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1 / October 2008 / SGS INTERNAL
Network Detection and AnalysisKaren PainterSandra Dorman
Eastern and Pennsylvania Benefit Integrity Support Centers
2 / October 2008 / SGS INTERNAL
Introduction
3 / OCTOBER 2008 / SGS INTERNAL Network Detection and Analysis
Traditional Data Analysis Approaches
•Individual providers
•High dollar billers
•Spike reports
•Top procedure codes
•Individual specialties
4 / OCTOBER 2008 / SGS INTERNAL Network Detection and Analysis
Current Fraud Landscape
•Fraud schemes are evolving and more sophisticated
•Medical management organizations
•Organized crime rings
•Identity theft
5 / OCTOBER 2008 / SGS INTERNAL Network Detection and Analysis
Network Detection and AnalysisTraditional Approach
6 / OCTOBER 2008 / SGS INTERNAL Network Detection and Analysis
Our Approach - FUSION Model
•Fraud Detection
•Utilization
•Statistical Models
• Integration
•Overpayment
•Network Analysis
7 / October 2008 / SGS INTERNAL
Network Detection Examples
8 / OCTOBER 2008 / SGS INTERNAL Network Detection and Analysis
Utilization Detection - Beneficiary Sharing
•Started with a known provider group suspected of sharing beneficiaries
•Gathered all data on the beneficiaries
•Identified 3,947 providers and 1,487 beneficiaries
•Identified 274 providers and 541 beneficiaries through a dense cluster analysis
9 / OCTOBER 2008 / SGS INTERNAL Network Detection and Analysis
Beneficiary Sharing - Analysis and Findings
10 / OCTOBER 2008 / SGS INTERNAL Network Detection and Analysis
Utilization Detection - Husband/Wife
•Found 1,800 instances of husband/wife beneficiaries– Receiving the same procedure
– With the same diagnosis
– On the same date of service
– With the same provider
•48 providers rendered services to these pairs
•One pair had a total of 22 different diagnosis codes
•Total Paid $425,256
11 / OCTOBER 2008 / SGS INTERNAL Network Detection and Analysis
Husband/Wife – Analysis and Findings
HIC Bene First
NameBene Last
Name
Bene Gender Desc
Claim First
Date of Service
Rendering Prov Name
Referring Prov Name
Line Dx
Code CPT
Bene Current Street 1
Adr
Bene Current Street 2
AdrPaid Amt
HIC1 Jane Doe FEMALE 01/05/07 Physician A Physician A 7390 98927123 Main
StAPT 3H $45.54
HIC2 John Doe MALE 01/05/07 Physician A Physician A 7390 98927123 Main
StAPT 3H $45.54
HIC3 Minnie Smith FEMALE 01/02/07 Physician B Physician C 7393 98942987 Smith
StAPT 4G $38.85
HIC4 Mickey Smith MALE 01/02/07 Physician B Physician C 7393 98942987 Smith
StAPT 4G $38.85
HIC5 Fannie Jones FEMALE 11/28/07 Physician D Physician D 4280 99213456 South
StAPT C-4 $55.69
HIC6 Fred Jones MALE 11/28/07 Physician D Physician D 4280 99213456 South
StAPT C-4 $55.69
12 / OCTOBER 2008 / SGS INTERNAL Network Detection and Analysis
Utilization Detection - Ambulance
•Identified Beneficiaries with transports of 5 or more different ambulance companies per year
•Identified transports to nowhere
•Currently under law enforcement investigation
13 / OCTOBER 2008 / SGS INTERNAL Network Detection and Analysis
Ambulance – Analysis and Findings
14 / OCTOBER 2008 / SGS INTERNAL Network Detection and Analysis
Utilization Detection - Laboratory
•Laboratories identified through ‘traditional’ spike models
•Analysis of referring providers uncovered suspect relationships
•Comparison of laboratory claims/diagnosis and treatment by the referring provider uncovered inconsistencies
15 / OCTOBER 2008 / SGS INTERNAL Network Detection and Analysis
Laboratory – Analysis and Findings
0
100,000
200,000
300,000
400,000
Lab Referring Provider
LAB Referring Provider
• Trend of laboratory and referring provider relationship
16 / OCTOBER 2008 / SGS INTERNAL Network Detection and Analysis
Utilization Detection - Physical Therapy
•Started with all beneficiary and provider combinations for PT (97110)
•Narrowed dataset to instances where beneficiaries saw 5 or more providers for 97110 within 1 year
•Identified a set of 522 providers
•Identified 318 beneficiaries
17 / OCTOBER 2008 / SGS INTERNAL Network Detection and Analysis
Physical Therapy – Analysis and Findings
• Trend of Diagnosis Code for Group billing PT & OT
0
20
40
60
80
Jan-0
6
Mar-06
May-06
Jul-0
6
Sep-06
Nov-06
Jan-0
7
Mar-07
May-07
Jul-0
7
Sep-07
Nov-07
Jan-0
8
Mar-08
Diagnosis Trend PT/OT Group
7245
7242
7231
7197
71516
71511
18 / OCTOBER 2008 / SGS INTERNAL Network Detection and Analysis
Utilization Detection - OT and PT Same DOS
•Beneficiaries who received occupational therapy and physical therapy on the same day
•Analysis on 3 month period
•A total of 308 providers were identified
•A total of 753 beneficiaries
19 / OCTOBER 2008 / SGS INTERNAL Network Detection and Analysis
OT and PT Same DOS – Analysis and Findings
20 / OCTOBER 2008 / SGS INTERNAL Network Detection and Analysis
Utilization Detection – Identity Theft
•Approach was to look for beneficiaries that had a sudden increase in the number of carriers
•Looked for a spike in payment for our beneficiaries out of state
•Looked for out of state beneficiaries in our jurisdiction
21 / OCTOBER 2008 / SGS INTERNAL Network Detection and Analysis
Identity Theft – Analysis and Findings
22 / October 2008 / SGS INTERNAL
Statistical Models
23 / OCTOBER 2008 / SGS INTERNAL Network Detection and Analysis
Spike Model
•Goal is to identify providers with a large increase (spike) in dollars paid
•Compare one recent month with a calculated baseline average (Previous 6 or 12 months)
• Identify providers with a 100% increase and a minimum of $50,000 paid in current month
24 / OCTOBER 2008 / SGS INTERNAL Network Detection and Analysis
Spike Model - Example
25 / OCTOBER 2008 / SGS INTERNAL Network Detection and Analysis
Outlier Model
•Goal is to identify providers that are not like their peer group (i.e. same specialty)
•Two complex variables are considered:
– Dollars per patient
– Patients per day
26 / OCTOBER 2008 / SGS INTERNAL Network Detection and Analysis
Outlier Model – Dollars per Patient Example
0 60 120 180 240 300 360 420 480 540
0
5
10
15
20
25
30
Mean = 148.29Median = 110.90Standard Deviation = 106.09Threshold for Outliers using Quartile Method = 403.28Threshold for Outliers using a Z-Score of 2 = 360.47Threshold for Outliers using a Z-Score of 3 = 466.56
27 / OCTOBER 2008 / SGS INTERNAL Network Detection and Analysis
Outlier Model – Patients per Day Example
3 9 15 21 27 33 39 45 51 57 63 69 75 81 87 93 99 105
0
10
Mean = 9.88Median = 6.79Standard Deviation = 9.58Threshold for Outliers using Quartile Method = 28.49
28 / OCTOBER 2008 / SGS INTERNAL Network Detection and Analysis
Trend Model
•Goal is to find providers that may not have ‘spiked’ but have had a statistically significant increase over a six month period
•Trend is evaluated on two complex variables
– Dollars per patient
– Patients per day
29 / OCTOBER 2008 / SGS INTERNAL Network Detection and Analysis
Trend Model – Dollars per Patient Example
30 / OCTOBER 2008 / SGS INTERNAL Network Detection and Analysis
Trend Model – Dollars per Patient Example
Trend ModelDollars per Bene for a Specialty 18 Provider
31 / OCTOBER 2008 / SGS INTERNAL Network Detection and Analysis
Static Model
•Goal is to identify providers that consistently bill the same set of procedure codes
•For example: office visit, blood test, urine test, for each beneficiary
•Potential to expand to diagnosis codes or other parameters
32 / OCTOBER 2008 / SGS INTERNAL Network Detection and Analysis
Static Model - Example
33 / OCTOBER 2008 / SGS INTERNAL Network Detection and Analysis
Logistic Regression Model
•Goal is to identify providers with a similar profile of known fraudulent/abusive providers
•Create a model based on historical data and then apply this model to current data
•Providers with patterns similar to providers already found to be fraudulent are flagged for review
34 / OCTOBER 2008 / SGS INTERNAL Network Detection and Analysis
Logistic Regression Model - Example
35 / OCTOBER 2008 / SGS INTERNAL Network Detection and Analysis
Integration of Statistical Models
Provider SPCSpike Aug07
Trend - $$/Bene
Trend - Benes/Day
Outlier - $$ /Bene
Outlier- Benes/
Day
Static Utilization
of CPT Codes Complaints SUM $$ Pd Comments
A 11 1 1 1 3 $ 626,121 Active Case
B 08 1 1 1 3 $ 173,631
C 18 1 1 2 $ 142,829
D 30 1 1 2 $ 130,000
E 65 1 1 2 $ 150,000
F 11 1 1 2 $ 120,355 Active Case
G 83 1 1 2 $ 109,722
36 / OCTOBER 2008 / SGS INTERNAL Network Detection and Analysis
Our Approach - FUSION Model
37 / OCTOBER 2008 / SGS INTERNAL Network Detection and Analysis
Results
•70+ Fraud Investigations
•15 Referrals to OIG
•Approx $5.1 million identified overpayments
•Approx $4.2 million in pre-payment savings
38 / October 2008 / SGS INTERNAL
Questions??
39 / October 2008 / SGS INTERNAL
SafeGuard Services, LLC225 Grandview AvenueCamp Hill, PA 17011717 975 [email protected]