Picture yourself balancing on top of a fence with vast expanses of land, each with their own set of governance, visible to you from both sides. You’re straddling the fence, your legs occupying each of the divided spaces. Where do you stand? It depends on which way the wind blows. Such is the case with Advize Health. As an Audit and Advisory firm working to reduce the cost of healthcare we often find ourselves sitting on the fence of CMS. We’ve approached audit projects for both payers and providers with a focus on medical billing and coding compliance. Many of our clients and leads have approached us to ask who we are trying to get money for. The truth is, we’re trying to stop healthcare fraud and over expenditure, regardless of who the offending parties are. Our objectivity has allowed us to participate in a plethora of legal cases reviewing for fraud, waste, and abuse (FWA).
Most auditing firm legal responsibilities lie within the investigative phase of proceedings. Our expertise in performing dynamic medical record reviews puts us in the optimal position to cooperate with law firms representing all client types. Many health plans can utilize tools to detect overpayments. Some of these tools are pieces of advanced technology, while others observe social media to identify red flags. Social media has proven to be an inexpensive way to identify these warning signs. For example, you may see a dental office promoting free dental exams on their Facebook. These exams may be free to patients, but someone is being wrongfully billed.
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Beyond social media’s superficial revelations, data plays an integral role in the investigation and audit selection processes. Clients have told us that data is both the greatest and the worst part of any investigation. Dealing with data calls for the act of data-mining. In its simplest definition, data mining is the act of examining and analyzing large databases to generate new information. In health plan overpayment and FWA investigations for payers, data-mining can present plans with information on:
- Total amounts billed per provider or facility
- Total number of patient visits
- Average bill sum per patient
- Patient visit frequency
- Average cost of medical testing per patient
- Prescription ratios
Examining these large pools of data can illustrate patterns of abuse. For instance, if a single provider is billing for 50+ patient visits in a day – this is cause for alarm. Data-mining can be performed in house, by the payer using Excel, Access, or ACL software. Another option is to hire an external firm such as Advize Health or Healthcare Fraud Shield. Data-mining can be fully executed using many of the software packages above, but also through the supplementary use of RAT-STATS. RAT-STATS is a statistical software package created by the Office of Inspector General that is used for medical claims reviews. This tool is used by OIG’s Office of Audit Services, some providers, and payers to ensure compliance and accuracy of data. It also plays a large role in provider self-disclosure protocol.
Taking into consideration the needs of our clients, data-mining results, and other extenuating circumstances, we can determine the scope and type of audit being performed for specific legal cases. Some audits that are used to reveal FWA are: RADV, HEDIS, DRG, Quality Improvement, and 5 Star/Medicare Advantage. Upon defining the scope of the audit and executing the project, results will often reveal discrepancies in medical records and billed procedures. These results are used in court proceedings, and the auditing firm may be asked to write reports, testify as Subject Matter Experts, and further cooperate with attorneys.
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