Deeper Than the Headlines: Proactive Data Mining

Though whistleblower settlements don’t necessarily seem to be slowing down, it does seem that the government is announcing more and more settlements that appear to have originated from government data mining as opposed to whistleblowers.

Last week we wrote about a New Jersey OB/GYN who settled for over $5 million.

That case appears to have originated from data mining by the government.

This week’s Deeper Than the Headlines post also highlights a settlement that appears to have originated from data mining as opposed to a whistleblower. Dr. Duttala Obul Reddy, a psychiatrist in central Illinois, recently settled for over $900,000 regarding allegations of false claims billings.

The government’s complaint, as found in court documents, claims that Dr. Reddy overbilled Evaluation and Management (E&M) codes for services provided in multiple nursing homes. The CPT codes in question were 99307-99310 (subsequent services at a nursing facility). This category is like other E&M code categories, in that the more complex and highest reimbursed code is 99310 while the least complex and lowest reimbursed code of the category is 99307. The government complaint alleged that in an approximately 5-year period, Dr. Reddy reported about 13,850 CPT Codes within the 99307–99310 series and 99.9% of the time he billed the highest reimbursed code of 99310. They claim he only billed a code lower than 99310 nine times while all the other thousands were billed as 99310.

The government’s complaint compared the alleged amount of actual time Dr. Reddy spent seeing patients with the amount of time they felt would be needed to bill the highest code of 99310. For example, they stated,

“Reddy claimed that he provided medical services on June 14, 2012 to sixty-one (61) patients at North Church Nursing & Rehabilitation (“NCR”) and Prairie Village Nursing Home (“PV”) between 7:24am and 9:34am, and from 9:39am to 11:49am, respectively, for a total of approximately 4.33 hours. Reddy billed CPT Code 99310 for all of these patients. Based on the billing of this code for 61 patients, Reddy would have needed approximately 35.5 hours to complete these services.”

This was followed by another example,

“Reddy claimed that he provided medical services on June 28, 2012 to fifty-nine (59) patients at Heritage Manor and Beverly Farms between 7:20am and 7:58am, and from 8:44am to 5:43pm, respectively, for a total of approximately 9.75 hours. Reddy billed CPT Code 99310 for all these patients. Based on the billing of this code for 59 patients, Reddy would have needed approximately 34.25 hours to complete these services.”

By way of demonstrating how it would have been very unlikely for Dr. Reddy to complete complex, time-consuming visits in a short amount of time, the government also claimed the following about the actual amount of time Dr. Reddy spent with patients:

“Reddy visited Mason City Nursing Home monthly. Upon Reddy’s arrival, Reddy discussed his patients with an employee, and then reviewed the patient charts. After reviewing the charts, Reddy, accompanied by a MCNH employee, would spend approximately five (5) minutes with each patient. During that brief patient interaction, Reddy did not take a comprehensive interval history from the patient nor perform a comprehensive examination.”

And another example:

“Reddy visited Heritage Health Nursing Home (“HH”) in Gillespie, Illinois regularly. During those visits, Reddy typically saw five (5) patients, and was present at HH for about thirty (30) minutes. Upon his arrival, Reddy would meet with an employee and they would discuss the patients, review the patient charts, and then Reddy, accompanied by a HH employee, would spend about one (1) minute with each patient face-to-face. During that brief patient interaction, Reddy did not take a comprehensive interval history from the patient nor perform a comprehensive examination.”

Given their analysis of the amounts of codes, type of codes, needed time to perform such codes, it seems the government based their investigation first on a data analysis of claims. None of the court documents mention a qui tam relator (i.e., whistleblower) but rather read as if claims analysis was performed.

In addition to the monetary settlement, Dr. Reddy has agreed to be excluded from the Medicare and Medicaid programs for 10 years while his exclusion from the Illinois Medical Assistance Program will be permanent.

This case highlights the importance of compliance programs to be involved in their own internal data analytics as a part of their regular auditing and monitoring.