5 Key Metrics You Will Want to Monitor During PM System Implementations

kathywilliamson-whBy Kathryn Williamson, Hayes Management Consulting
Twitter: @HayesManagement

Practice Management Systems are evolving constantly in response to regulatory changes in healthcare and improvements in technology. It is not uncommon for organizations to rush into the purchasing of a new system thinking it will be an immediate fix to a number problems they might be currently experiencing—from workflow to revenue issues. Sometimes organizations may find out after the fact that their issues stem from business management inefficiencies, workflow inefficiencies, or a lack of monitoring of key revenue data. Are you planning on implementing a new practice management system?

If so, it is important to understand your current business first. Monitoring certain key revenue cycle metrics will help guide the build phase of your new implementation, ensuring your organization will get the expected metrics out of the new system at go-live. Monitoring of key metrics should continue during all implementation phases as well as throughout the life of your practice.

It is important to establish processes to monitor the following key metrics to understand the current baseline for your practice. These measurements should be taken at least 6-8 months prior to the implementation of your new system:

  1. Claims Denial Rates: Claims denial rates are the percentage of claims adjudicated and denied by payors. A low denial rate indicates a healthy cash flow. To calculate the claims denial rate; sum the total dollar ($) of claims denied by a payor and then divide by the total number (#) of claims denied by the payor. In 2012, HFMA established a benchmark of 6.3% and MGMA established an acceptable rate of 7.37%.
  2. Claims Rejection Rates: Claims rejection rates are the percentage of non-adjudicated claims that are not accepted by a payer at first pass as they have not met specific payor requirements.
  3. Days in A/R: This measurement calculates how long it takes for a service to be paid by all payers. Most practice management systems deliver Accounts Receivable reports. Monitoring this metric is very important to any healthcare organization because it demonstrates the average number of days that A/R is unpaid. This calculation can be payor specific. If you track this data prior to a major organizational change, such as a system change; identifying problem payors will be easier to track during and after the change. Best practice guidelines suggest A/R over 90 days should be no more than 17-20% of total A/R and 10-12% over 120 days.
  4. Adjusted Collection Rate: Adjusted collection rate is the percentage of collected reimbursement as compared to the allowed amount. This calculation indicates the effectiveness of a practice’s ability to collect legitimate reimbursements. To calculate this rate take the payments minus credits and divide by the charges minus contractual adjustments. Basically, an adjusted collection rate of less than 95 percent is identified as poor. HFMA has identified a high performer rate of 98% while MGMA identified a high performer rate of 97.07% (2013).
  5. Charge Lag: This measurement is calculated as the number of days from service date to the date it was posted in the practice management system. Depending on whether you are a hospital or a physician group HFMA outlined the following benchmark guidelines in 2013:
    1. In hospital settings the acceptable lag rate is 10 days for non-surgical charges, 4 days for consult charges, and 6 days for surgical charges.
    2. For physician groups the acceptable charge lag rate is 2-6 days.

Ensuring the establishment of critical data baselines prior to any system implementation is essential for ensuring a successful transition. It is one of the ways an organization can fully understand and evaluate the efficiency of the switch to the new system. Keeping a finger on the pulse of your business will allow for the evaluation, and successful correction, of dips in performance should they occur post go-live.

This article was originally published on Hayes Management Consulting and is republished here with permission.