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Medical Revenue Cycle Metrics Template

Four documents and four sheets, every metric computed per payer, because the practice-wide average hides the payer dragging it.

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Clean Claim Rate

One row per payer, not one number for the practice

Every metric in this pack is computed per payer and carries its own denominator on the row. The three rejection columns are what the single rate hides.

PayerPeriodClaims submittedAdjudicated first passClean claim rateRejected at clearinghouseRejected pre-adjudicationDenied first passPrior periodMovementOutside noise band
           
           

The definition this sheet holds itself to

Clean claim rate is claims adjudicated on first pass with no edit, no rejection and no denial, over claims submitted. Three separate failure modes sit in the denominator, and a rate that rises because one of them was reclassified has not improved.

Why the noise band column exists

A metric that moves every month is a metric nobody acts on. The band is set once per metric in the definitions document, and only a movement outside it goes on the review agenda. Everything inside it is recorded and left alone.

The other three sheets

Days in AR, denial rate by payer with cash at risk, and net collection rate, each per payer and each carrying its own denominator. Four metrics is the whole dashboard. A fifth is usually a metric somebody wanted rather than a decision somebody makes.

A practice-wide clean claim rate of 88.7 percent and 33.2 days in AR is a pair of unremarkable numbers. Computed per payer, the same quarter contains a payer at 82.7 percent and 44.5 days, and that payer is a quarter of the charges. So every metric in this pack carries a payer on the row and its own denominator beside it. An aggregate is an average of four different relationships, and the averaging is what hides the one relationship that has moved. Ranking the payers is what makes the numbers arguable instead of merely reported.

Two of the four metrics lead and two lag. Clean claim rate and denial rate by payer are measurable the week a claim goes out, and they set what the next quarter's cash will be. Net collection rate tells you what happened, months later, and it is provisional until runout closes. So the sheets state months of runout on the row and compare against a like-aged prior period, rather than against the most recent closed quarter.

Then one derived column turns the leading pair into money: cash at risk, which is denied charge times one minus that payer's own appeal recovery rate. At Bellhaven Family Health, Summit Advantage is 26.3 percent of charges and 64.4 percent of the 59,375 at risk, because it denies at 12.9 percent and overturns 38 percent of appeals. Which denial categories to work is denial root cause analysis.

A quarter where three payers each needed a different action

The two leading metrics ranked against each other, denial rate converted to cash at risk, and the lagging metric with its runout stated.

Clean Claim Rate and Days in AR

Illustrative figures for a fictional practice, Bellhaven Family Health, 2026 Q1. Both metrics per payer, both ranked, with each payer's share of charges alongside so the ranking can be weighted.

PayerSubmittedFirst pass cleanClean claim rateRankEnding ARDaily chargeDays in ARRankCharge share
Medicare1,8401,71293.0%1118,4004,584.4425.8140.4%
Horizon Medicaid56051291.4%241,9001,070.0039.239.4%
Ridgeline Health98084386.0%384,3002,712.2231.1223.9%
Summit Advantage1,12092682.7%4132,6002,982.2244.5426.3%
All payers4,5003,99388.7% 377,20011,348.8933.2 100%

Read the two rank columns together. Best and worst first-pass rates are also best and worst days in AR, which is the relationship the whole dashboard exists to expose. The two middle payers swap, and the swap is the finding rather than noise: Horizon Medicaid submits second-cleanest at 91.4 percent and still sits third at 39.2 days, so that delay is payer behaviour the practice cannot fix by submitting better. Ridgeline submits less cleanly and turns around faster. The aggregate row is the reason to compute per payer at all: 88.7 percent and 33.2 days are unremarkable, and they conceal a payer at 82.7 and 44.5.

Denial Rate by Payer

Denial rate is per line rather than per claim, because a claim with one denied line of six is not a denied claim. The right-hand columns turn the rate into a cash number using the practice's own appeal history.

PayerLines adjudicatedLines deniedDenial rateRankDenied chargeLargest code pairLines on itAppeal recoveryCash at risk
Medicare3,6101413.9%118,300CO-16 with N2903871%5,307
Horizon Medicaid1,080625.7%26,800CO-27 coverage terminated1762%2,584
Ridgeline Health1,9101688.8%329,400CO-45 charge exceeds fee schedule5155%13,230
Summit Advantage2,24028912.9%461,700CO-197 authorization absent9438%38,254
All payers8,8406607.5% 116,200   59,375

Cash at risk, and the concentration it exposes

Cash at risk is denied charge times one minus that payer's own historical appeal recovery rate. It is the money the practice expects to lose rather than the money currently unpaid.

PayerShare of chargesShare of cash at riskRatio
Summit Advantage26.3%64.4%2.4x
Ridgeline Health23.9%22.3%0.9x
Medicare40.4%8.9%0.2x
Horizon Medicaid9.4%4.4%0.5x

Summit Advantage is a quarter of the charges and nearly two thirds of the expected loss, because it denies at 12.9 percent and overturns only 38 percent of what gets appealed. Medicare denies 141 lines and keeps only 5,307 at risk because 71 percent come back. A dashboard that reports denial rate and stops treats those two as the same kind of problem.

Net Collection Rate

The lagging metric, and the only one on the dashboard that is provisional when first computed. Every row states how many months of runout it includes and is compared against a like-aged prior period rather than the most recent closed quarter.

PayerGross chargesContractual adjustmentsNet chargesPaymentsNet collection rateRunout monthsPrior like-agedMovement
Medicare412,600168,300244,300236,90097.0%397.4%-0.4
Ridgeline Health244,10096,800147,300140,20095.2%395.6%-0.4
Horizon Medicaid96,30051,70044,60042,10094.4%394.0%+0.4
Summit Advantage268,400119,600148,800138,70093.2%395.1%-1.9
All payers1,021,400436,400585,000557,90095.4%396.0%-0.6

What the four metrics say together, per payer

PayerClean claimDays in ARDenialNet collectionOutside noise bandWhat the quarter licenses
Summit Advantage82.7%44.512.9%93.2%Yes, on two metricsA contract conversation. Worst on all four, and the appeal path recovers least.
Horizon Medicaid91.4%39.25.7%94.4%NoAn escalation, not a submission fix. The claims are clean and the payment is slow.
Ridgeline Health86.0%31.18.8%95.2%NoA submission fix. The code pair names the missing element.
Medicare93.0%25.83.9%97.0%NoNothing. Record it and move on.

Three payers, three different actions, and getting the action wrong is expensive in both directions. Telling the billing team to submit more cleanly to Horizon Medicaid wastes effort on a payer already at 91.4 percent. Escalating Ridgeline's speed ignores that its own 86.0 percent first-pass rate is what is slowing it. Only Summit is outside the noise band, on two metrics, which is why it is the one item on the agenda.

What's in the pack

01

Metric Definitions

The numerator and denominator of each of the four metrics, written down, plus the noise band that decides whether a movement reaches the agenda or is recorded and left alone.

02

How Clean Claim Rate Predicts Days in AR

The one relationship that makes the dashboard worth building, the two payers that swap rank and why that is informative, and the three separate actions a finding can license.

03

Clean Claim Rate

Per payer, with clearinghouse rejections, pre-adjudication rejections and first-pass denials kept in separate columns so a rate cannot improve by reclassifying one of them.

04

Days in AR

Ending AR over average daily charge on a trailing 90 day base, per payer, with the daily charge shown so a small payer's number is readable as the small denominator it is.

05

Denial Rate by Payer

Per line rather than per claim, with the largest reason and remark code pair, the practice's own appeal recovery rate, and cash at risk derived from the two.

06

Net Collection Rate

Payments over net charges after contractual adjustments, marked provisional, with runout months on the row and a like-aged prior period as the comparison.

07

Review Cadence and Escalation Basis Note

A monthly agenda that reads only the rows outside their band, and the rule that an escalation needs a written obligation behind it rather than a metric.

08

Handoffs from a finding to the work

A payer paying late on clean claims goes to the AR and collections pack. A payer paying the wrong amount goes to the underpayment recovery pack.

How to use it

  1. 1

    Open in River, or download it

    Open the pack in River and let the agent compute the four metrics from your claims and remittance exports, or download the blank Word and CSV files instantly and fill them in.

  2. 2

    Fix the definitions before computing anything

    Especially what counts as clean and what counts as a denied line. A metric whose denominator is not written down will be quietly redefined the first month it looks bad.

  3. 3

    Compute all four per payer, then rank

    Ranking is what makes the numbers arguable. Put each payer's share of charges beside its rank so a bad rate on two percent of the charges is read as what it is.

  4. 4

    Read only the rows outside their band

    Then decide which of three things the row licenses: a submission fix, a payer escalation, or a contract conversation. Those are different actions and the metrics distinguish them.

Frequently asked questions

Is this template free?

Yes. The four documents and four sheets download as Word and CSV files with no signup and no card. "Edit with AI" is the optional path for practices that want the four metrics computed from their own exports. The rest of the library is at the template library.

What format are the downloaded files?

Word documents for the definitions, the clean claim rate note, the review cadence and the escalation basis note, plus CSV for the four metric sheets, zipped into one file. They open in Word, Pages, Google Docs, Excel, Numbers and Sheets with nothing to convert first.

Why only four metrics?

Because each of the four changes a decision, and a fifth usually does not. Clean claim rate and denial rate say what next quarter's cash will be. Days in AR says when money arrives. Net collection rate says whether the practice eventually got what the contracts promised. Anything past that gets reported and never acted on.

What is cash at risk?

Denied charge times one minus that payer's own historical appeal recovery rate, computed from your appeal outcomes rather than an industry figure. It converts a denial rate into the money you expect to lose, which is why a payer overturning 71 percent of appeals and one overturning 38 percent stop looking comparable.

Why compare against a like-aged prior period?

Because net collection rate rises for months after a quarter closes as runout arrives. Comparing a three-month-old quarter against a fully run-out one manufactures a decline that is not there. Each row states its runout months so the comparison is between two numbers of the same maturity.

Can we escalate a payer using these numbers?

The numbers identify which payer, and then the escalation needs a written obligation rather than a metric. Two exist by regulation: a Medicare Advantage contract must provide that the plan pays 95 percent of clean claims within 30 days for the claim types named there.

Does the same obligation exist for Medicaid?

For claims paid by the state agency, yes, and the thresholds are different again. The agency must pay 90 percent of clean claims from practitioners within 30 days of receipt, and 99 percent within 90 days. Managed Medicaid runs through the plan contract instead, so read that before writing.

Find out which payer is dragging both numbers

Send a claims export, a remittance file and your appeal outcomes. The first thing back is the four metrics per payer, ranked, with cash at risk derived from your own recovery rate.

Edit with AI