April 5, 2006
If an automated system can accurately classify, in advance, what group of patients is going to pay hospital bills almost 98 percent of the time, would this be of use to you? The February 2006 issue of HFMA's Revenue Cycle Strategist newsletter takes a look at the use of technology, based on scientific algorithms, to "model" consumers for collection activity. Such strategies have been in widespread commercial use for well over 30 years.
Reducing Bad Debt and Collection Costs
Every major sector of business, except health care, has sought to understand consumer payment methods and then revamped collection efforts based on this information. This effort was undertaken for two reasons. First, commercial businesses want to minimize writing off accounts to bad debts and, second, commercial businesses do not want to waste collection resources.
Many healthcare providers have relied on collection agencies to collect on unpaid accounts. In the meantime, write-offs have skyrocketed, and the hospital industry has been depicted negatively for some collection practices used with uninsured and underinsured patients.
Front-End Technology
As revenue cycle focus shifts from the back end to the front end, hospitals would benefit from implementing new technology that can predict payment. This technology can help hospitals tailor their collection approach according to whether patients have a high probability of paying or a low probability of paying. The business world outside of health care uses such technology to make this distinction.
Support for Patient Financial Counseling
Like for-profit businesses, not-for-profit healthcare providers need to operate in a businesslike manner. Many healthcare providers are now implementing state-of-the art prediction of payment technology in the front end of their revenue cycle operations. The technology is not used to decide who gets treatment; rather, providers are using it during registration and financial counseling processes to identify account balance resolution opportunities, such as:
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Real-time charity eligibility processing
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Improving demographic validation, registration integrity
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Reclassifying bad debts to charity write-offs
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"Re-screening" accounts already at collection agencies and reclassifying as charity (when applicable)
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Improving front-end and back-end collection productivity due to stratification of accounts based on likelihood of payment and charity screening
Interestingly, the information provided by the technology often is used to help patients understand how they can pay their hospital bills. For example, when financial counselors have access to up-to-date financial information, they can steer patients to charity programs or Medicaid. In addition, financial counselors can show patients how they can pay the bill using outstanding credit card availability. For everyone's benefit, patients who qualify for charity discount programs are enrolled in them right away, on the front end, saving time and money.
Look for a Track Record
Producing a calibrated model that healthcare providers can effectively use is no easy task. It takes a proven algorithm that may be modified continually. After all, this calibrated model is going to be the basis on which collection process decisions are made. Therefore, it is important to use both a vendor that has a proven history and associated case studies that testify to the efficiency of the model.
SOURCE: "Prediction of Payment and the Revenue Cycle," Bruce Nelson, vice president, Search America, February 2006 Revenue Cycle Strategist.
Additional Resources
- Exposure Draft of Revised P&P Board Statement No. 15, Valuation and Financial Statement Presentation of Charity Service and Bad Debts by Institutional Healthcare Providers
- Understanding Your True Cost to Collect
- Today's Charity Care Challenges: What Should You Be Doing?
- HFMA Executive Roundtable: Issues in Up-Front Collections
- More HFMA programs, tools, and articles on revenue cycle improvement
- More HFMA programs, tools, and articles on serving the uninsured
If you have questions or comments about HFMA Wants You to Know, contact editor Laura Noble.
HFMA Wants You to Know ISSN: 1540-0697. Volume V, Issue 8. Copyright 2006, Healthcare Financial Management Association. All rights reserved.