Projecting revenues: A by-the-numbers primer


Convincing evidence suggests that, as suspected, managed care companies lack the ability to properly adjudicate claims and pay the contracted amount for services rendered.

Every practice, large and small, should have a sound method to project revenue. Yet most radiology groups have no formal method in place to do so. This lack of revenue projection occurs even though some of the most important decisions made in a practice, such as hiring, depend on future revenue streams.There are many methods that can be used to accurately calculate expected revenue. Just make sure that the selected method does not base projected revenue on previous performance. If it does, you may perpetuate prior errors or inefficiencies and overlook existing problems. Without proper analysis, problems can go undetected and lead to a significant loss of revenue.At year's end, compare actual collections with the projection. Any variables should be explained. Below are two recommended revenue projection methods. These calculations can be used to develop revenue projections for an existing practice or for new hospital sites that the group may be considering. These methods can also be modified and used to develop expected revenue for a new device or imaging center. Either or both can be used to determine projected revenue. Preparing a projection using both methods can add validity to the final adopted projected revenue goal.The first method, the payclass approach, uses gross dollars billed, procedure volume, practice payclass, and collection ratio. The billing data used in this calculation is referred to as primary data as opposed to processed data. Primary data is defined as data used as an input to the billing system. Processed data is data that is reported from the billing system. Any reliance on processed data runs the risk of compounding existing inefficiencies. Some processed data must be used in order to calculate the expected revenue, however. Whenever possible, it is preferable to use primary data.It should be easy to determine gross dollars billed, procedure volumes, and the practice payclass distribution. The collection ratio used in the projection should not be derived from processed data. The collection percentage should be calculated based on the payer contracts that are in place. For example, if the practice sets its fee schedule at three times what Medicare allows, the practice can expect its collections ratio on Medicare claims to be 33%. Or, if one of the managed care carriers pays 160% of Medicare, the practice can expect to receive 53% of charges from that insurer. The collection percentage should be determined for each contracted payer. Noncontracted payers should be expected to pay the full fee for procedures. With all of the elements determined, the calculation might look like Exhibit 1. The benefit of the payclass approach is that it is straightforward and produces an accurate result.The second method, the collection analysis approach, uses practice charges, accounts receivables, net payments, and contractual write-offs, as illustrated in Exhibit 2. Again, the contractual write-offs should not be derived from processed data. The contractual write-offs should be calculated based on payer contracts in place by the practice. This method not only projects what the practice should collect but also analyzes current performance.

The results obtained from these two calculations should be very close and will indicate optimal collections for the practice. The final result obtained should be used as the revenue projection. At year's end, any variance from the projected revenue should be investigated to determine the cause. Long-term solutions cannot be implemented until the problem is identified. Exhibit 3 illustrates a useful calculation for analyzing collection performance versus projected collections. No projection is perfect and projections must be evaluated based on actual results. A variance does not necessarily indicate an inaccurate projection or poor revenue performance. Revenue could be greater than projected due to increased volume or an increase in Medicare reimbursement. Revenue could be lower than expected due to the loss of a site or service, or a decrease in managed care reimbursement from a new contract signed midway through the year. The key is to determine the cause of the variance, and then take the appropriate action. Exhibit III compares actual results to the initial projections for the period. Any variance should be explainable and factored into revenue projections for the following year.Practices must be able to systemically quantify and determine the extent of billing and revenue problems, in order to develop long-term solutions or monitor problems to verify that solutions in use are effective.Mr.Reinitz is president of Comprehensive Medical Data Management in Powell, OH. He can be reached at

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