Pharmaceutical drug fraud a 360 degree hurt to US economy that also includes $60 Billion Medicare fraud and Money Laundry. They defeat the drivers of genomics, mHealth, TeleHealth innovations. Random samples are drawn from large samples and analyzed mathematically (calculus, Regression etc)
Mathematics of Outlier Detection and Pattern Recognition: Pharmacy Fraud •Product: MED-DETECTION •Pharmaceutical drug non-adherence causes $290 Billion additional cost of care in USA. •Pharmaceutical drug reimbursements drive genomics innovation, care for chronic diseases and car accident patients, Central to mHealth and Tele-health initiatives. •Pharmaceutical drug fraud by patients, pharmacists and providers create 360 degree Economic Hurt that also includes
Transcript
Mathematics of Outlier Detection and Pattern Recognition: Pharmacy Fraud
•Product: MED-DETECTION•Pharmaceutical drug non-adherence causes $290 Billion
additional cost of care in USA. •Pharmaceutical drug reimbursements drive genomics innovation, care for chronic diseases and car accident
patients, Central to mHealth and Tele-health initiatives. •Pharmaceutical drug fraud by patients, pharmacists and
providers create 360 degree Economic Hurt that also includes $60 Billion Medicare Pharmacy Fraud and Money Laundry.
•Complex Behavior: Mathematics Needed!
Sample 1: CMS Data Released in 2013: waves on right side (2010)
Sample 2: Mathematics extracted only 6% data as outlier: Pattern Continues…
Sample 3: 8 random samples were found from 450k data. All samples different in 2010.
Sample 4: Quantity dispensed to 360 units, Days supply to 180 days and Patient Payment to $570 in 450K data: note the right
side in 2010, likely due lower DAYS_SUPLY_NUM.
Sample 5: Mathematical Equations were used for segmentation; note left (2008-2009) VS right (2010) data.
Sample 6: Patient paid_$ also decreased in right side of pane (2010) in all samples; plan looses $.
Sample 7: same pattern all over here; more intense in 2010.
Sample 8: 2008-2009 Learning the fraud and, 2010 Execution of fraud.
2010 data separated from 2008-09 data and analyzed: Prescription drug fraud!
The circle on right is very high quantity dispensed at low price… Why?
Look at the hole in middle-why? Zero supply days for some money, nice!
CONCLUSIONS: REAL TIME ANALYTICS: STORE AND ANALYZE ONLY WHAT IS NEEDED. SHAVE COSTS OFF!
• High- Low Fraud Condition: Low drug quantity sold for high price and high drug quantity sold at low price in order to stay below the radar. •It all adds up- 1000 times $10 per capsule is > than 50 times $100/ tablet. You make money from Fraud! •Similar pattern for Days_supply:- 30 days is more frequent than 90 days for the same price. Helps to make money more frequently from fraud. •Very few patients showed up for 60 Days_supply! Many of the same patients from 30 days showed up in 90 days supply to raise no suspicion….
TECHNICAL PRESENTATION OF NAVIN KUMAR SINHA, DOUBLE CHECK CONSULTING: 952-905-6636 ([email protected]). PUBLIC VIEW: AS WITH OTHER PRODUCTS OF DOUBLE CHECK CONSULTING (DATAVISIONS AND DATACONNECTIONS), THIS IS ALSO PUBLIC VIEW OF MED-DETECTION PRODUCT. THERE IS LOT MORE HERE BUT PUTTING 500 SLIDES IS INCONVENIENCE TO ALL. THANK YOU FOR YOUR TIME AND INTERESTS. MATHEMATICS IS BEAUTIFUL- CHEERS!
