Provider Predictive Modeling: Utilizing SNF Data to Mitigate Risk · 2013. 4. 24. · • Was due September 30, 2012 • Issued December 14, 2012 Category $ Millions EstimatedActual

HCCAApril 22, 2013

Provider Predictive Modeling: Utilizing SNF Data to Mitigate Risk

Shawn Halcsik DPT, MEd, OCS, RAC‐CT, CPC, CHCVice President of ComplianceEvergreen Rehabilitation

Paula G. Sanders Esq.Principal & Chair, Health Care Practice

Post & Schell, P.C.

Shawn Halcsik DPT, MEd, OCS, RAC‐CT, CPC, CHC is the VP of Compliance at Evergreen Rehabilitation, a long term care contract therapy provider. In addition to bringing her vast

experience as a physical therapist to the role, she also spent 3 ½ years as a Senior Medical Reviewer at a Medicare PSC where she provided subject matter expertise in coding, reimbursement, documentation, and Medicare regulations to internal and

external customers including FBI, OIG, AG, and AUSA; performed pre/post pay review to identify overpayments, cost savings, and fraud/abuse issues; participated in onsite audits; and provided medical review perspective to data analysis, allegation triage, and special fraud/abuse proactive identification projects.

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Paula G. Sanders, Esq., Principal and Chair of Post & Schell’s health care practice group, focuses her national practice

exclusively on health care law. She represents clients on both substantive and procedural aspects of health facility regulation, such as surveys; licensure; Medicare/Medicaid; compliance; RAC,

MIC, PERM, CERT and ZPIC audits; accreditation; payment matters; HIPAA; fraud and abuse, False Claims Act investigations and voluntary disclosures. She vigorously advocates for her

clients before multiple regulatory and law enforcement agencies and is especially successful at coordinating an integrated

response to her clients’ issues.

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http://www.hms.com/our_services/services_program_integrity.asp

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Objectives• Overview of Center for Program Integrity (CPI) and Fraud Prevention System (FPS)

• Identify SNF claims data used by CMS, FI/MACs, RACs and ZPICs

• Understand how to use your data to perform internal predictive modeling and create your own risk score

• Learn to analyze data and not get caught up in tunnel vision to identify areas of risk

• Be able to answer the question:

“What does my claims data profile say about me?”

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Health Care Fraud and Abuse (HCFAC) Program

• $4.2 billion recovered in 2012 • Return on investment (ROI): $7.90 for every $1• > $23 billion returned to Medicare Trust Fund since 1997

• Department of Health and Human Services & Department of Justice Health Care Fraud and Abuse Control Program Annual Report for Fiscal Year 2012 (2/11/2013); https://oig.hhs.gov/publications/docs/hcfac/hcfacreport2012.pdf

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Center for Program Integrity (CPI)

• Established April 2010 by CMS• Mission is to ensure that correct payments are made to legitimate providers for covered, appropriate, and reasonable services for eligible beneficiaries– Enhance efforts to screen enrolling providers and suppliers

– Detect aberrant, improper, or potentially fraudulent billing patterns and take quick actions against providers suspected of fraud

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Fraud Prevention System (FPS)

• Required by Small Business Jobs Act• Implemented July 2011 to all ZPIC geographic zones

• Analyzes Medicare claims data using models of fraudulent behavior

• Generates automatic alerts on specific claims and providers

• Alerts are prioritized for review and investigation by program integrity analysts

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Fraud Prevention System (FPS)

• Predictive Analytic Model Categories– Rules Based– Anomaly Detection– Predictive Models

• As of July 1, 2012– 14 Rules Based– 8 Anomaly Detection– 3 Predictive

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First Year ResultsCMS Report to Congress

• Was due September 30, 2012• Issued December 14, 2012

Category $ Millions

Estimated Actual Savings 31.8

Estimated Projected Savings 83.6

Total Estimated Savings 115.4

Total Costs 34.7

Estimated Return on Investment: 3.3 to 1

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First Year Results: OIG & GAO Reports

• Did not fully comply with the requirements for reporting actual and projected improper payments recovered and avoided in the Medicare Fee for Service program and its return on investment

• Methodology for savings calculations included some invalid assumptions that may have affected the accuracy of reported amounts (100% fraud)

• CMS has not defined or measured quantifiable benefits or established appropriate performance goals

• Has integrated the FPS into its overall fraud‐prevention strategy but not the payment processing system

• FPS will strengthen the efforts to combat fraud, waste, and abuse in the Medicare Fee for Service program

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First Year Results: GAO Report‐ZPIC Feedback

• FPS has not fundamentally changed the way in which they investigate fraud

• FPS has not significantly sped up investigations or enabled quicker administrative actions– FPS provides broad indicators

• Beware of false positives– Often require additional investigative steps

• Provides data to support analysis of leads• Near real‐time claims data

– Time sensitive interviews– Verification of tips and complaints

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ZPIC Proactive Analysis Beyond FPS

• Peer Comparisons• Weighted Risk Score by provider type• Incorporate Multiple Pieces of Claims Data• Identify Outliers• Identify Trends

• Provider Profiles• Time Studies• Beneficiary Utilization

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What does my claims data profile say about me?

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Build Your Profile & Risk Score

• Build your provider profile– Use the same claim data as CMS, FI/MACs, RACs, and ZPICs

– Consider use of additional non‐claim data to provide contextual and background information

• Determine your risk score– Overall, Part A, Part B– Base on national or state benchmarks when available– Develop internal benchmarks when needed

• Update in response to regulatory changes• Evaluate and Explain

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SNF MEDICARE DATA:Part A

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Two Different Profiles

Provider 1

Total patients

40

Average LOS 60

RU% 93

RV% 6.9

RH% .13

RM% .04

Provider 2

Total patients

5990

Average LOS 26.13

RU% 94.2

RV% 4.0

RH% .90

RM% 1.017

OIG Report 12/2010:Questionable Billing By SNFs

• SNFs increasingly billed for higher paying RUGS from 2006 to 2008 even though beneficiary characteristics remained largely unchanged

• Ultra high therapy RUGS increased from 17% in 2006 to 28% in 2008, resulting in payments increasing by nearly 90% from $5.7 billion to $10.7 billion

• Higher level of assistance with ADLs • For‐profit SNFs

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OIG Report 11/2012:Inappropriate Payments to Skilled Nursing Facilities Cost Medicare More Than a Billion Dollars in 2009

• SNFs billed one‐quarter of all claims in error in 2009, resulting in $1.5 billion in inappropriate Medicare payments. – 20.3% claims were upcoded– 2.5% downcoded– 2.1% did not meet Medicare coverage requirements.

• SNFs misreported information on the MDS for 47 percent of claims– 30.3% Therapy (i.e., physical, occupational, speech)– 16.8% Special Care (e.g., intravenous medication, tracheostomy care)– 6.5% Activities of Daily Living (e.g., bed mobility, eating)– 4.8% Oral/Nutritional Status (e.g., parenteral feeding)– 2.4% Skin Conditions and Treatments (e.g., ulcers, wound dressings)

• CMS should use its Fraud Prevention System to identify and target SNFs that have a high percentage of claims for ultrahigh therapy and for high levels of assistance with activities of daily living.

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SNF Part A Data

• RUGs– Ultra High Therapy*– ADL score

• Length of Stay• Type of Assessment*

– COT

• Discharge Destination• Claim Status/Location (Rejections)

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SNF Part A Data:Benchmarks

FY 2011 FY2012 QTR 1

FY2012 QTR 1 & 2

FY 2012 QTR 1, 2, & 3

Ultra‐High Rehabilitation (≥ 720 minutes of therapy per week)

44.9% 46.7% 46.2% 46.9%

Very‐High Rehabilitation (500 – 719 minutes of therapy per week)

26.9% 27.3% 26.7% 26.2%

High Rehabilitation (325 – 499 minutes of therapy per week)

10.8% 10.4% 10.7% 10.5%

Medium Rehabilitation (150 – 324 minutes of therapy per week)

7.6% 6.3% 6.6% 6.5%

Low Rehabilitation (45 – 149 minutes of therapy per week)

0.1% .1% .1% 0.1%

www.cms.gov/Medicare/Medicare‐Fee‐for‐ServicePayment/SNFPPS/Spotlight.html 21

SNF Part A Data:Benchmarks

FY 2011 FY2012 QTR 1

FY2012 QTR 1 & 2

FY 2012 QTR 1, 2, & 3

Individual 91.8% 99% 99.5% 99.5%

Concurrent .8% 1% .4% .4%

Group 7.4% 0% .1% .1%

Scheduled PPS assessment

95% 85% 84% 84%

Start‐of‐Therapy (SOT) assessment

2% 2% 2% 2%

End‐of‐Therapy (EOT) assessment (w/o Resumption)

3% 3% 3% 3%

Change‐of‐Therapy (COT) assessment

N/A 10% 11% 11%

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SNF Part A Data Benchmarks: Claims Oct 1, 2011 ‐ June 30, 2012

Urban Rural TOTAL % RUX 203,296 22,338 225,634 0.50%RUL 148,881 20,206 169,087 0.40%RVX 91,253 19,128 110,381 0.20%RVL 93,471 18,970 112,441 0.30%RHX 42,607 11,474 54,081 0.10%RHL 41,735 11,947 53,682 0.10%RMX 37,392 10,159 47,551 0.10%RML 21,107 7,184 28,291 0.10%RLX 587 333 920 0.00%RUC 5,660,209 1,137,530 6,797,739 15.30%RUB 7,792,839 1,014,207 8,807,046 19.80%RUA 4,039,536 869,451 4,908,987 11.00%RVC 2,936,944 887,164 3,824,108 8.60%RVB 3,523,930 760,493 4,284,423 9.60%RVA 2,538,725 809,720 3,348,445 7.50%RHC 1,223,998 493,709 1,717,707 3.90%RHB 1,168,021 361,344 1,529,365 3.40%RHA 903,846 427,705 1,331,551 3.00%RMC 816,876 330,825 1,147,701 2.60%RMB 678,292 206,421 884,713 2.00%RMA 542,283 245,630 787,913 1.80% 23

Fac Score *RU%*RU +RV%

RUG days

Site Prod

*Part B avgLOS

Part A avgLOS

Avg$/Claim‐Month‐PT

Avg$/Claim‐Month‐OT

Avg$/Claim‐Month‐ST

Avgunits/visit‐part B‐PT

Avgunits/visit‐part B‐OT

Avgunits/visit‐part B‐ST

*% COT

*YTD % KX

A 30 71.1 100 149 93.10 43.92 75 1384 1316 998 4.01 4.11 1.01 0.00 72.70%

B 24 67.6 90.1 423 90.70 13 43.63 1013 1328 439 4.07 4.08 1.08 0.00 72.70%

C 24 81.6 84.4 179 86.20 37.69 20.67 1083 1276 926 3.82 3.42 1.13 7.10 58.30%

D 24 55.4 80.1 624 83.50 36.1 37.43 1019 800 766 4.16 3.95 1.05 7.30 62.50%

E 17 38.1 78.1 572 88.80 26.27 37.08 884 846 812 3.57 3.6 1.07 0.00 60.50%

F 14 72.1 85 559 91.10 20.93 23.18 730 916 389 3.67 3.43 1.21 10.60 53.60%

G 11 49.5 84.1 327 88.70 16.6 33.54 444 400 872 2.57 2.7 1.06 7.70 37.40%

H 5 18.1 60 1376 83.10 14.52 32.69 669 803 698 2.85 2.79 1.9 14.60 37.30%

Provider Profile

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Red Flags

Facility A

Score 30

RU% 71.1%

RU+RV% 100%

Part A Average Length of Stay

75 days

% COT 0%25

Big Picture vs. Tunnel VisionFacility D F H

Score 24 14 5

RU% 55.4% 72.1% 18.1%

RUG days 624 559 1376

Part A Average Length of Stay

37.43 23.18 32.69

% COT 7.3 10.6 14.6

Facility D: Documentation Review and TMR excellent payment % 26

Two Different Stories

Provider 1

Total patients

40

Average LOS 60

RU% 93

RV% 6.9

RH% .13

RM% .04

Provider 2

Total patients

5990

Average LOS 26.13

RU% 94.2

RV% 4.0

RH% .90

RM% 1.027

SNF MEDICARE DATA:Part B

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2011 Distribution of Spending in Outpatient Therapy by Setting

37.00%

30.00%

16.00%

11.00%

4.00% 2.00%

SNF

PT Private Prac

HOPD

ORF, CORF, & HHA

Phys and Nonphys PP

OT and SLP PP

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OIG Report 12/2010:Questionable billing For OP Therapy

• Medicare expenditures increased 133% between 2000 and 2009 from $2.1 billion to $4.9 billion while the number of Medicare beneficiaries receiving outpatient therapy only increased 26% from 3.6 million to 4.5 million– PT services accounted for 74% ($3.6 billion)– OT services accounted for 19% ($945 million)– SLP services accounted for 7% ($328 million)

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• Average number of outpatient therapy services per beneficiary that providers indicated would exceed an annual cap. OIG calculated the average number of services (units) per beneficiary that had the KX modifier.

• Percentage of outpatient therapy beneficiaries whose providers indicated that an annual cap would be exceeded on the beneficiaries’ first date of service in 2009. OIG identified beneficiaries whose providers billed Medicare using the KX modifier on the beneficiaries’ first date of service in calendar year 2009.

• Percentage of outpatient therapy beneficiaries whose providers were paid for services that exceeded one of the annual caps.

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• Percentage of outpatient therapy beneficiaries whose providers were paid for more than 8 hours of outpatient therapy provided in a single day

• Average Medicare payment per beneficiary who received outpatient therapy from multiple providers. OIG identified beneficiaries who received outpatient therapy from more than one provider in 2009 and calculated the average reimbursement per beneficiary in 2009.

• Percentage of outpatient therapy beneficiaries whose providers were paid for services provided throughout the year. OIG identified beneficiaries who received outpatient therapy during all four quarters of 2009.

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Manual Medical Review (MMR) of Claims > $3,700

• Medicare Administrative Contractors (MACs) will conduct prepayment review until 3/31/2013

• Demonstration project pre‐payment review by RACs (Recovery Audit Contractors) effective 4/1/2013: Florida, California, Michigan, Texas, New York, Louisiana, Illinois, Pennsylvania, Ohio, North Carolina and Missouri

• Post payment review will be conducted by the RAC in the other states

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SNF Part B Data

• KX Modifier Usage*• $3700 = ADR• Length Of Stay*• Units per Visit• Dollars/Claim or Episode*

• Beneficiary Episode #

• Codes Sets Billed (static)

• Claim Status/Locations (rejections)

• Time Code Study*• Functional Limit Reporting

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Medicare Part B Data BenchmarksOutpatient Therapy Spending and Usage in 2011

# TherapyUsers (Million)

Total Spending (Billion)

Share of Spending

Mean Spending Per User

Mean Visits / User

Users AboveCap

Mean Spending on Users Who Exceed Cap

PT 4.3 $4.1 71% $942 1319% $3013

ST .6 $.5 10% $981 12

OT 1.1 $1.1 19% $1026 14 22% $3026

Total 4.9 $5.7 $1173 16

MEDPAC Report November 2012 35

Fac Score *RU%*RU +RV%

RUG days

Site Prod

*Part B avgLOS

Part A avgLOS

Avg$/Claim‐Month‐PT

Avg$/Claim‐Month‐OT

Avg$/Claim‐Month‐ST

Avgunits/visit‐part B‐PT

Avgunits/visit‐part B‐OT

Avgunits/visit‐part B‐ST

*% COT

*YTD % KX

A 30 71.1 100 149 93.10 43.92 75 1384 1316 998 4.01 4.11 1.01 0.00 72.70%

B 24 67.6 90.1 423 90.70 13 43.63 1013 1328 439 4.07 4.08 1.08 0.00 72.70%

C 24 81.6 84.4 179 86.20 37.69 20.67 1083 1276 926 3.82 3.42 1.13 7.10 58.30%

D 24 55.4 80.1 624 83.50 36.1 37.43 1019 800 766 4.16 3.95 1.05 7.30 62.50%

E 17 38.1 78.1 572 88.80 26.27 37.08 884 846 812 3.57 3.6 1.07 0.00 60.50%

F 14 72.1 85 559 91.10 20.93 23.18 730 916 389 3.67 3.43 1.21 10.60 53.60%

G 11 49.5 84.1 327 88.70 16.6 33.54 444 400 872 2.57 2.7 1.06 7.70 37.40%

H 5 18.1 60 1376 83.10 14.52 32.69 669 803 698 2.85 2.79 1.9 14.60 37.30%

Provider Profile

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Red Flags

Facility AScore 30Part B avg LOS 43.92Avg $/Claim‐Month‐PT 1384

Avg $/Claim‐Month‐OT 1316YTD % KX 72.7

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Big Picture vs. Tunnel Vision

Facility DScore 24Part B avg LOS 36.1Avg $/Claim‐Month‐PT 1019

YTD % KX 62.5

Documentation Review and MMR Pre‐authexcellent payment %

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KX3700

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Drill Down on KX and 3700• KX % / $3700 %

– Facility Peer Comparison– Discipline Drill Down– Therapist Drill Down

• MMR ADR Denial Rate– Facility– Discipline– Therapist

• Impacted by Length of Stay, Units/Visit, and Code Sets Billed

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Length Of Stay

0

10

20

30

40

50

60

0 20 40 60 80 100 120

Part B Length of Stay (4/2012‐9/2012)—Average 11.44 visits

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Code Sets BilledDate Range: 7/1/2012 ‐ 9/30/2012 PT OT

Code Description Minutes Units Minutes Units97001 PT evaluation 570 18 0 0

97003 OT evaluation 0 0 165 11

97035 Ultrasound therapy 120 8 0 0

97110 Therapeutic exercises 15965 1065 7115 474

97112 Neuromuscular reeducation 0 0 1935 129

97116 Gait training therapy 4485 242 0 0

97530 Therapeutic activities 9124 663 6245 416

97535 Self care management training 0 0 5705 381

G0283 Electric stim other than wound 535 23 0 0

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18 8

1065

0

242

663

23 0 0 00

200

400

600

800

1000

1200

97001 97035 97110 97112 97116 97530 G0283 97140 97760 97762

Units

Code Sets Billed

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Code Sets BilledProvider Code Set Percent

of VisitsLength of Stay

Time/Visit Visits/Day

A OT: 97110 X 2, 97140 X 2, 97535 x 1, G0283

100% 30 visits 1 hr 15 minutes

80

B OT: 97110 X 2, 97140 X 2, 97535 x 1, G0283


6

C OT: 97110 X 2, 97140 X 2, 97535 x 1, G0283


6

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Timed Codes172 units2 therapists

272 units2 therapists




6 7






13 14






20 21






27 28




72 units = 99.4%

62 units = 85%

Know what your productivity reports say about you 45

Timed Codes152 units1 therapist



452 units1 therapist


6 7






13 14






20 21






27 28




72 units = 99.4%

52 units = 144%

Know what your productivity reports say about you 46

Non Claim Data

• ADRs• Denials• Documentation Due Reports• Part B Clinician Involvement• Billing Errors/Line Item Denials

– Modifier– Diagnosis

• Documentation Audit Results

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Provider Response to CMS Screening All Claims on Front End

• Know your data profile as good as, if not better, than the CMS, ZPICs, FI/MACs, and RACs– Identify trends and outliers that require further drill down and evaluation

– Utilize to develop Audit and Monitoring Plan• Evaluate and Re‐evaluate documentation and billing practice

• Be prepared to respond to documentation requests and audits

• Know when to involve legal counsel

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Legal Counsel Involvement

• Ensure attorney client protections• Develop appropriate responses to discovered problems

• Review your contracts• Remember 60 day repayment rule

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Conclusion

• Audit and monitor• Assess your risks• Consult with counsel as necessary• Train and implement• Report and refund as necessary

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Questions?

Shawn Halcsik414.791.9122

[email protected]

Paula G. Sanders717‐612‐6027

[email protected]

Documents

Provider Predictive Modeling: Utilizing SNF Data to Mitigate Risk · 2013. 4. 24. · • Was due September 30, 2012 • Issued December 14, 2012 Category $ Millions EstimatedActual