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Reimbursement Bootcamp- Coding, Coverage & Payment lecture by David Farber, King & Spalding

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Levi Shapiro
Levi Shapiro

Presentation by David Farber, King & Spalding LLP, "Reimbursement Bootcamp- Coding, Coverage & Payment". Includes a comparison of FDA and CMS – The Important Differences. Setting Expectations and Understanding Timing. FDA Approval/Clearance vs. CMS (Medicare) Coverage. “Reasonable and Necessary” CMS coverage determination (formal or informal); Focus on health benefits; Economic data is important; Superiority endpoint often needed; Focus on Medicare beneficiaries; Public processes; Publishes proposed decisions. Information Considered by CMS. Center for Medicare & Medicaid Services. Clinical evidence (including FDA submissions) External technology assessments; Advisory committee recommendations; Position statements by relevant groups; Expert opinions; Public comments; Economic and other cost-effectiveness data; Other informal opinions. The Basics of Reimbursement • Coverage Is the item or service eligible for payment? • Coding How is the item or service identified? • Payment What are the payment methodologies and amounts? Medicare Coverage: Defined Benefit Category Not Excluded “Reasonable and necessary for the diagnosis or treatment of illness or injury or to improve the functioning of a malformed body member.” — Social Security Act § 1862(a)(1)(A). CMS and Its Contractors Make Medicare Coverage Decisions • National Coverage Determinations (NCDs) • Local Coverage Determinations (LCDs) • Individual Consideration National Coverage Determinations (NCD): National and binding decision by CMS Coverage and Analysis Group (CAG). May be requested by anyone (CMS or external party.) Public process that generally takes 9-12 months once initiated. May include certain conditions for coverage (including Coverage with Evidence Development (CED)). Coverage with Evidence Development (CED). Evidence-based coverage paradigm that permits CMS to develop coverage policies for treatments that are likely to show health benefits for Medicare beneficiaries but for which the evidence base is not sufficiently developed. Two kinds of CED: (1) clinical study and (2) registry. Local Coverage Determinations (LCD): Issued by local Medicare Administrative Contractors (MACs). May be requested by anyone (MAC or external party.) New formal process in 2019 to request LCDs. Limited to particular MAC jurisdiction. Medicare Administrative Contractors. Coding is the “language of reimbursement.” Coding operationally links coverage and payment. Having a code does not guarantee reimbursement! TYPE OF CODE, CODING SYSTEM, WHO SETS CODE? WHO USES CODE? Diagnosis, Procedure or Service, Products and Certain Services, Drugs. Current Procedural Terminology (CPT) Codes. Maintained by the AMA CPT Editorial Panel. Identify medical services furnished by physicians. 5-digit numeric codes with generic descriptors. Three types of CPT codes. Application process takes at least 15 months for Category I codes, with specific clinical data requirements.

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David J. Farber Partner dfarber@kslaw.com Preeya Noronha Pinto Partner ppinto@kslaw.com mHealth Presentation July 4, 2024 U.S. Reimbursement
Agenda I. Introduction II. FDA and CMS – The Important Differences III. The Three Elements of Reimbursement I. Coverage II. Coding III. Payment IV. Advanced Strategies
Introduction: Setting Expectations and Understanding Timing 3
“ But despite . . .big digital health ambitions, the path to success will not be an easy one. Digital health companies across the world are facing … a market marred by reimbursement difficulties.” — MedTech Insight (April 23, 2018, p.14) 4
“ As one VC investor noted, ‘Payers are pulling back on paying for new things. It is difficult to get new technologies covered. It’s taking companies three to five years … to collect enough data and go through the processes to obtain coverage following FDA approval.’” — Deloitte, Out of the valley of death: How can entrepreneurs, corporations, and investors reinvigorate early-stage medtech innovation? (April 2018, p.5) 5
Introduction -- Why Is This Important? 6
7
The Differences Between FDA and CMS 8
FDA Approval/Clearance vs. CMS (Medicare) Coverage 9 FDA CMS “Safety and Effectiveness” FDA-approved labeling Focus on function and clinical risk vs. benefits Economic data is irrelevant Non-inferiority endpoint acceptable Focus on intended population Generally not public processes Does not publish proposed decisions “Reasonable and Necessary” CMS coverage determination (formal or informal) Focus on health benefits Economic data is important Superiority endpoint often needed Focus on Medicare beneficiaries Public processes Publishes proposed decisions
Information Considered by FDA and CMS 10 Food and Drug Administration Center for Medicare & Medicaid Services “Well-controlled” clinical investigation data Non-clinical laboratory studies Quality system controls Labeling Post-market controls Advisory committee recommendations Published and unpublished literature “Well-controlled” clinical investigation data Clinical evidence (including FDA submissions) External technology assessments Advisory committee recommendations Position statements by relevant groups Expert opinions Public comments Economic and other cost-effectiveness data Other informal opinions
What Is Reimbursement? 11
The Basics of Reimbursement • Coverage Is the item or service eligible for payment? • Coding How is the item or service identified? • Payment What are the payment methodologies and amounts? 12
An Overview of Coverage 13
Medicare Coverage: Defined Benefit Category Not Excluded “Reasonable and necessary for the diagnosis or treatment of illness or injury or to improve the functioning of a malformed body member.” — Social Security Act § 1862(a)(1)(A) 14
15 CMS and Its Contractors Make Medicare Coverage Decisions • National Coverage Determinations (NCDs) • Local Coverage Determinations (LCDs) • Individual Consideration
National Coverage Determinations (NCD): National and binding decision by CMS Coverage and Analysis Group (CAG). May be requested by anyone (CMS or external party.) Public process that generally takes 9-12 months once initiated. May include certain conditions for coverage (including Coverage with Evidence Development (CED)). 16
Coverage with Evidence Development (CED) Evidence-based coverage paradigm that permits CMS to develop coverage policies for treatments that are likely to show health benefits for Medicare beneficiaries but for which the evidence base is not sufficiently developed. Two kinds of CED: (1) clinical study and (2) registry. 17
Local Coverage Determinations (LCD): Issued by local Medicare Administrative Contractors (MACs). May be requested by anyone (MAC or external party.) New formal process in 2019 to request LCDs. Limited to particular MAC jurisdiction. 18
Medicare Administrative Contractors 19 JF Noridian JE Noridian JF JH Novitas J5 WPS J6 NGS J8 WPS J15 CGS JL Novitas JK NGS JM Palmetto JJ Palmetto JN FCSO
An Overview of Coding 20
Coding is the “language of reimbursement.” Coding operationally links coverage and payment. Having a code does not guarantee reimbursement! 21
Types of Codes 22 WHO USES CODE? WHO SETS CODE? CODING SYSTEM TYPE OF CODE All Providers WHO and NCHS ICD-10-CM, Diagnoses, Vols. 1 & 2 Diagnosis Hospital Inpatient WHO and CMS ICD-10-CM, Procedures, Vol. 3 Procedure or Service Physicians, Hospital Outpatient, Clinical Labs, etc. AMA CPT-4 Procedure or Service Physicians, Hospital Outpatient, DMEPOS Suppliers, etc. CMS HCPCS Products and Certain Services Pharmacies, etc. FDA NDC Drugs
Current Procedural Terminology (CPT) Codes 23 Maintained by the AMA CPT Editorial Panel. Identify medical services furnished by physicians. 5-digit numeric codes with generic descriptors. Three types of CPT codes: Category I (permanent #####) – for established treatments Category II (performance tracking ####F) – for treatments with uncertain evidence – tracking only no payment Category III (emerging technology ####T) – for emerging technologies – tracking only no payment Application process takes at least 15 months for Category I codes, with specific clinical data requirements.
Healthcare Common Procedural Coding System (HCPCS) Codes 24 Maintained by the CMS HCPCS Workgroup. Identify items and services not identified by CPT codes. 5-digit alphanumeric codes with generic descriptors. Three types of HCPCS codes: Permanent Temporary (Q codes) Miscellaneous/Not Otherwise Classified (99 codes) CMS recently announced a semi-annual application process for devices (historically only a January deadline.)
An Overview of Payment 25
How much will the payer pay for the item or service? What is the payment methodology? Depends on the site of service and provider/supplier type. 26
Medicare Payment Systems 27 NEW TECHNOLOGY PAYMENT PROGRAM CODES CLAIMED TO GENERATE PAYMENT AMOUNT TYPE OF PAYMENT METHODOLOGY SITE OF SERVICE Add-On Payment ICD-10 Diagnosis Codes, ICD- 10 Procedure Codes IPPS MS-DRG Bundle (per discharge) (Medicare Part A) Hospital Inpatient Pass-Through Status New Technology APC ICD-10 Diagnosis Codes, CPT Codes, HCPCS Codes OPPS APC Package (per procedure) (Medicare Part B) Hospital Outpatient ICD-10 Diagnosis Codes, CPT Codes, HCPCS Codes Physician Fee Schedule (Medicare Part B) Physician ICD-10 Diagnosis Codes, HCPCS Codes DMEPOS Fee Schedule or Competitive Bidding (Medicare Part B) DMEPOS ICD-10 Diagnosis Codes, CPT Codes Clinical Laboratory Fee Schedule (Medicare Part B) Clinical Laboratory Tests
Medicare Payments for New Technology Inpatient: New Technology Add-on Payment Outpatient: “Pass-Through” Outpatient: New Technology Ambulatory Payment Classification (APC) 28
Be Realistic – This is Difficult 29 New treatments for chronic conditions like opioid addiction, ADHD and insomnia are here and they’re on your smartphone — not in a pill bottle. But the government won’t pay for them, even as tech entrepreneurs insist to Congress and the Biden administration that their digital therapeutics are the next big thing. Though the Food and Drug Administration has cleared dozens of these software-based medicines — which include apps and even video games — the Centers for Medicare and Medicaid Services can’t reimburse providers, in part because Congress hasn’t approved new billing codes that describe the therapy. Because private insurers often take their cues from the government, the companies behind these new ideas are struggling to gain traction.
Three Advanced Strategies for Digital Health 30
Strategy I: Generate FDA-Quality Clinical Trial Data 31
Articles Continue to Warn of AI Risks “Many doctors and consumer advocates fear that the tech industry, which lives by the mantra “fail fast and fix it later,” is putting patients at risk and that regulators aren’t doing enough to keep consumers safe….Early experiments in AI provide reason for caution, said Mildred Cho, a professor of pediatrics at Stanford’s Center for Biomedical Ethics….Systems developed in one hospital often flop when deployed in a different facility, Cho said. Software used in the care of millions of Americans has been shown to discriminate against minorities. And AI systems sometimes learn to make predictions based on factors that have less to do with disease than the brand of MRI machine used, the time a blood test is taken …” 32
Politico 4.4.23 Facing regulation, health industry leaders explain how to use AI responsibly B Y B E N LE ON AR D | 0 4 /0 4 /2 0 2 3 0 6 : 0 0 AM E D T The Coalition for Health AI, an alliance of major health systemsand tech companies, has released a blueprint to facilitate trust in artificial intelligence’s use in health care. In it, the coalition, whose membersincludeGoogle, Microsoft, Stanford and John Hopkins, calls for any algorithms used in thetreatment of disease to be testable, safe, transparent, and explainable, and for software developers to take steps to mitigate bias and protect privacy. That’s not always the case now. “We have a Wild West of algorithms,” said Michael Pencina, coalition co-founder and director of Duke AI Health. “There’s so much focus on development and technological progress and not enough attention to its value, quality, ethical principles or health equity implications.” Among other things, theblueprint calls for: — AI to be continuouslymonitored throughout its lifecycle to ensure transparency — Careful efforts to avoid bias in algorithms — Data security and privacy protections Why it matters: Regulators are grappling with how to regulate artificial intelligence in health care as providers use it to inform diagnoses and treatment decisions. The FDA has outlined its plans to regulate software as a medical device, in 2021 issuing guidelines for market clearance for AI or machinelearning. The White House released a voluntary “AI Bill of Rights” aimed at protecting Americans in October. And on Monday, the FDA issued draft guidanceto ease improvements to algorithms by allowing software developers to win pre-approval for them, rather than requiring them to go through an authorization process for each upgrade. The Centers for Medicare and Medicaid Services, the White House Office of Science and Technology Policy, the FDA, the National Institutes of Health and HHS’ National “We have the wild west of algorithms...”
Threatening New Focus on AI Bias/Discrimination 34 • Federal Legislation • Congressional Letters to Regulator • Congressional Letters to Health Plans
Will AI Products be Covered Without Strong Data? 35 “None of the AI products sold in the U.S. have been tested in randomized clinical trials, the strongest source of medical evidence, Topol said. The first and only randomized trial of an AI system which found that colonoscopy with computer-aided diagnosis found more small polyps than standard colonoscopy was published online in October. Few tech startups publish their research in peer-reviewed journals, which allow other scientists to scrutinize their work, according to a January article in the European Journal of Clinical Investigation. Such “stealth research” described only in press releases or promotional events often overstates a company’s accomplishments. And although software developers may boast about the accuracy of their AI devices, experts note that AI models are mostly tested on computers, not in hospitals or other medical facilities.” (underlines added) Scientific American, Artificial Intelligence Is Rushing Into Patient Care - And Could Raise Risks, Dec. 24, 2019, available at https://www.scientificamerican.com/article/artificial-intelligence-is- rushing-into-patient-care-and-could-raise-risks/
Strategy II: Engage The Medical Societies 36
37
Strategy III: Plan for Reimbursement As You Plan for FDA 38
Bring the entire team together early in the development process to discuss goals and objectives. • Clinical, regulatory, reimbursement, marketing, R&D. 39
Consider the intended patient population and the payer mix for the product. • In what settings of care will the device be used? • Are there special payer rules that will be applicable? • Will device labeling be consistent with the reimbursement strategy? 40
Clinical trials should be conducted, and structured to maximize reimbursement. • Comparative effectiveness studies important to demonstrate value proposition. • Medicare requires its beneficiaries to be part of study population • Must demonstrate an improvement in overall outcomes (safe and effective is not enough.) • Payers are increasingly looking to evidence of cost savings to justify coverage, especially for expensive treatments. 41
FDA pathway can and usually will affect coverage, coding and payment. • 510(k) may make it difficult to justify a new code and payment amount. • PMA may make it difficult to use an existing code and payment amount. • 510(k) submission may not generate the level of clinical data required by payers. • Be wary of “prevention”—it is rarely covered by Medicare. 42
Build broad support for the product. • Physician Societies • Patient Groups • Political Pressure/Legislative Strategy 43
Consider the changing payer landscape. • Fee for service is moving out. • Bundles, packages, transfer of risk, value-based payments are moving in. 44
Key Takeaways 45 • Data is becoming critical! • Start Planning on FDA- Quality Studies • It is never too early to plan your reimbursement strategy
Questions?

More Related Content

Reimbursement Bootcamp- Coding, Coverage & Payment lecture by David Farber, King & Spalding

  • 1. David J. Farber Partner dfarber@kslaw.com Preeya Noronha Pinto Partner ppinto@kslaw.com mHealth Presentation July 4, 2024 U.S. Reimbursement
  • 2. Agenda I. Introduction II. FDA and CMS – The Important Differences III. The Three Elements of Reimbursement I. Coverage II. Coding III. Payment IV. Advanced Strategies
  • 3. Introduction: Setting Expectations and Understanding Timing 3
  • 4. “ But despite . . .big digital health ambitions, the path to success will not be an easy one. Digital health companies across the world are facing … a market marred by reimbursement difficulties.” — MedTech Insight (April 23, 2018, p.14) 4
  • 5. “ As one VC investor noted, ‘Payers are pulling back on paying for new things. It is difficult to get new technologies covered. It’s taking companies three to five years … to collect enough data and go through the processes to obtain coverage following FDA approval.’” — Deloitte, Out of the valley of death: How can entrepreneurs, corporations, and investors reinvigorate early-stage medtech innovation? (April 2018, p.5) 5
  • 6. Introduction -- Why Is This Important? 6
  • 7. 7
  • 8. The Differences Between FDA and CMS 8
  • 9. FDA Approval/Clearance vs. CMS (Medicare) Coverage 9 FDA CMS “Safety and Effectiveness” FDA-approved labeling Focus on function and clinical risk vs. benefits Economic data is irrelevant Non-inferiority endpoint acceptable Focus on intended population Generally not public processes Does not publish proposed decisions “Reasonable and Necessary” CMS coverage determination (formal or informal) Focus on health benefits Economic data is important Superiority endpoint often needed Focus on Medicare beneficiaries Public processes Publishes proposed decisions
  • 10. Information Considered by FDA and CMS 10 Food and Drug Administration Center for Medicare & Medicaid Services “Well-controlled” clinical investigation data Non-clinical laboratory studies Quality system controls Labeling Post-market controls Advisory committee recommendations Published and unpublished literature “Well-controlled” clinical investigation data Clinical evidence (including FDA submissions) External technology assessments Advisory committee recommendations Position statements by relevant groups Expert opinions Public comments Economic and other cost-effectiveness data Other informal opinions
  • 12. The Basics of Reimbursement • Coverage Is the item or service eligible for payment? • Coding How is the item or service identified? • Payment What are the payment methodologies and amounts? 12
  • 13. An Overview of Coverage 13
  • 14. Medicare Coverage: Defined Benefit Category Not Excluded “Reasonable and necessary for the diagnosis or treatment of illness or injury or to improve the functioning of a malformed body member.” — Social Security Act § 1862(a)(1)(A) 14
  • 15. 15 CMS and Its Contractors Make Medicare Coverage Decisions • National Coverage Determinations (NCDs) • Local Coverage Determinations (LCDs) • Individual Consideration
  • 16. National Coverage Determinations (NCD): National and binding decision by CMS Coverage and Analysis Group (CAG). May be requested by anyone (CMS or external party.) Public process that generally takes 9-12 months once initiated. May include certain conditions for coverage (including Coverage with Evidence Development (CED)). 16
  • 17. Coverage with Evidence Development (CED) Evidence-based coverage paradigm that permits CMS to develop coverage policies for treatments that are likely to show health benefits for Medicare beneficiaries but for which the evidence base is not sufficiently developed. Two kinds of CED: (1) clinical study and (2) registry. 17
  • 18. Local Coverage Determinations (LCD): Issued by local Medicare Administrative Contractors (MACs). May be requested by anyone (MAC or external party.) New formal process in 2019 to request LCDs. Limited to particular MAC jurisdiction. 18
  • 20. An Overview of Coding 20
  • 21. Coding is the “language of reimbursement.” Coding operationally links coverage and payment. Having a code does not guarantee reimbursement! 21
  • 22. Types of Codes 22 WHO USES CODE? WHO SETS CODE? CODING SYSTEM TYPE OF CODE All Providers WHO and NCHS ICD-10-CM, Diagnoses, Vols. 1 & 2 Diagnosis Hospital Inpatient WHO and CMS ICD-10-CM, Procedures, Vol. 3 Procedure or Service Physicians, Hospital Outpatient, Clinical Labs, etc. AMA CPT-4 Procedure or Service Physicians, Hospital Outpatient, DMEPOS Suppliers, etc. CMS HCPCS Products and Certain Services Pharmacies, etc. FDA NDC Drugs
  • 23. Current Procedural Terminology (CPT) Codes 23 Maintained by the AMA CPT Editorial Panel. Identify medical services furnished by physicians. 5-digit numeric codes with generic descriptors. Three types of CPT codes: Category I (permanent #####) – for established treatments Category II (performance tracking ####F) – for treatments with uncertain evidence – tracking only no payment Category III (emerging technology ####T) – for emerging technologies – tracking only no payment Application process takes at least 15 months for Category I codes, with specific clinical data requirements.
  • 24. Healthcare Common Procedural Coding System (HCPCS) Codes 24 Maintained by the CMS HCPCS Workgroup. Identify items and services not identified by CPT codes. 5-digit alphanumeric codes with generic descriptors. Three types of HCPCS codes: Permanent Temporary (Q codes) Miscellaneous/Not Otherwise Classified (99 codes) CMS recently announced a semi-annual application process for devices (historically only a January deadline.)
  • 25. An Overview of Payment 25
  • 26. How much will the payer pay for the item or service? What is the payment methodology? Depends on the site of service and provider/supplier type. 26
  • 27. Medicare Payment Systems 27 NEW TECHNOLOGY PAYMENT PROGRAM CODES CLAIMED TO GENERATE PAYMENT AMOUNT TYPE OF PAYMENT METHODOLOGY SITE OF SERVICE Add-On Payment ICD-10 Diagnosis Codes, ICD- 10 Procedure Codes IPPS MS-DRG Bundle (per discharge) (Medicare Part A) Hospital Inpatient Pass-Through Status New Technology APC ICD-10 Diagnosis Codes, CPT Codes, HCPCS Codes OPPS APC Package (per procedure) (Medicare Part B) Hospital Outpatient ICD-10 Diagnosis Codes, CPT Codes, HCPCS Codes Physician Fee Schedule (Medicare Part B) Physician ICD-10 Diagnosis Codes, HCPCS Codes DMEPOS Fee Schedule or Competitive Bidding (Medicare Part B) DMEPOS ICD-10 Diagnosis Codes, CPT Codes Clinical Laboratory Fee Schedule (Medicare Part B) Clinical Laboratory Tests
  • 28. Medicare Payments for New Technology Inpatient: New Technology Add-on Payment Outpatient: “Pass-Through” Outpatient: New Technology Ambulatory Payment Classification (APC) 28
  • 29. Be Realistic – This is Difficult 29 New treatments for chronic conditions like opioid addiction, ADHD and insomnia are here and they’re on your smartphone — not in a pill bottle. But the government won’t pay for them, even as tech entrepreneurs insist to Congress and the Biden administration that their digital therapeutics are the next big thing. Though the Food and Drug Administration has cleared dozens of these software-based medicines — which include apps and even video games — the Centers for Medicare and Medicaid Services can’t reimburse providers, in part because Congress hasn’t approved new billing codes that describe the therapy. Because private insurers often take their cues from the government, the companies behind these new ideas are struggling to gain traction.
  • 30. Three Advanced Strategies for Digital Health 30
  • 31. Strategy I: Generate FDA-Quality Clinical Trial Data 31
  • 32. Articles Continue to Warn of AI Risks “Many doctors and consumer advocates fear that the tech industry, which lives by the mantra “fail fast and fix it later,” is putting patients at risk and that regulators aren’t doing enough to keep consumers safe….Early experiments in AI provide reason for caution, said Mildred Cho, a professor of pediatrics at Stanford’s Center for Biomedical Ethics….Systems developed in one hospital often flop when deployed in a different facility, Cho said. Software used in the care of millions of Americans has been shown to discriminate against minorities. And AI systems sometimes learn to make predictions based on factors that have less to do with disease than the brand of MRI machine used, the time a blood test is taken …” 32
  • 33. Politico 4.4.23 Facing regulation, health industry leaders explain how to use AI responsibly B Y B E N LE ON AR D | 0 4 /0 4 /2 0 2 3 0 6 : 0 0 AM E D T The Coalition for Health AI, an alliance of major health systemsand tech companies, has released a blueprint to facilitate trust in artificial intelligence’s use in health care. In it, the coalition, whose membersincludeGoogle, Microsoft, Stanford and John Hopkins, calls for any algorithms used in thetreatment of disease to be testable, safe, transparent, and explainable, and for software developers to take steps to mitigate bias and protect privacy. That’s not always the case now. “We have a Wild West of algorithms,” said Michael Pencina, coalition co-founder and director of Duke AI Health. “There’s so much focus on development and technological progress and not enough attention to its value, quality, ethical principles or health equity implications.” Among other things, theblueprint calls for: — AI to be continuouslymonitored throughout its lifecycle to ensure transparency — Careful efforts to avoid bias in algorithms — Data security and privacy protections Why it matters: Regulators are grappling with how to regulate artificial intelligence in health care as providers use it to inform diagnoses and treatment decisions. The FDA has outlined its plans to regulate software as a medical device, in 2021 issuing guidelines for market clearance for AI or machinelearning. The White House released a voluntary “AI Bill of Rights” aimed at protecting Americans in October. And on Monday, the FDA issued draft guidanceto ease improvements to algorithms by allowing software developers to win pre-approval for them, rather than requiring them to go through an authorization process for each upgrade. The Centers for Medicare and Medicaid Services, the White House Office of Science and Technology Policy, the FDA, the National Institutes of Health and HHS’ National “We have the wild west of algorithms...”
  • 34. Threatening New Focus on AI Bias/Discrimination 34 • Federal Legislation • Congressional Letters to Regulator • Congressional Letters to Health Plans
  • 35. Will AI Products be Covered Without Strong Data? 35 “None of the AI products sold in the U.S. have been tested in randomized clinical trials, the strongest source of medical evidence, Topol said. The first and only randomized trial of an AI system which found that colonoscopy with computer-aided diagnosis found more small polyps than standard colonoscopy was published online in October. Few tech startups publish their research in peer-reviewed journals, which allow other scientists to scrutinize their work, according to a January article in the European Journal of Clinical Investigation. Such “stealth research” described only in press releases or promotional events often overstates a company’s accomplishments. And although software developers may boast about the accuracy of their AI devices, experts note that AI models are mostly tested on computers, not in hospitals or other medical facilities.” (underlines added) Scientific American, Artificial Intelligence Is Rushing Into Patient Care - And Could Raise Risks, Dec. 24, 2019, available at https://www.scientificamerican.com/article/artificial-intelligence-is- rushing-into-patient-care-and-could-raise-risks/
  • 36. Strategy II: Engage The Medical Societies 36
  • 37. 37
  • 38. Strategy III: Plan for Reimbursement As You Plan for FDA 38
  • 39. Bring the entire team together early in the development process to discuss goals and objectives. • Clinical, regulatory, reimbursement, marketing, R&D. 39
  • 40. Consider the intended patient population and the payer mix for the product. • In what settings of care will the device be used? • Are there special payer rules that will be applicable? • Will device labeling be consistent with the reimbursement strategy? 40
  • 41. Clinical trials should be conducted, and structured to maximize reimbursement. • Comparative effectiveness studies important to demonstrate value proposition. • Medicare requires its beneficiaries to be part of study population • Must demonstrate an improvement in overall outcomes (safe and effective is not enough.) • Payers are increasingly looking to evidence of cost savings to justify coverage, especially for expensive treatments. 41
  • 42. FDA pathway can and usually will affect coverage, coding and payment. • 510(k) may make it difficult to justify a new code and payment amount. • PMA may make it difficult to use an existing code and payment amount. • 510(k) submission may not generate the level of clinical data required by payers. • Be wary of “prevention”—it is rarely covered by Medicare. 42
  • 43. Build broad support for the product. • Physician Societies • Patient Groups • Political Pressure/Legislative Strategy 43
  • 44. Consider the changing payer landscape. • Fee for service is moving out. • Bundles, packages, transfer of risk, value-based payments are moving in. 44
  • 45. Key Takeaways 45 • Data is becoming critical! • Start Planning on FDA- Quality Studies • It is never too early to plan your reimbursement strategy