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Today’s BIG Idea is from a practice in the Midwest who had a payer deny a claim because the pre-authorization was for one day and the day of the procedure moved. Are pre-authorizations giving your practice headaches, too? Listen for ideas from both AthenaPractice and AthenaOne on how to build an exception report to track appointments that may be a problem. The first step is to reliably filter those appointments to only find appointments that need pre-authorization. That may take standardization and consistency from your scheduling team. The second step is to data mine to find appointments without authorization. Some pre-authorizations are based on dates and other authorizations are based on procedure count. Some patients have more than one appointment/procedure that needs authorization. Matching the right authorization to the right procedure takes work. Standardization really helps. The process is not easy, but catching even one procedure that is has a missing or an expired authorization is well worth your time.

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Still thinking about payer transparency data and knowing what your competitors are getting paid?

So am I.

Today’s BIG Idea is an overview approach to what competing medical practices are getting paid. The example is from an orthopedic practice in the Boston area. I took 5 major procedure codes and compared what Anthem is paying competing providers in four counties around Boston. The graphic accompanying the podcast shows orange for the highest contract for the provider I chose and blue for competing practices. This market overview report shows this practice is at the lower end of the scale for all 5 procedure codes. Note that for some codes there is a wide range of maximum contracted amounts and for other codes the range is more narrow. Either way, this practice is toward the bottom of the scale. As I play more with this data, today’s market overview report may be an ideal place to start with this payer transparency data. I said this the past two weeks and I will say it one more time. There is real opportunity in understanding and leveraging this data. Thanks for joining me.

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