Most practices have dashboards. Far fewer know which number to act on next. Healthcare Logic's KPIs Model tracks the handful of metrics that actually move money -- clean claim rate, days in AR, net collection rate, denial rate, first-pass resolution -- and ties each one to the operational cause behind it, so the data tells you exactly what to fix.
These are the metrics that reveal where a revenue cycle is healthy and where it is leaking. We track each against a benchmark set for your specialty and payer mix, and tie every movement to its operational cause.
The share of claims that go out without errors and pay without rework. High performers target around 95 percent or better; a dip points straight to front-end or coding problems we can isolate.
How long, on average, money sits unpaid after service. A target under roughly 40 days keeps cash flowing; a climbing figure shows where follow-up and posting are slipping.
The percentage of collectible revenue you actually capture after contractual adjustments. Near 95 to 96 percent or higher is the goal; a gap reveals revenue written off that should have been recovered.
How often claims are denied and, just as important, why. We track denials by reason so the largest categories surface first and get worked before they age out of appeal windows.
How often a claim is paid the first time it is submitted, with no resubmission or appeal. A target near 90 percent or higher means the front end and coding are working; below it means avoidable rework.
AR aging buckets and rolling trends behind every headline number, so a single bad week is separated from a real shift, and the metrics show direction, not just a snapshot.
The model is built to end every review with a decision. Here is how a number becomes a fix.
Numbers on a screen do not improve collections; acting on the right ones does. The KPIs Model exists to turn financial pressure into a short, prioritized list of fixes, so the team always knows where the next dollar is and what to do to capture it.
A focused set of metrics that reveal revenue health, instead of a wall of charts no one acts on.
Every movement is connected to its operational source, so you fix the problem, not the number.
Targets set for your specialty and payer mix, so deviations actually mean something.
Frequent review of leading indicators means problems are addressed while they are still small.
A handful of metrics tell you most of what you need to know about revenue cycle health: clean claim rate, days in accounts receivable, net collection rate, denial rate, and first-pass resolution rate. Clean claim rate shows how often claims go out without errors, days in AR shows how quickly you get paid, net collection rate shows how much of what you are owed you actually collect, denial rate shows where claims fail, and first-pass resolution shows how often a claim is paid the first time it is submitted. Watching these together reveals where revenue is leaking.
As general industry reference points, high-performing organizations aim for a clean claim rate of roughly 95 percent or better, days in AR under about 40 days, a net collection rate near 95 to 96 percent or higher, a denial rate in the low-to-mid single digits, and a first-pass resolution rate around 90 percent or higher. The right target varies by specialty and payer mix, so we set benchmarks appropriate to your practice rather than applying one number to everyone.
A dashboard shows numbers; the KPIs Model is built to drive decisions from them. We connect each metric to the operational cause behind it, so a rising denial rate points to a specific front-end or coding issue, and a climbing days-in-AR figure points to where follow-up is slipping. The goal is not to admire the data but to know exactly what to change next and to see the effect of that change in the metrics.
The leading indicators, such as clean claim rate, denials by reason, and aging buckets, are most useful reviewed frequently so problems are caught while they are small, while trend metrics like net collection rate and days in AR are best read over rolling periods to separate signal from noise. We establish a cadence that fits your operation and flag meaningful movements rather than burying you in reports.
Yes, because what gets measured gets managed. When the right metrics are tracked against clear targets and tied to specific operational causes, the team can act on the largest leaks first, denials get worked before they age out, and front-end errors get fixed at the source. The model turns abstract financial pressure into a short list of concrete actions, and the collections improvement follows from acting on them consistently.
Talk to Healthcare Logic about putting the KPIs Model to work on your revenue cycle and acting on the numbers that matter.
Talk to an Expert