Practices are becoming more efficient these days, thanks to health information technology software, and these systems have the potential to improve accounts receivable services as well.
Currently, hospitals and doctor's offices handle a massive amount of information. Depending on the size of the facility, details on a patient's medical history could be in the hundreds, even thousands of people. Within these records, some of these accounts could be an example of health care fraud, and you may not even notice.
As health care becomes more digital, hospitals and doctor's offices can weed out fraudulent accounts through the use of Big Data. This technology is being used in many sectors, notably social media, through predictive modeling. Forbes Magazine contributor Steve Culp wrote that this can "detect potential fraud as early as possible in the claims process."
"Although predictive modeling is not new to fraud prevention, it can be highly effective when combined with other analytical tools as part of a concerted global effort," Culp explained.
Traditionally, accounts receivable services use the "pay and chase model" to process claims, but in Massachusetts, the state's investigators found much more success using predictive modeling — recovering $2 million in claims within six months, GCN Tech reported.
The program is fairly new in the Bay State, but Joan Senatore, director of the Massachusetts Medicaid Fraud Unit, found that they have been able to recover payments that were issued to beneficiaries who were dead or no longer a part of the federally-funded system.
Predictive modeling helps the state identify historic patterns, which in turn can applied in real-time — claims can immediately be rejected or put on hold for further investigation. The disadvantage of utilizing Big Data to detect fraud is that learning how to apply these data sets takes a significant amount of time.
If your hospital or practice plans on implementing this solution, but may not have the resources to train these staff members, consider outsourcing medical claims management. This solution will ensure backlog remains low while employees are learning.