Saturday, June 24, 2017

June 2017 Version of MolDx article M00127 V3: NGS Billing Policies; Code 81479

https://www.palmettogba.com/palmetto/MolDX.nsf/docscat/MolDx%20Website~MolDx~Browse%20By%20Topic~Covered%20Tests~Next%20Generation%20Sequencing%20Coding%20and%20Billing%20Guidelines%20(M00127%20V3)


Next Generation Sequencing Coding and Billing Guidelines (M00127, V3)


June 21, 2017

Next Generation Sequencing (NGS)
NGS allows identification of somatic and/or germline alterations in multiple genes simultaneously. This guideline focuses on Targeted and Comprehensive Genomic Profile testing for somatic variant detection using tumor tissue only-based panels.  Panels involving germline variants, matched tumor-normal, or “liquid biopsies” (including circulating tumor cells (CTCs) or DNA (ctDNA), or cell-free DNA (cfDNA)) will be addressed separately, but should be billed using CPT 81479.
Targeted (aka Hot Spot) Tumor Panels
Targeted NGS panels identify somatic alterations known to occur in certain areas (i.e., 'hotspots') in specific genes of interest. Generally, these NGS panels can detect single nucleotide variants (SNVs or point mutations) and small (typically ≤40 bp) insertions or deletions (indels), but not copy number alterations (CNAs) or structural variants (SVs), such as gene rearrangements, fusions, or translocations. These alterations typically represent genomic targets with corresponding targeted cancer therapies. Identification of a somatic alteration guides use of the corresponding targeted therapy.
To bill for targeted NGS services for somatic variant detection, review CPT codes 81445, 81450 and 81455. Select the appropriate CPT code based on the number of genes in your laboratory’s NGS panel and the test indication for either solid organ or hematolymphoid neoplasms. The units of service (UOS) for an NGS panel is one (UOS=1). 
Effective July 1, 2017, laboratories with 1 to 4 gene(s) on their targeted NGS panel should use CPT 81479 and one (1) UOS along with their test identifier (DEX Z-code) to represent this service on their claims.  (Similarly, CPT 81479 should be used to bill for somatic variant detection performed by a targeted NGS panel on a “fluid” sample (e.g., KRAS in pancreatic cyst fluid). Reimbursement is based on the number of reported genes in these small NGS panels. Tier 1 and/or Tier 2 individual biomarker CPT codes should not be used for a single gene or any combination of genes when testing is performed as part of a NGS or other multiplexing technology panel.
Comprehensive Genomic Profile (CGP) TestingCGP refers to NGS-based testing that has been optimized to identify all types of molecular alterations (i.e., SNVs, small and large indels, CNAs, and SVs) in cancer-related genes in a single test using complex and often proprietary bioinformatics.  CGP may also include testing for MSI (microsatellite instability) and TMB (tumor mutational burden).
Because CGP includes SNVs, small (≤40 bp) and large (> 40 bp) indels, CNAs, and SVs, CPT codes 81445, 81450, and 81455 do NOT describe a CGP service. Therefore, to report a CGP service, test providers should use CPT code 81479.

February 2016 Version of MOLDX M00130 Guidelines, V2, NGS and T1 T2 Coding

As of summer 2017, MolDX guideline M00130 V2 appears to be taken down from the MolDX website, although some MoLDX documents still guide the reader to look up needed instructions within M00130.

M00130 V2 was still available in June 2017 via GOOGLE CACHE.  As below.

https://webcache.googleusercontent.com/search?q=cache:ASsLgFP_fBYJ:https://www.palmettogba.com/palmetto/providers.nsf/vMasterDID/A6LLL81487%3FOpenDocument+&cd=1&hl=en&ct=clnk&gl=us


Next Generation Sequencing (NGS) and Tier 1 and Tier 2 Coding and Billing Guidelines (M00130, V2)



When the AMA developed and published the descriptions for the Tier 1 (T1) and Tier 2 (T2) codes in the Molecular Pathology Procedure Section, the technology for NGS was not fully developed. At that time labs typically used polymerase chain reaction (PCR) and non-NGS sequence analysis to interrogate a single gene or gene component. Therefore, the T1 and T2 codes describe services for a single or occasionally two genes test and subdivide the descriptions by full gene sequence, common variants, duplication/deletion variants, and known familial variants.
NGS platforms have the ability to target and detect multiple specific genes of interest, including common variants, duplication/deletion variants, and known familial variants in one run to create a single report. Therefore, MolDX considers an NGS panel a single test with multiple potential indications. The AMA describes NGS gene panels in the Genomic Sequencing Procedure and Other Molecular Multianalyte Assay (GSP) Section.
To correctly report NGS panels for MolDX claim processing, please review the following guidelines:
  • Compare the CPT code descriptions in the GSP Section and select the panel that describes your test. Appropriate GSP codes include the following: 81410, 81412, 81415, 81417, 81420, 81425, 81430, 81432, 81433, 81434, 81435, 81437, 81440, 81442, 81445, 81450, 81455, 81460, 81465, and 81470.
  • Do NOT report NGS tests with T1 (codes 81161-81355) and T2 (codes 81400-81408) even if a single gene or multiple genes are selected for testing. MolDX will deny NGS panels reported with T1 and T2 codes as an unbundled service from the primary NGS panel.
  • Report codes 81445, 81450 and 81455 for tumor-based targeted (i.e. “hotspot”) panels that test only for SNVs and small indels (10bp)
  • Report circulating tumor DNA (ctDNA) and matched tumor-normal testing with 81479
  • Report comprehensive NGS panels that perform tumor tissue testing (e.g.SNVs, indels, CNVs and translocations/rearrangements) with 81479.
  • Tests reported with CPT code 81479 should be submitted for a teachnical assessment (TA) through DEX after a Z-Code Identifier has been assigned. 
Please suspend claims submission until MolDX has determined coverage and reimbursement for your test. 
Somatic and germline NGS test panel claim submission examples: 
1. One somatic NGS “hotspot” panel split into two tests based on indication and INCORRECTLY submitted with T1/T2 codes and two different Z-Code Identifiers
NGS Test
Investigated Genes
CPT Code
Claim Submission
ID
NGS Colon Cancer Panel 1
BRAF, KRAS, and NRAS
81210, 81275, 81311
Incorrect
Z1234
NGS Lung Cancer Panel 2
EGFR, KRAS, and BRAF
81235, 81275, 81210
Incorrect
Z4567
2. One somatic NGS “hotspot” panel split into two tests based on indication and INCORRECTLY submitted with CPT code 81479 and two different Z-Code Identifiers.
NGS Test
Investigated Genes
CPT Code
Claim Submission
ID
NGS Colon Cancer Panel 1
BRAF, KRAS, and NRAS
81479
Incorrect
Z1234
NGS Lung Cancer Panel 2
EGFR, KRAS, and BRAF
81479
Incorrect
Z4567
3. One somatic NGS “hotspot” panel for two different solid tumor indications and CORRECTLY submitted with CPT code 81445 and one Z-Code Identifier.
NGS Test
Patient Indication
CPT Code
Claim Submission
ID
NGS: targeted genomic sequence analysis panel, solid organ
Colon cancer
81445
Correct
Z4444
NGS: targeted genomic sequence analysis panel, solid organ
Lung cancer
81445
Correct
Z4444
4. One germline test for two patients with different hereditary cancer indications and CORRECTLY submitted with CPT code 81432 and one Z-Code Identifier.
NGS Test
Patient Indication
CPT Code
Claim Submission
ID
NGS: Hereditary breast cancer-related disorders (breast, ovarian, endometrial…)
Breast cancer
81432
Correct
Z5555
NGS: Hereditary breast cancer-related disorders
Endometrial cancer
81432
Correct
Z5555
   *Do not submit code 81432 in addition to T1/T2 testing on the same patient.

February 16, 2016

Tuesday, June 6, 2017

Quick Guide to Using the Online Medicare Physician Billing Database

Since 2014, CMS has posted annual files of Part B billing data by provider name.  Available files are for CY 2012, CY2013, CY2014, and in June 2017, CY2015.

Originally, you had to download many very large files by alphabet letter of provider's last name, or download a 2 GB database too large for Excel.   Now, you can go to the online web interface and instantly sort for data of interest and download that data quickly into an Excel file that can be easily studied.

For more about the history of this important data file and an example of analyzed data, here.

Some process steps are described below.

Find the home page for the data set here.   The path would be CMS home page > Research and Statistics > Medicare Provider Utilization > Physician and Other Supplier Data 2014 (or 2015).



Click on "Detailed Data: Interactive Dataset: Medicare Physician and Other Supplier PUF CY2014 Interactive Dataset."   Here.   Click yes on a CPT copyright screen.  You now are looking at the tip-to corner of a massive, 2 GB dataset with a couple dozen columns and millions of rows.


What you want to focus on is the FILTER button (above).  Click on this and see a drop down box that includes the button: "+ Add A New Filter Condition." (Below).


Click on "Add A New Filter Condition."  There will be another dropdown - you can choose to filter on NPI, Last Name, City, State, etc.   For example, filter on "HCPCS Code" 95004 to see all data on allergy skin testing.


Instantly, the screen you see in your browser is a far tinier dataset of the 4,114 providers who billed Medicare for "95004" skin allergy testing in CY2014.

You're almost done.  Just click the pale blue EXPORT button and export CSV EXCEL (comma delimited file for Excel).  Save on your hard drive as 2014 95004.csv.  




Open it in Excel, and resave it right away as Excel Workbook.

You have the 900 kb of data you need and are free of the 2 GB scale of the original data.   Now, you can delete unnecessary columns and sort and analyze with ease.

One quirk.  The spreadsheet holds a column for "number of services allowed," and one for "average Medicare allowable price per service."  You probably will want to make an additional column that multiplies these two columns together to get the total dollars allowed for that provider for that service in that year.  E.g. 500 services allowed X $9.00 per service becomes a new column of $4,500.00.

_______________________

I can't give a course in Excel and I'm not an expert with it, but two particularly useful functions are these.

"Sort and Filter" (upper right), click on  Custom Sort, click "Expand Selection" if offered, be sure "My Data Has Headers" is checkmarked, and filter on one or more columns.  For example, you can filter by state, then, by provider type, then, by services allowed in the year.

To quickly see a line plot of data, select an entire column, click Insert, and click "Recommended Charts."  This instantly gives you graphics like this one:




Wednesday, May 17, 2017

Agenda of April 2017 Conference (RWE)

http://www.eyeforpharma.com/real-world-evidence/conference-agenda.php?elqTrackId=74a54b7e2c6d4cd1957d49e5d8a9aead&elqaid=16957&elqat=2



Day One

  • 08:15-09:00
    Registration
    09:00-09:05
    Opening Address
    09:05-09:35
    Work cross-functionally to unlock new insights throughout the lifecycle
    • Adopt a cross-functional approach, enabling increased real-world understanding from discovery to post-approval
    • Understand how different teams can work together to break data silos, enhancing the internal spread of knowledge
    • Meet increasing regulatory requirements by engraining a continuous cycle of evidence generation into your company’s core efforts
    09:35-10:00
    Insights, Ecosystems, and Outcomes: Using Data to Drive Value Based, Personalised Healthcare
    • Understand how the healthcare ecosystem is undergoing an unprecedented period of change
    • Explore how life science organisations are investing in end to end evidence approaches which require new operating models and technology choices
    • Industry Case Study - Implementing an enterprise wide RWE strategy
    10:00-10:25
    Make sure your product is launch ready by integrating market access into drug discovery and development
    • Use payer insights to tailor clinical trial design to ensure the data collected meets market requirements
    • How to promote market access priorities in phase II and III to ensure a seamless, HTA-ready launch
    • Explore ways to engage payers early in order to evade potential pitfalls and hurdles to reimbursement
    10:25-10:55
    Coffee break
    10:55-11:35
    Panel discussion: Emerging data sources – meet evolving data needs with the latest innovations
    • Discover the increased patient insight offered by previously under-utilised data sources
    • Meet increased HTA/payer demands with increased value demonstration
    • Learn how to maximise analytical capabilities by harmonising data collection across multiple platforms
    11:35-12:00
    Increase product launch success with a cross-functional use of real world evidence.
    • Prepare for future product development and launch by integrating RWE across functions (Clinical Development, Medical, Market Access, Marketing)
    • Enhance product understanding and communication with a fluid approach
    • Case example of innovative basal insulin launched in crowded diabetes market place and price containment context
    12:00-12:25
    External collaboration with stakeholders to optimize patients access strategies “from clinical development to patient access”
    • Understand the principles of market access and medical teaming up to shape patients outcomes in unmet haematological malignancies
    • Hear how R&D innovation is being accelerated through the nurturing of a ground breaking public-private relationship
    • Genuinely maximise your real-world capability by building your strategy in partnership key stakeholders and competitors
    12:25-12:50
    Driving Market Access with RWE: Rhetoric vs. Reality
    • Explore the different perceptions surrounding RWE and optimise your real-world access strategy with greater understanding of the other halves needs
    • Interactive session gauging the audience’s own perceptions on the Market Access/RWE relationship
    12:50-14:00
    Lunch Break (New Chair: Agathe Le Lay, Head of HEOR Europe, Novo Nordisk)
    14:00-15:00
    Multi-presentation feature: See how IMI’s ‘GetReal’ project is increasing RWE’s practical application with earlier adoption into the lifecycle
    • Hear how best to demonstrate effectiveness through real-life clinical studies with thought leadership from stakeholders across healthcare
    • Smoothly incorporate pragmatic trials into your operations with the latest methodological approaches
    • Delve into the range of tools developed from the program accelerating RWE development
    15:00-15:30
    Lean Clinical Development - Adding value with visual evidence.
    • BDD Scintigraphy as a tool to maximise clinical investment
    • Seeing is believing - RWE to support product claims, marketing and strategy
    • Case study; In vivo imaging of novel complex oral product
    15:30-16:00
    Coffee Break
    16:00-16:30
    Optimise your clinical trials using Electronic Health Records
    • See how the EHR4CR project is increasing patient understanding through the catalyse of EHR use in Europe
    • Enhance your clinical trial efficiencies with RWD protocol data testing, accelerated patient recruitment and enhanced EHR data extraction
    • See how the new ‘Champion Programme’ is reducing the risk of investing in EHRs, encouraging growth of the EHR ecosystem
    16:30-17:00
    The Importance of an Integrated Medical Plan
    • A review of recent drug launch success
    • Where RWE collection could have played its part
    • Building an Integrated Medical Plan to prepare for success: “Begin with the End in Mind”
    • The “Resource v Demand” Challenge in this environment
    17:00-17:30
    Why choosing RWD from the right league changes everything.
    • What are the different leagues of real world data and how do they change the opportunities for relevant research?
    • Discover why Registry Based Randomized Clinical Trials will be the next disruptive technology in clinical research
    • Value Based Health Care examples based on high quality data sets
    17:30-18:00
    Real World Data (RWD) and Real World Evidence (RWE): Turning the myriad of data sources into clinical practice evidence
    • Is RWE actually a new trend? Why are we talking so much about it now?
    • Explore the differences, perceived and real, between RWD & RWE
    • Understand the values and risk associated with adopting a real-world approach
    18:00-19:00
    Networking Drinks
    19:00
    End of Day One




Day Two

  • 09:00-09:30
    Expand your research capability by utilising CPRD as a tool for innovation
    • Explore how the CPRD is evolving to further vary and increase their sources of data, expanding research possibilities
    • Educate clinical trial design to improve clinical output with more targeted patient identification
    • Providing the data for different research purposes in clinical trials
    09:30-10:00
    Unleashing data science in RWE via next generation tools
    • Machine learning, deep-learning, phenotyping or tensors can transform RWE 
    • Major barriers exist: lack of skills, using data scientists for simple data management
    • QuintilesIMS discusses case studies and next generation tools to unlock data science
    10:00-10:30
    Draw further insight from your RWD with interactive visualization techniques
    • Understand how interactive visualization can help you explore your data in new ways, finding previously undiscovered hypothesis
    • Case study examples surrounding the latest Janssen work in partnership with Karolinska Institute and the Royal Institute of Technology
    10:30-11:00
    Coffee Break
    11:00-11:45
    The GSK Salford Lung Study: Lessons learnt
    • Hear how experiences from pioneering pragmatic phase III study can aid in pushing further real-world studies into reality
    • Understand how electronic health records allowed for quick and easy access of patient information – enabling the study to take place 
    • See the way the studies inclusive approach generated greater insight into drug effectiveness in a real-world setting
    • Learn how collaboration with local healthcare providers played a crucial role in the studies effectiveness and operational capacity 
    11:45-12:15
    Innovative approaches to Real World uses of EHR data
    • Find out how Ignite are using EHR data to find and consent patients onto studies across the UK
    • Discover how current technology is being utilised to extract data across most UK healthcare settings
    • Understand how some traditional processes can support the use of technology and eSourced data
  • 12:15-13:15 Choose between the following 3 workshops
    Choice 1
    Interactive Workshop 1: The role of digital technology in RWD programs
    • Explore the use of technology to support patient data capture across observational, pragmatic and commercial health management programs
    • Build in representativeness through use of patient’s own devices
    • Understand how this approach facilitates the capture of high quality, regulatory compliant datasets built for analysis and mining in a real-world setting
    • Discuss how, where applicable, technology can support enhanced patient engagement and improved health outcomes
    Choice 2
    Interactive Workshop 2: Market Access - Back to The Future
    • In this interactive workshop, we will explore Market Access Reality vs Market Access Ideology, to test the hypothesis that:
    • “To improve post-launch market access success, market access activities must start early in a product’s lifecycle”
    • If the current reality is suboptimal, what opportunities are we missing?
    • If we could go back in time and change what was done, could things have been different - could the challenges have been predicted and addressed?
    Choice 3
    Interactive Workshop 3: Maximizing real world data with governance in a digital world
    • Gain insights into managing RWD with effective governance to help create tailored programs. This workshop will help you learn how to future proof your data with best practices (acquiring, qualifying and maximizing RWD)
    • Understand the challenges of acquiring data with a real-life case study of how pharma organizations are filling the gaps on their own compliance practices
    • Explore how RWD can be used to create an effective patient/HCP journey and analyse the campaign performance
  • 13:15-14:15
    Lunch Break
    14:15-14:45
    The Patient Perspective: Real World Evidence = Real World Patients: Design your real-world strategy around the key stakeholder
    • Hear how to work with patients in your real-world set-up to change attitudes toward data collection; improving your collection techniques and results
    • Explore the opportunities social media offers for patient engagement and data collection
    • Understand why the strive for a patient-centric pharma does not exclude big data
    14:45-15:15
    Real World Evidence: who cares? Investigating how EU payers actually base decisions on RWE
    • Address increasing evidence expectations from EU payers by exploring their usage of RWE in HTA and reimbursement decisions
    • Assess EU payer receptiveness and future trends for RWE, to build buy-in from partner functions for RWE investment
    • Share selected learnings on how industry leaders can use RWE for positive impact on payer decisions.
    15:15-15:45
    Increase your understanding of the burden of illness through text mining
    • Break the traditional feedback model to discover new findings from the analysis of open-ended patient feedback
    • Explore how text mining advancements are expanding the traditional scope of data analysis
    15:45-17:00
    Coffee to stay or go