The Meduit Innovation Lab Blog

Are You Wasting Time on Patient Collections?

Posted by Ali Bechtel on Apr 12, 2018 6:00:00 AM
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How are you prioritizing patient accounts before calling on outstanding balances?

Whether you realize it or not, you are making a business decision each time you choose which patients to contact. With payers making it increasingly difficult to file a clean claim and patient responsibility on the rise, your patient finance staff probably doesn’t have much time to dedicate to self-pay collections. Make sure that when they are able to carve out the time for delinquent account follow up they are spending their time wisely by appropriately prioritizing patient accounts.

Quality > Quantity

When you are under pressure to collect more, it may seem best to contact the patients with the highest balances first, but that is not necessarily the case. Rather than trying for quantity, go for quality. There are methods of account scoring available that can help you determine which patients have the highest propensity to pay – or who are most likely to pay. Collecting several small balances from patients who can pay is a much better use of your time than attempting to collect a high balance from a patient who cannot.

Collectability scoring, or patient account scoring, is a process different from the well-known FICO scores used by credit bureaus. Scoring models are rampant in the industry and no two models are the same, but most agree the greatest benefit comes from evaluating information from several sources. Our experience has been that the focus of a great scoring model should be on socioeconomic factors that help determine patient’s ability and willingness to pay rather than their credit capacity, with their payment history at the forefront.

Prioritizing Accounts without Scoring Tools

If you or your current revenue cycle partner do not have access to these scoring tools, it is still possible to prioritize accounts manually. When organizing your call list for the day, review each patient’s file for the following information:

  • Past payment history: Has the patient always paid their bills on time with you in the past, or are they regularly delinquent? This can give you an idea of their ability or willingness to pay their balances with you.
  • Age of the balance: How far past due is the patient’s balance? The older the account is the less likely it is that you will recover your balance in full.
  • Patient satisfaction: How long has the patient been coming to your facility? A patient who has developed a good relationship with your providers and who has always had a great experience is far more likely to pay than a patient who is new or who has had complaints in the past.

When you are reviewing patient accounts for prioritization remember not to focus on balance. Often it is the patients with the lower balances who are more likely to pay, or who have had a more stable payment history with your organization.

Once you have determined which patients to contact, save more time by making sure you are contacting them at the right time and with the appropriate technology, i.e. SMS, email, patient portals, or IVR and dialer technology. Want to learn more about how collectability scoring can help improve your recovery? Our RCM experts have all the answers you need, contact us today.

For more analytics tools you should be using to turn your data into insights that can impact your bottom line, download our free Healthcare Data Analytics & RCM white paper today!

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Written by Ali Bechtel, Meduit Marketing Manager

This information is not intended to be legal advice and may not be used as legal advice.  Legal advice must be tailored to the specific circumstances of each case.  Every effort has been made to assure this information is up-to-date as of the date of publication. It is not intended to be a full and exhaustive explanation of the law in any area, nor should it be used to replace the advice of your own legal counsel. 

Topics: healthcare revenue cycle management, medical debt collections, healthcare KPIs, healthcare data analytics