for both compliance trouble and delayed revenue, and it’s the one most directly under the agency’s control.

Should caregivers see their own numbers? Yes, in most cases. Caregivers who can see their own clock-in success rate and open exceptions tend to fix problems faster than ones who only hear about them in a supervisor’s call.

Where Zayd Fits

Zayd’s exception manager flags missed clock-ins, location mismatches, and manual entries as they happen rather than after an export, which is what keeps exception aging and time to resolve (numbers three and four on this scorecard) low in the first place. Visits flow into HHAeXchange through Alt-EVV sync, so your billing workflow and system of record stay where they are while you run the monthly review.