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)

1. 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!

2. Sample 1: CMS Data Released in
2013: waves on right side (2010)
X-axis:SRVC_DT: January 2008 to December 2010
Quantity Dispensed
Days Supply Number
Patient Paid Amount
SRVC_DT

3. Sample 2: Mathematics extracted only 6%
data as outlier: Pattern Continues…
x-axis: SRVC_Date: January 2008 to December 2010
QTY_DSPNSD_NUM
DAYS_SUPLY_NUM
PTNT_PAY_AMT
SRVC_DT

4. Sample 3: 8 random samples were found
from 450k data. All samples different in 2010.
0
50
100
150
200
250
300
350
400
SRVC_DATE : January 2008 to December 2010
QTY_DSPNSD_NUM
DAYS_SUPLY_NUM
PTNT_PAY_AMT
SRVC_DATE

5. 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.
Service_Date: January 2008 to December 2010
QTY_DSPNSD_NU
M
DAYS_SUPLY_NUM
PTNT_PAY_AMT

6. Sample 5: Mathematical Equations were used for
segmentation; note left (2008-2009) VS right (2010) data.
0
50
100
150
200
250
300
350
400
SRVC Date: January 2008 to December 2010
QTY_DSPNSD_NUM
DAYS_SUPLY_NUM
PTNT_PAY_AMT

7. Sample 6: Patient paid_$ also decreased in right
side of pane (2010) in all samples; plan looses $.
0
50
100
150
200
250
300
350
400
SRVC_Date: January 2008 to December 2010
QTY_DSPNSD_NUM
DAYS_SUPLY_NUM
PTNT_PAY_AMT

8. Sample 7: same pattern all over
here; more intense in 2010.
0
50
100
150
200
250
300
350
400
Service_Date: January 2008 to December 2010
QTY_DSPNSD_NUM DAYS_SUPLY_NUM
PTNT_PAY_AMT

9. Sample 8: 2008-2009 Learning the
fraud and, 2010 Execution of fraud.
SRVC_Date: January 2008 to December 2010
a1.QTY_DSPNSD_NUM
b1.DAYS_SUPLY_NUM
c1.PTNT_PAY_AMT

10. 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!
y = -0.0319x + 39.565
R² = 0.0114
y = 0.0002x2 - 0.093x + 41.752
R² = 0.0168
y = -2E-06x3 + 0.0012x2 - 0.203x + 44.102
R² = 0.0204
0
50
100
150
200
250
0 100 200 300 400
TOT_RX_CST_AMT
QTY_DSPNSD_NUM
QTY_DSPNSD_NUM Line Fit Plot
TOT_RX_CST_AMT
Predicted
TOT_RX_CST_AMT
Linear
(TOT_RX_CST_AMT)
Poly.
(TOT_RX_CST_AMT)
Poly.
(TOT_RX_CST_AMT)
y = 0.0171x + 36.943
R² = 0.0003
y = -0.002x2 + 0.2324x + 32.778
R² = 0.0027
y = -7E-05x3 + 0.0065x2 - 0.0204x +
34.467
R² = 0.0032
0
50
100
150
200
250
0 50 100
TOT_RX_CST_AMT
DAYS_SUPLY_NUM
DAYS_SUPLY_NUM Line Fit Plot
TOT_RX_CST_AMT
Predicted
TOT_RX_CST_AMT
Linear
(TOT_RX_CST_AMT)
Poly.
(TOT_RX_CST_AMT)
Poly.
(TOT_RX_CST_AMT)

11. 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….

12. TECHNICAL PRESENTATION OF NAVIN KUMAR SINHA,
DOUBLE CHECK CONSULTING: 952-905-6636
(SINHANAVIN@HOTMAIL.COM).
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!
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