- how long it takes to code a claim correctly
- how fast it take to bill a claim to the payer
- profitability stats
- first-pass resolution rate
- days in accounts receivable
- percentage of account receivable > 120 days
- net collection rate
- average reimbursement per encounter
- denial rates
When your organization is able to monitor these type of stats, you are able to ensure that you do not have issues that need to be addressed. Problems with these stats can indicate problems with revenue flow.
It is always best to have some frame of reference to know if your organization is operating efficiently. The more efficient an organization is, the more profitable.
- First-Pass Resolution Rate
This is claims that are paid the first time they are submitted. This should be 90% + Standard Calculation: Total Number of Claims Paid / Total Number of Claims Submitted - Days in Accounts Receivable
This is how many days it takes for a claim to be paid. This should be below 50 days, but 30-40 day range is more desirable.
Standard Calculation: (Total Current Receivables – Credits)/Average Daily Gross Charge Amount - Percentage of Account Receivable > 120 Days
Less than 25% of accounts receivable should be in >120 days bucket.
Standard Calculation: Dollar Value of A/R> 120 Days / Dollar Value of Total A/R - Net Collection Rate
This is also known as “adjusted collection rate.”It is the percentage of total potential reimbursement collected out of the total allowed amount. This should be above 95%.
Standard Calculation: (Payments – Credits) / (Charges – Contractual Adjustments) - Average Reimbursement per Encounter
There is no standard for this industry wide, but it is an important statistic to track.
Standard Calculation: Total Reimbursement / # of Encounters in a Given Time Period - Denial Rate
This should be below 20% at most, but should be 5-10% for an ideal. Standard Calculation: Total Denied Items / Total Claims Filed to a Payer
Tracking these type of stats will allow any existing problems to be identified and addressed. It will also allow for comparison before and after the ICD-10 conversion so that any problems created by the conversion can be quickly fixed. It is very important to start tracking these stats now. Without a baseline for comparison, determining any problems created by the ICD-10 conversion will be very difficult, if not impossible.
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