[{"innerBlocks":[],"name":"core\/freeform","postId":145,"blockType":{"name":"core\/freeform","keywords":[],"attributes":{"content":{"type":"string","source":"raw"},"lock":{"type":"object"}},"providesContext":[],"usesContext":[],"selectors":[],"supports":{"className":false,"customClassName":false,"reusable":false},"styles":[],"variations":[],"apiVersion":3,"title":"Classic","description":"Use the classic WordPress editor.","category":"text"},"originalContent":"While artificial intelligence has the potential to address the epidemic of diagnostic errors in healthcare, the industry must overcome the challenges and limitations of these new digital tools. That\u2019s the contention of a new book<\/a> on clinical decision support co-authored by John Halamka, MD, president of the Mayo Clinic Platform, and healthcare writer Paul Cerrato.\u201cAlgorithms that take advantage of machine learning, neural networks and a variety of other types of artificial intelligence (AI) can help address many of the shortcomings of human intelligence,\u201d explain Halamka and Cerrato, who make the point that the complexity of medicine now exceeds the capacity of the human mind.The book\u2019s authors contend that such complexity \u201crequires humility for clinicians with years of experience successfully diagnosing patients\u2019 ills to admit that they may be missing as many disorders as they catch.\u201dNonetheless, while AI has the potential to address many of the shortcomings of human intelligence, the authors also outline in the book the criticisms, obstacles and limitations of this technology\u2014including the fact that the evidence to show that it is having an impact on patient outcomes is mixed. \u201cAmong the criticisms discussed is the relative lack of hard scientific evidence supporting some of the latest algorithms and the \u2018explainability\u2019 dilemma,\u201d write Halamka and Cerrato. \u201cMost machine learning systems are based on advanced statistics and mind-bending mathematical equations, which have made many clinicians skeptical about their worth.\u201dThey also make the case that \u201cany attempt to reinvent CDS also needs to tackle the outdated paradigm that still serves as the underpinning for most patient care\u201d\u2014namely that the \u201creductionistic mindset (that) insists that most diseases have a single cause.\u201d In addition, Halamka and Cerrato charge that the \u201ccurrent medical model relies too heavily on a population-based approach to medicine\u201d and that this \u201cone-size-fits-all model is being replaced by a precision medicine approach that takes into account a long list of risk factors.\u201dHalamka, who previously served as executive director of the Health Technology Exploration Center for Beth Israel Lahey Health in Massachusetts, joined the Mayo Clinic on January 1.

At Mayo, Halamka now leads a portfolio of new digital platform businesses focused on transforming health by leveraging AI, the Internet of Things and an ecosystem of partners. However, he emphasizes in a recent blog post that while his new book is being published during his tenure at Mayo Clinic, \u201cit is not endorsed by Mayo Clinic and represents the personal opinions of Paul and me.\u201dHalamka and Cerrato also previously co-authored a 2017 book entitled Realizing the Promise of Precision Medicine: The Role of Patient Data, Mobile Technology and Consumer Engagement<\/i>. However, they contend that their new book on CDS is the \u201cfirst to be published about platform thinking\u201d and attempts to provide an in-depth look at the emerging technologies that are transforming the way clinicians manage patients.At the same time, Halamka and Cerrato note that their \u201centhusiastic take on digital innovation should not give readers the impression that AI will ever replace a competent physician.\u201d Still, they add that there is \u201clittle doubt that a competent physician who uses all the tools that AI has to offer will soon replace the competent physician who ignores these tools.\u201d","saveContent":"While artificial intelligence has the potential to address the epidemic of diagnostic errors in healthcare, the industry must overcome the challenges and limitations of these new digital tools. That\u2019s the contention of a new book<\/a> on clinical decision support co-authored by John Halamka, MD, president of the Mayo Clinic Platform, and healthcare writer Paul Cerrato.\u201cAlgorithms that take advantage of machine learning, neural networks and a variety of other types of artificial intelligence (AI) can help address many of the shortcomings of human intelligence,\u201d explain Halamka and Cerrato, who make the point that the complexity of medicine now exceeds the capacity of the human mind.The book\u2019s authors contend that such complexity \u201crequires humility for clinicians with years of experience successfully diagnosing patients\u2019 ills to admit that they may be missing as many disorders as they catch.\u201dNonetheless, while AI has the potential to address many of the shortcomings of human intelligence, the authors also outline in the book the criticisms, obstacles and limitations of this technology\u2014including the fact that the evidence to show that it is having an impact on patient outcomes is mixed. \u201cAmong the criticisms discussed is the relative lack of hard scientific evidence supporting some of the latest algorithms and the \u2018explainability\u2019 dilemma,\u201d write Halamka and Cerrato. \u201cMost machine learning systems are based on advanced statistics and mind-bending mathematical equations, which have made many clinicians skeptical about their worth.\u201dThey also make the case that \u201cany attempt to reinvent CDS also needs to tackle the outdated paradigm that still serves as the underpinning for most patient care\u201d\u2014namely that the \u201creductionistic mindset (that) insists that most diseases have a single cause.\u201d In addition, Halamka and Cerrato charge that the \u201ccurrent medical model relies too heavily on a population-based approach to medicine\u201d and that this \u201cone-size-fits-all model is being replaced by a precision medicine approach that takes into account a long list of risk factors.\u201dHalamka, who previously served as executive director of the Health Technology Exploration Center for Beth Israel Lahey Health in Massachusetts, joined the Mayo Clinic on January 1.At Mayo, Halamka now leads a portfolio of new digital platform businesses focused on transforming health by leveraging AI, the Internet of Things and an ecosystem of partners. However, he emphasizes in a recent blog post that while his new book is being published during his tenure at Mayo Clinic, \u201cit is not endorsed by Mayo Clinic and represents the personal opinions of Paul and me.\u201dHalamka and Cerrato also previously co-authored a 2017 book entitled Realizing the Promise of Precision Medicine: The Role of Patient Data, Mobile Technology and Consumer Engagement<\/i>. However, they contend that their new book on CDS is the \u201cfirst to be published about platform thinking\u201d and attempts to provide an in-depth look at the emerging technologies that are transforming the way clinicians manage patients.At the same time, Halamka and Cerrato note that their \u201centhusiastic take on digital innovation should not give readers the impression that AI will ever replace a competent physician.\u201d Still, they add that there is \u201clittle doubt that a competent physician who uses all the tools that AI has to offer will soon replace the competent physician who ignores these tools.\u201d","order":0,"get_parent":{},"attributes":[],"attributesType":{"content":{"type":"string","source":"raw"},"lock":{"type":"object"}},"dynamicContent":""}]

AI can reinvent clinical decision support, but obstacles remain

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