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The Impact of FDA Digital Health Guidance on CDS

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The FDA recently released guidance documents on the use of clinical decision support (CDS) and medical software that may be of concern to forward-thinking healthcare innovators who rely on these technologies to deliver exceptional care and improve outcomes. What will be the impact of this guidance on machine learning and predictive analytics efforts? How will the guidance affect timelines, costs, and effectiveness of ongoing machine learning implementation? As healthcare delivery increasingly relies on digital innovation and support, more questions emerge about the governance of the accompanying tools and technology. This article provides a summary of the FDA guidance on CDS, how CDS is defined, whether or not CDS is exempt from regulation, and how the FDA intends to enforce compliance. It also summarizes the FDA guidance on medical software, what software is exempt from regulation, and helps to answer some of the questions surrounding the digital health space.

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The Impact of FDA Digital Health Guidance on CDS

  1. 1. The Impact of FDA Digital Health Guidance on CDS, Medical Software, and Machine Learning Carolyn Wong Simpkins, MD, PhD & Daniel Orenstein, General Counsel
  2. 2. © 2016 Health Catalyst Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. FDA Health Guidance for the 21st Century The FDA recently released guidance documents on select provisions of the 21st Century Cures Act (the Cures Act). Digital health products and services providers are most concerned about guidance on the use of clinical decision support (CDS) and medical software. For healthcare organizations working these fast-changing technologies and constantly pushing digital innovation, federal guidance that hints at changing the regulation of their pioneering efforts may send up warning flags.
  3. 3. © 2016 Health Catalyst Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. FDA Health Guidance for the 21st Century There is little cause for alarm. The FDA regularly issues clarification on how it is going to enforce statutes and regulations to provide useful interpretive information to the industry. The FDA digital health guidance documents are not regulation, they are non-binding, informational communications. Digital health executives and developers can still use the FDA’s guidance to understand the current approach it is taking toward regulation, and how this approach impacts CDS and medical software development, as well as provider workflows.
  4. 4. © 2016 Health Catalyst Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. FDA Guidance on CDS Healthcare organizations use CDS to reduce errors and improve efficiency, standardization, and cost savings. The FDA guidance on CDS (the CDS Guidance) describes what types of software tools the FDA considers to be CDS, and which CDS is excluded from FDA regulation as a medical device.
  5. 5. © 2016 Health Catalyst Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. FDA Guidance on CDS The CDS Guidance states that software functions must meet the following three criteria to be considered CDS: 1. Not intended to acquire, process, or analyze a medical image or a signal from an in vitro diagnostic device or a pattern or signal from a signal acquisition system; 2. Intended for the purpose of displaying, analyzing, or printing medical information about a patient or other medical information (such as peer-reviewed clinical studies and clinical practice guidelines); 3. Intended for the purpose of supporting or providing recommendations to a health care professional about prevention, diagnosis, or treatment of a disease or condition.
  6. 6. © 2016 Health Catalyst Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. FDA Guidance on CDS Having met these three criteria, CDS must then meet a fourth criterion to fall outside the FDA’s definition of a medical device and be exempt from regulation: 4. Intended for the purpose of enabling such health care professional to independently review the basis for such recommendations that such software presents so that it is not the intent that such health care professional rely primarily on any of such recommendations to make a clinical diagnosis or treatment decision regarding an individual patient.
  7. 7. © 2016 Health Catalyst Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. FDA Guidance on CDS The CDS Guidance provides examples of CDS software functions that do and do not meet these criteria. Two key elements are provided in the guidance to further define the criteria for exemption: 1. The healthcare practitioner must be able to independently evaluate the basis of the CDS recommendations. 2. The CDS recommendations must be based on publicly available clinical guidelines (i.e., studies, published literature, clinical practice guidelines). These two elements beg the question: What about using algorithms and machine learning as the basis for CDS recommendations?
  8. 8. © 2016 Health Catalyst Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. Machine Learning as a Basis for CDS Recommendations Healthcare machine learning models produce information that improves patient care. This information may not always be based on published literature, but its reliability is correlated to significant historical patient data and actual outcomes. Providers will exercise clinical judgment before taking any action on the output of machine learning, which is often in the form of recommendations, alerts, and risk prioritizations.
  9. 9. © 2016 Health Catalyst Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. Machine Learning as a Basis for CDS Recommendations What’s concerning is that an algorithm could operate on unspecified health data within a “black box” and deliver a result, the basis of which a provider might not understand. The FDA is appropriately addressing this issue by requiring disclosure of the inputs used in order for software to be excluded from regulation. Health Catalyst agrees with the principle that any applications using algorithms should have functionality that allows users to view the input features and variables, including the clinical guidelines or findings that helped shape the predictive model.
  10. 10. © 2016 Health Catalyst Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. Machine Learning as a Basis for CDS Recommendations It is also important to note that, as discussed in an earlier article, a clinical intermediary will always be part of machine learning-enabled CDS to impose judgement and connect any recommendations (produced by the machine learning model) to relevant clinical guidelines. Health Catalyst and other organizations will seek clarification from the FDA on the use of algorithms and machine learning as the basis for providing CDS recommendations, in lieu of, or in addition to, publicly available clinical guidelines.
  11. 11. © 2016 Health Catalyst Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. Enforcement Discretion The CDS Guidance provides informative examples of CDS functionality that fall into the following three categories: 1. CDS functionality that does not constitute a medical device—these are CDS functions that do not meet the definition of a medical device; 2. CDS functionality that may meet the definition of a medical device but for which the FDA does not intend to enforce compliance; and 3. CDS functionality that the FDA intends to regulate as a medical device
  12. 12. © 2016 Health Catalyst Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. Enforcement Discretion Where the FDA “does not intend to enforce compliance” means that the decision to not regulate non-medical-device software is based on the FDA’s discretion. In the future, the FDA could modify its policy, which could result in a more significant impact on vendors that use CDS with machine learning functionality. While the FDA’s approach introduces uncertainty, it is our opinion that, because there have been enough policies issued over a sustained period, radical shifts in enforcement policy are unlikely.
  13. 13. © 2016 Health Catalyst Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. Patient Decision Support The CDS Guidance also addresses patient decision support (PDS) software, regarding functionality for use by patients rather than clinicians. This guidance has similar criteria to CDS and indicates that PDS will not be regulated as a device. The FDA appears to be drawing the distinction because PDS likely applies to a different audience (patients). For example, PDS guidance applies to patient- accessed modules and functions within Health Catalyst’s Care Coordination application in the Care Management suite.
  14. 14. © 2016 Health Catalyst Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. FDA Guidance on Medical Software The FDA guidance on changes to existing medical software policies (the Medical Software Guidance) provides clarification on policy changes made by the Cures Act. The Medical Software Guidance builds upon several previous FDA guidance documents and clarifies that software functions classified into any of four areas are exempt from regulation as a medical device: 1. Software function intended for administrative support of a healthcare facility. 2. Software function intended for maintaining or encouraging a healthy lifestyle. 3. Software function intended to serve as electronic patient records. 4. Software function intended for transferring, storing, converting formats, or displaying data and results.
  15. 15. © 2016 Health Catalyst Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. Additional Ramifications of the FDA Digital Health Guidance As long as software vendors comply with the FDA guidance, any cost impact should be minimal, provided that their software does not seem to fall within a category that the FDA indicates is a medical device. If vendors aren’t already providing transparency through their applications, then workflow processes could be impacted as they move from a black box approach to one in which data inputs used by algorithms are disclosed to users.
  16. 16. © 2016 Health Catalyst Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. Additional Ramifications of the FDA Digital Health Guidance Providing these disclosures could potentially involve more time and effort by providers because it could add an input review phase with an internal clinician panel, although this would be discretionary. The CDS Guidance and Medical Software Guidance were issued in draft form to allow the FDA to consider public comments. While possible, it is not likely that the exemptions will change significantly in the final documents.
  17. 17. © 2016 Health Catalyst Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. Additional Ramifications of the FDA Digital Health Guidance Vendors might expect to see clarification on how to disclose the basis for recommendations or conclusions derived by CDS, and where machine learning fits into these disclosures. The FDA will also likely include a few more examples of what functionality it considers to be exempt from, or subject to, regulation when it issues its final guidance later in 2018.
  18. 18. © 2016 Health Catalyst Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. Good News for Digital Health Innovators There are no major surprises with the new FDA guidance documents in terms of what will be regulated or not. The CDS Guidance reassures practitioners that CDS functions that meet the non-device criteria will either be excluded from regulation or the FDA will not enforce regulation. This approach can help promote innovation by ensuring a quicker time to market—and value— for developers and CDS system users.
  19. 19. © 2016 Health Catalyst Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. Good News for Digital Health Innovators In its own words, the FDA’s intent is to foster, not inhibit, innovation, and to encourage the development of tools that can help people be more informed about their health. Though these documents don’t establish rules, they should be taken seriously because they contain useful information about how the FDA will enforce its rules, and how it interprets the Cures Act.
  20. 20. © 2016 Health Catalyst Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. Good News for Digital Health Innovators The industry response to these new guidance documents should be positive. The policies provide appropriate oversight, promote software transparency, and let digital health developers “know where they stand relative to the FDA’s regulatory framework.” Most importantly, the guidance supports the success of vendors and healthcare organizations as they continue working to improve the features and functionality of their CDS systems and medical software.
  21. 21. © 2016 Health Catalyst Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. For more information: “This book is a fantastic piece of work” – Robert Lindeman MD, FAAP, Chief Physician Quality Officer
  22. 22. © 2016 Health Catalyst Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. More about this topic Link to original article for a more in-depth discussion. The Impact of FDA Digital Health Guidance on CDS, Medical Software, and Machine Learning Machine Learning in Healthcare: How it Supports Clinician Decisions—and Why Clinicians are Still in Charge Carolyn Wong Simpkins, MD, PhD, Chief Medical Informatics Officer; Daniel Orenstein, Senior VP, General Counsel, and Secretary Machine Learning 101: 5 Easy Steps for Using it in Healthcare Michael Mastanduno, PhD, Data Scientist The Why And How Of Machine Learning And AI: An Implementation Guide For Healthcare Leaders Kenneth Kleinberg, Managing Director, the Advisory Board Company; Eric Just, Sr. VP of Product Development Healthcare Decision Support: A Modern Tool for Today's Chief Nursing Officer Dr. John Haughom, Senior Advisor, Health Catalyst Why Healthcare Decision Support Is No Longer Optional for Chief Operating Officers Dr. John Haughom, Senior Advisor, Health Catalyst
  23. 23. © 2016 Health Catalyst Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. Other Clinical Quality Improvement Resources Click to read additional information at www.healthcatalyst.com Carolyn Wong Simpkins is a physician, health technology executive, and health system transformation leader. She joined the leadership team at Health Catalyst as Chief Medical Informatics Officer to lead the development of medical content and accelerate the infusion of clinical insight its next-generation suite of products, and is also helping to shape machine learning algorithms so they can best be used to influence important care decisions. She brings to this role insights from her experiences practicing medicine in diverse settings, from academic medical centers to critical access hospitals and community health centers, combined with a keen understanding of federal health policy and its systemic implications, gleaned from her time on the staff of the U.S. House of Representatives Ways and Means Health subcommittee and her observations from working globally on health system transformation programs and solutions for the UK based British Medical Journal. She is passionate about data, technology, design and disrupting healthcare paradigms to improve health outcomes for all. Carolyn is a Fellow of the second class of the Liberty Fellowship and a member of the Aspen Global Leadership Network. Carolyn Wong Simpkins, MD, PhD
  24. 24. © 2016 Health Catalyst Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. Prior to joining Health Catalyst Dan Orenstein was at athenahealth, Inc. (NASDAQ: ATHN) for 10 years, the last 7 as General Counsel and Secretary. Prior to that, Dan practiced in the areas of corporate, intellectual property, and healthcare law with law firms in Boston and Washington, D.C. He has written and presented on health care law and IT topics throughout his career. He also served as a leader of the American Health Lawyers Association’s Health IT practice group. Other Clinical Quality Improvement Resources Click to read additional information at www.healthcatalyst.com Daniel Orenstein

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