John W. Hanna, MBA

VP Marketing

Veracyte, Inc.

john@veracyte.com

650.243.6362

Advanced Diagnostics in a Post-PAMA Era

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Veracyte is a Recognized Industry Leader

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About Veracyte, Inc.

• Founded in 2008 to address diagnostic ambiguity

• HQ and CLIA Molecular Lab in South San Francisco, CA

• Over 200 employees

• Three commercial products

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Overtreatment is a Global Epidemic

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Commercial Payer Trends

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Trends to Watch in Diagnostics Reimbursement

Utilization Management Payer Consolidation

Narrowing Networks Reference Pricing

Copyright 2016 American Medical Association. All rights reserved.

Association of Reference Pricing for Diagnostic LaboratoryTesting With Changes in Patient Choices, Prices,and Total Spending for Diagnostic TestsJames C. Robinson, PhD; Christopher Whaley, BA; Timothy T. Brown, PhD

IMPORTANCE Prices for laboratory and other clinical services vary widely. Employers andinsurers increasingly are adopting “reference pricing” policies to create incentives for patientsto select lower-priced facilities.

OBJECTIVE To measure the association between implementation of reference pricing andpatient choice of laboratory, test prices, patient out-of-pocket spending, and insurerspending.

DESIGN, SETTING, AND PARTICIPANTS We conducted an observational study of changes inlaboratory pricing and selection by employees of a large national grocery firm (n = 30 415)before and after the firm implemented a reference pricing policy for laboratory services andcompared the findings with changes over the same period for policy holders of a largenational insurer that did not implement reference pricing (n = 181 831). The grocery firmestablished a maximum payment limit at the 60th percentile of the distribution of prices foreach laboratory test in each region. Employees were provided with data on prices at alllaboratories through a mobile digital platform. Patients selecting a laboratory that chargedmore than the payment limit were required to pay the full difference themselves. A total of2.13 million claims were analyzed for 285 types of in vitro diagnostic tests between 2010 and2013.

MAIN OUTCOMES AND MEASURES Patient choice of laboratory, price paid per test, patientout-of-pocket costs, and employer spending.

RESULTS Compared with trends in prices paid by insurance policy holders not subject toreference pricing, and after adjusting for characteristics of tests and patients, implementationof reference pricing was associated with a 31.9% reduction (95% CI, 20.6%-41.6%) in averageprice paid per test by the third year of the program. In these 3 years, total spending onlaboratory tests declined by $2.57 million (95% CI, $1.59-$3.35 million). Out-of-pocket costsby patients declined by $1.05 million (95% CI, $0.73-$1.37 million). Spending by the employerdeclined by $1.70 million (95% CI, $0.92-$2.48 million).

CONCLUSIONS AND RELEVANCE When combined with access to price information, referencepricing was associated with patient choice of lower-cost laboratories and reductions in pricesand payments by both employer and employees.

JAMA Intern Med. doi:10.1001/jamainternmed.2016.2492Published online July 25, 2016.

Invited Commentary

Author Affiliations: School of PublicHealth, University of California,Berkeley.

Corresponding Author: James C.Robinson, PhD, School of PublicHealth, University of California,Berkeley, 247 University Hall,Berkeley, CA 94720-7360 (james.robinson@berkeley.edu).

Research

Original Investigation

(Reprinted) E1

Copyright 2016 American Medical Association. All rights reserved.

Downloaded From: http://archinte.jamanetwork.com/ by John Hanna on 08/24/2016

1 2

3 4

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Increasing Molecular Diagnostics Spend

UnitedHealth Center for Health Reform & Modernization, 2012

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Payers Will Likely Use Cost Containment Strategies Similar to Specialty Rx

38%

28%

68%61%

70%

82%89%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Specialtydrugcarveout

Specialtypharmacydispensingprogram

StepTherapies TightLimitsonthenumberofunitsadministeredata

singletime

UtilizationManagementPrograms

PriorAuthorization MailOrder

All Large Firms (200 or More Workers)

Kaiser/HRET Survey of Employer-Sponsored Health Benefits, 2016.

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DOJ Moves to Block Big Insurer Mergers

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The New Era of Mega-Plans

Ladika, S. The New Era of Mega-Plans. Managed Care. September 2015

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• Nearly 2,000 insurance companies in the U.S.

• Yet medical policy decision making is highly concentrated

Health Technology Assessment Organizations

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Who Conducts HTA’s?

Segment HTA Organization Payer Covered LivesCommercial eviCore, ECRI,

Interqual,Milliman, Hayes

United, Aetna, Cigna, Humana, Emblem,HealthNet, etc.

70 Million

Blue Cross BCBS TEC, Hayes Blues Plans 100 Million

Medicare AHRQ, MolDx,MAC Contractors

CMS 60 Million

Medicaid ICER, CTAF, etc. States Medicaid Plans 65 Million

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90% of payers made policies public

146 – 698 policies per payer

31% of policies are diagnostics & imaging

Representative Set of 28 Policies57% covered by all payers11% were non-covered by all87% assessed literature80% reviewed guidelines15% reviewed ICER studies0% reported patient input

Coverage Trends for 20 Largest Plans

Chambers JD, AJMC 2016

THE AMERICAN JOURNAL OF MANAGED CARE VOL. 22, NO. 9 e323

TRENDS FROM THE FIELD

I n US healthcare, multiple public and commercial payers is-

sue coverage policies for medical interventions.1-3 Because

payers conduct their own assessments and issue their own

decisions, whether and how they cover medical interventions

can vary, which, in turn, can affect patients’ access to care. Re-

searchers have highlighted variation in payer coverage policies

and examined decision making.4,5 Recent research has studied

trends in Medicare National Coverage Determinations (NCDs)

and the consistency of coverage with the reviewed evidence.6-8

Another recent study found substantial variation in how Medi-

care and private payers cover medical devices.9

This study adds to the literature by examining coverage poli-

cies for medical interventions issued by the top 20 US commer-

cial payers. First, we examined the coverage policies issued by the

largest US-based commercial payers. Second, for a representa-

tive set of interventions, we compared coverage determinations

across payers (ie, whether and how the payers cover the interven-

tions and the types of evidence the payers reported reviewing

when formulating their policies).

METHODSWe identified the 20 largest US-based commercial payers in terms of

number of covered lives.10 We searched each payer’s website to de-

termine the availability of their medical benefit coverage policies. In

many cases, payers provide memoranda, which describe the target

patient population, any conditions on patient access to an interven-

tion, and, frequently, the clinical trials, clinical guidelines, and other

evidence the payer reports reviewing when formulating the cover-

age policy. We focused on coverage policies pertaining to the payers’

commercial line of business by excluding coverage policies pertain-

ing to their Medicaid managed care or Medicare Advantage lines of

business. When we were unable to locate memoranda, we contacted

the payer to confirm their unavailability.

We identified all coverage policies issued by each of the 20 pay-

ers (n = 7372). Included policies were current as of August 1, 2014.

Mapping US Commercial Payers’ Coverage Policies for Medical InterventionsJames D. Chambers, PhD; Matthew D. Chenoweth, MPH; and Peter J. Neumann, ScD

ABSTRACT

OBJECTIVES: To examine coverage policies for medical interventions issued by the largest US commercial payers.

STUDY DESIGN: Review of publicly accessible coverage policies for medical interventions.

METHODS: We categorized the 20 largest commercial payers’ medical benefit coverage policies for medical technologies—current as of August 1, 2014—with respect to technology type (eg, medical devices, pharmaceuticals, surgeries). We identified the interventions most commonly subject to coverage policies and compared payer coverage determinations in terms of whether they covered the intervention and the evidence they reported reviewing.

RESULTS: Eighteen payers made their coverage policies publicly available and 17 reported the evidence they reviewed in formulating policies. The types of technologies considered varied across payers, although most focused on devices and diagnostics. Of the 28 interventions most commonly subject to coverage policies, the coverage of 9 varied (ie, some payers covered the intervention and others did not). On average, payers reported reviewing clinical studies in 87% of coverage policies (range = 25%-100%). Two payers did not report reviewing systematic reviews or meta-analyses in any coverage policies, and 9 reported reviewing such evidence in at least half of their policies. Fourteen payers reported reviewing cost-effectiveness analyses at least some of the time, with frequency ranging from 8% to 43%. Commercial payers’ coverage decisions did not appear to reflect direct input from patients or patient advocates, at least as stated in published coverage policies.

CONCLUSIONS: Coverage of medical interventions varies across US private payers. Payers often report reviewing different evidence when formulating coverage policies, but do not report considering input directly from patients in evidence assessments.

Am J Manag Care. 2016;22(9):e323-e328

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Narrowing Networks

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Lab Benefit Management Programs & Reference Pricing

Copyright 2016 American Medical Association. All rights reserved.

Association of Reference Pricing for Diagnostic LaboratoryTesting With Changes in Patient Choices, Prices,and Total Spending for Diagnostic TestsJames C. Robinson, PhD; Christopher Whaley, BA; Timothy T. Brown, PhD

IMPORTANCE Prices for laboratory and other clinical services vary widely. Employers andinsurers increasingly are adopting “reference pricing” policies to create incentives for patientsto select lower-priced facilities.

OBJECTIVE To measure the association between implementation of reference pricing andpatient choice of laboratory, test prices, patient out-of-pocket spending, and insurerspending.

DESIGN, SETTING, AND PARTICIPANTS We conducted an observational study of changes inlaboratory pricing and selection by employees of a large national grocery firm (n = 30 415)before and after the firm implemented a reference pricing policy for laboratory services andcompared the findings with changes over the same period for policy holders of a largenational insurer that did not implement reference pricing (n = 181 831). The grocery firmestablished a maximum payment limit at the 60th percentile of the distribution of prices foreach laboratory test in each region. Employees were provided with data on prices at alllaboratories through a mobile digital platform. Patients selecting a laboratory that chargedmore than the payment limit were required to pay the full difference themselves. A total of2.13 million claims were analyzed for 285 types of in vitro diagnostic tests between 2010 and2013.

MAIN OUTCOMES AND MEASURES Patient choice of laboratory, price paid per test, patientout-of-pocket costs, and employer spending.

RESULTS Compared with trends in prices paid by insurance policy holders not subject toreference pricing, and after adjusting for characteristics of tests and patients, implementationof reference pricing was associated with a 31.9% reduction (95% CI, 20.6%-41.6%) in averageprice paid per test by the third year of the program. In these 3 years, total spending onlaboratory tests declined by $2.57 million (95% CI, $1.59-$3.35 million). Out-of-pocket costsby patients declined by $1.05 million (95% CI, $0.73-$1.37 million). Spending by the employerdeclined by $1.70 million (95% CI, $0.92-$2.48 million).

CONCLUSIONS AND RELEVANCE When combined with access to price information, referencepricing was associated with patient choice of lower-cost laboratories and reductions in pricesand payments by both employer and employees.

JAMA Intern Med. doi:10.1001/jamainternmed.2016.2492Published online July 25, 2016.

Invited Commentary

Author Affiliations: School of PublicHealth, University of California,Berkeley.

Corresponding Author: James C.Robinson, PhD, School of PublicHealth, University of California,Berkeley, 247 University Hall,Berkeley, CA 94720-7360 (james.robinson@berkeley.edu).

Research

Original Investigation

(Reprinted) E1

Copyright 2016 American Medical Association. All rights reserved.

Downloaded From: http://archinte.jamanetwork.com/ by John Hanna on 08/24/2016

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PAMA & Clinical Lab Fee Schedule Reform

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The Post-PAMA Era Reforms Impacting ADLTs

Market Based Price Setting Coding for New ADLTs1 2

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Advantages & Challenges for ADLTs

ADLTs CDLTsDesignation Process

Meet ADLT Definition + Demonstrate Test Provides New Clinical Information

Offered and Performed in the U.S.

Coding Unique Test-Specific Code

No Directive for Unique Codes

Initial Payment Three Quarters at List Charge

Contractor Priced Until On Fee Schedule

Rate Setting Median of Commercial Payer Rates

Crosswalk or Gapfill

Data Reporting Annual Reporting Every Three Years

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The Tier II Conundrum – 40% of Billed Molecular Services

CMS Public Use File CY 2014

HCPCS Code Gene Number of

ProvidersNumber of Services

Unique Patients

Average Charge

Average Allowed

81401 MoPath L2 167 422,556 208,265 $157.54 $113.08

81479 MISC 101 58,055 43,220 $1,860.49 $1,140.59

81355 VKORC1 19 24,543 24,524 $277.80 $88.97

81270 JAK2 243 21,176 20,520 $370.87 $124.53

81400 MoPath L1 58 20,072 11,595 $254.89 $121.24

81404 MoPath L5 77 19,593 7,950 $1,365.11 $242.78

81403 MoPath L4 132 16,193 10,014 $1,326.12 $113.02

81235 EGFR 131 13,275 13,094 $1,820.10 $331.22

81374 HLA typing 95 10,636 10,556 $222.05 $98.62

81275 KRAS 164 9,040 8,902 $753.20 $196.97

81210 BRAF 161 8,796 8,489 $863.50 $179.75

81402 MoPath L3 65 5,297 5,214 $442.41 $288.23

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AMA CPT Announcement – PLA Coding is Coming

May 13, 2015

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November PLA Application Meeting

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1Q 3Q2Q

Start of Initial Period

1st Quarter Following LCD Effective Date

Initial Data Reporting

Period

Medicare Final LCD Effective

Date

Initial Commercial Offering of New Test

May take several years for labs to generate clinical utility data sufficient for

LCD coverage

Draft LCD Published

Act

ivity

M

edic

are

Rat

e

No Medicare Payment

No Medicare Payment

Contractor Priced

Initial Data Collection

Period

Labs may report most recent 12 months of data

Actual List Charge (ALC)Payment for New ADLT

Medicare Rate Set at Weighted

Median

Code & Rate Added to CLFS and Set Until

Next ADLT Reporting Cycle

Lab Can Apply For ADLT Status and Be Assigned a Code Anytime Prior to Start of Initial Period

Hanna JW, Coalition for 21st Century Medicine Letter to CMS. January 18, 2016

New ADLT Designation, Coding & Rate Setting

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The Gapfill Challenge

Code Test/Laboratory

2015 ContractorAllowable

PreliminaryGapfill NLA

Final GapfillNLA Change

81538 VeriStratBiodesix $2,112.00 $283.00 $1,341.87 -36.46%

81525

OncotypeDxColon

GenomicHealth

$3,104.00 $848.86 $2,062.10 -33.57%

81595 AllomapCareDx $2,821.00 $732.12 $1,920.93 -31.91%

81540 CancerTypeIDBiotheranostics $2,900.00 $1,522.17 $2,355.46 -18.78%

81545 AfirmaVeractye $3,200.00 $2,240.16 $2,864.45 -10.49%

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Gapfill Amounts Reversed

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New Clinical Information – The Curse of Rule Making

“The test must provide new clinical diagnostic information that cannot be obtained from any other existing test on the market or combination of tests.”

“Based on our view that ADLTs that meet the criterion are innovative tests that are new and different from any prior test already on the market and provide the individual patient with valuable genetic information to predict the trajectory of the patient’s disease process or response to treatment of the patient’s disease that could not be gained form another test or [combination of] tests on the market.”

CMS PAMA Final Rule 42 CFR 414 [CMS-1621-F]

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Would CMS Consider 0008M and 81519 ADLTs? Code Descriptor Medicare NLA

0008M Oncology (breast), mRNA analysis of 58 genes using hybrid capture, on formalin-fixed paraffin-embedded (FFPE) tissue, prognostic algorithm reported as a risk score.

$3,416.00

81519 Oncology (breast), mRNA, gene expresison profiling by real-time RT-PCR of 21 genes, utilizing formalin-fixed paraffin embedded tissue, algorithm reported as a recurrence score.

$3,416.00

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CMS Comments on MAC Consolidation

“If we were to exercise only the authority to reduce the number of MACs issuing LCDs for CDLTs, such a change could likely be finalized within the next 2 to 4 years.”

“However, reducing the number of MACs processing claims for CDLTs would involve significantly more complex programmatic and operational issues. For instance, the consolidation of Medicare claims processing for CDLTs would require complex changes to Medicare’s computer systems. Thus, such a transition could take several years to implement.”

PAMA Proposed Rule, CMS 2015

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Type of Service Percent of Codes Subject to LCD 2011

Medical Procedures 71%E&M Services 52%Imaging 47%Drugs 42%Diagnostic Tests 31%Other (<10% of Services) 74%

In 2003 MMA Called for Greater Consistency

Levinson DR. OEI-01-11-00500 January 2014

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28 of 57 MAC Jurisdictions follow MolDx Coverage and

Pricing Determinations

MAC Contractors & Local Coverage

MAC Jurisdictions Rate SettingNoridian 14

MolDx ProgramWPS* 8Palmetto 4CGS 2NGS 12 AnthemNovitas 12

BCBS FloridaFirst Coast 2Cahaba 3 Cahaba

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Coverage with Data Development

LCD Test Indication

L35632 ConfirmMDX Prostate Cancer

L36153 OncotypeDx Prostate Prostate Cancer

L35869 Prolaris Prostate Cancer

L35868 Decipher Prostate Cancer

L36665 ProMark Prostate Cancer

L36143 Comprehensive Genomic Profiling Non Small Cell Lung Cancer

DL36912 OncotypeDx Breast DCIS Breast Cancer

DL36854 Percepta Lung Cancer

Certification and Training Registry Program (CTR)

Additional Utility Publication to Remove Coverage Restrictions

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FDA & CMS Parallel Review

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Parallel Review Experience

Ridge JR, Statz S. Expert Review Molecular Diagnostics. 2015

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1. PAMA requires intentional strategy for success

2. Commercial reimbursement is getting tougher

3. HTA transparency & standardization is needed

4. ADLT designation and coding remain uncertain

Key Take Away

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Thank you!