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HEALTHCARE FRAUD INVESTIGATION

Healthcare Fraud Investigation

Expertise

Read more at www.integramedanalytics.com

 

Integra Med Analytics is experienced and skilled in the investigation of healthcare fraud and abuse. Using a variety of datasets across different healthcare settings, Integra applies statistical techniques to locate fraudulent activities with confidence. We seek to expose fraud in the healthcare industry and change the way that the industry functions. Some of the areas in which Integra is proficient are examined below, and more details can be found at www.integramedanalytics.com.

Integra FEC Healthcare Fraud Investigation Firm

Types of Healthcare Fraud

  1. Nursing Home Ratings: Although the Centers for Medicare and Medicaid Services releases a star rating for nursing homes to assist the public in choosing a facility for themselves or a loved one, these star ratings are partially based on measures reported by the facilities themselves which leaves them open for manipulation by dishonest facilities. We have shown that these measures are being fraudulently manipulated by facilities in order to get better star ratings and attract more patients. At Integra Med Analytics, we have developed a star rating system that is driven by the data itself and not what facilities report. Our star rating is less susceptible to bias caused by facilities’ self reporting, incorporates Integra’s measures of potential fraud, and provides a more honest assessment of the quality of facilities for patients so they can make better decisions for themselves and loved ones. The star ratings that we have developed are searchable and posted at www.nursinghomereporting.com.

  2. Upcoding: Upcoding is a very common method for fraudulent health care providers to gain more compensation for their services. It involves providers adding codes to healthcare claims for services that they did not provide or swapping codes for services they did provide for higher paying similar codes. The type of upcoding that occurs is specific to different care settings and payment systems that the providers are compensated by. At Integra Med Analytics, we have experience detecting and understanding upcoding in a variety of care settings and payment systems. While upcoding generally does not cause significant patient harm, it represents a large amount of financial harm due to how easy it is for fraudulent providers to add codes to increase revenue. We have also seen that facilities that are upcoding are also willing to cut back on things that impact care, such as staffing levels, resulting in worse patient care. 

  3. Skilled Nursing Fraud: Skilled nursing facilities provide stays for patients who require a level of intensity of care lesser than inpatient hospitals but greater than could be provided in an at home setting. At Integra Med Analytics, we have investigated skilled nursing fraud extensively from multiple angles. Skilled nursing facilities often get paid under complicated reimbursement systems that allow for upcoding across multiple different dimensions, and we have developed methods to identify potentially fraudulent manipulation of these different aspects of the patient's record. In addition, skilled nursing facilities commonly falsely report information that is then used for quality measure by the Centers for Medicare and Medicaid Services, which provides a skewed impression of the facilities to patients. Integra is adept at working with large quantities of detailed data in this setting and compiling this data to create actionable insights. Much of the potential fraud in the skilled nursing space is either to cover up patient harm or results in patient harm directly, so Integra Med Analytics’s work in this area directly affects both patient care and financial fraud. Integra has been very successful and active in this area of fraud by filing several qui tam lawsuits, some of which are still ongoing. 

  4. Unnecessary Treatment: Providers can give treatment to patients that is not medically necessary given the patients’ conditions in order to increase reimbursement and profit. This type of fraud can take several different forms such as unnecessary admission to a particular care setting, keeping an inpatient patient for longer than recommended, or performing procedures that do not benefit the patient. There has recently been a significant push to place patients in the least restrictive care setting for their condition, which is intended to be tailored to specific patient needs as well as being more economically efficient. Unnecessarily admitting a patient to certain care settings decreases the patients quality of life and results in large, unjustified payments to these providers. Integra can detect these unnecessary admissions with a variety of statistical methods and datasets. Manipulating length of stay is also a main method by which healthcare providers can increase profitability. This can involve keeping patients for longer in a particular setting in order to extract the most per-diem payments, or it could involve keeping patients a number of days just over a particular cutoff at which the compensation changes dramatically. Integra Med Analytics understands the ways the length of stay is manipulated by facilities with respect to the different payment systems and has utilized statistical techniques to detect this manipulation. In addition to increasing payments to providers, length of stay fraud has a significant impact on patient outcomes since it necessarily involves keeping patients less than or greater than what would be the ideal number of days for each patient's condition. Keeping patients extra days increases the likelihood that the patient acquires an infection or other negative conditions such as bedsores. Working to uncover and expose length of stay fraud improves patient well-being and decreases wasted financial and healthcare resources. Lastly, some providers will perform extra procedures that would not be advisable given the patients’ conditions. This hurts the health of the patients due to risks inherent to medical procedures as well as representing an unnecessary payment to a provider. 

  5. Medicare Claims Data Fraud: Integra Med Analytics is very experienced at working with Medicare claim data across all covered care settings. We understand the different reimbursement methods by which providers are paid under Original Medicare. Each care setting’s payment methodology provides different incentives for fraudulent actors to exploit. We are able to recognize these adverse incentives and develop methods to detect facilities or hospital systems that are taking advantage of these weaknesses in the reimbursement process. Also, by connecting various types of Medicare claims, we are able to develop a rich timeline of a patient as they move to different care settings. This allows us to identify parts of a patient's history that are abnormal and potentially fraudulent when viewed in light of their other healthcare claims. One successful instance of this type of analysis is using patients who went to an inpatient hospital after a skilled nursing stay to uncover severe underreporting of health conditions like bedsores or catheters at the skilled nursing facility in order to improve their quality rating. This is just one part of the analysis that has gone into our improved quality ratings for skilled nursing facilities mentioned above. Integra Med Analytics’s significant experience with Medicare claims positions us to work on any fraud cases involving Medicare, and our experience in this environment will carry over to other types of medical claims data. 

  6. Inpatient Hospital Fraud: We have also done extensive analysis in the acute inpatient hospital setting. We have experience working with the hospital claims data and assessing it for potentially fraudulent diagnosis codes that significantly increase the compensation for the hospital. We have found several hospital systems that had much higher usage rates of specific diagnosis codes that are able to be added to a patient’s claim at a hospital to increase revenue. By examining the patients’ other diagnoses and history, we believe that these were fraudulent claim codes added by the health systems as part of a systemwide method to increase compensation without increased costs. We utilized a variety of statistical techniques to control for patient condition and determine that these codes were likely fraudulent. The payment in this setting is driven by the patient’s diagnosis codes present in the claims, providing the opening for opportunistic systems to easily increase their profit. 

Need to investigate Healthcare Fraud? Contact Integra FEC
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