Description

Book Synopsis

Though algorithms are chosen to eliminate bias in the Learning Health Systems (LHS) that support medical decision making, we are left with unconscious bias present in data due to lack of representation for marginalized populations, particularly in palliative care. Medical practitioners often lack historical foundations for decision making for patients in underrepresented populations, which lead to palliative patients being subjected to uneven quality of care and an absence of treatment goals due to a lack of advocacy and other challenges.

Data Ethics and Digital Privacy in Learning Health Systems for Palliative Medicine reviews the ethical foundations that drive our approach, data collection (public data, private data and data privacy), data stratification methodologies to support marginalized and intersectional populations, analysis techniques, algorithmic development to maintain privacy, survival analysis, result interpretation, LHS development, and LHS implementation. These methodologies address the HIPAA Privacy Rule, which clearly establishes the standard to protect digitally held health care data.

Informing both research and practice, Data Ethics and Digital Privacy in Learning Health Systems for Palliative Medicine brings attention to an important issue that lies at the intersection of medicine, science, and digital technology and communication.



Table of Contents

Chapter 1. Making the Case; Daniel J. Miori
Chapter 2. Privacy and Learning Health Systems; Daniel J. Miori
Chapter 3. Shaping the Continuum of Care Through Public Policy and Data; Thomas R. Martin
Chapter 4. Public Data Sources: Cleaning and Wrangling; Virginia M Miori
Chapter 5. Public Data Sources: Sizing the Palliative Population; Virginia M Miori
Chapter 6. Private Data Sources, Data Privacy and Data Simulations for Palliative LHS; Virginia M Miori
Chapter 7. Synthea Descriptive Analysis; Virginia M Miori
Chapter 8. Palliative LHS Analysis; Virginia M Miori
Chapter 9. Data Repository Design for Public Data Analysis; Brian W. Segulin
Chapter 10. Palliative LHS Development and API to Ensure Data Privacy; Brian W. Segulin
Chapter 11. Learning Health Systems Ethics Review; Daniel J. Miori

Data Ethics and Digital Privacy in Learning

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    £80.00

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    Order before 4pm tomorrow for delivery by Wed 5 Aug 2026.

    A Hardback by Virginia M. Miori, Daniel J. Miori, Flavia Burton

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      Publisher: Emerald Publishing Limited
      Publication Date: Publication Date: 15/11/2023
      ISBN13: 9781802623109, 978-1802623109
      ISBN10: 1802623108

      Description

      Book Synopsis

      Though algorithms are chosen to eliminate bias in the Learning Health Systems (LHS) that support medical decision making, we are left with unconscious bias present in data due to lack of representation for marginalized populations, particularly in palliative care. Medical practitioners often lack historical foundations for decision making for patients in underrepresented populations, which lead to palliative patients being subjected to uneven quality of care and an absence of treatment goals due to a lack of advocacy and other challenges.

      Data Ethics and Digital Privacy in Learning Health Systems for Palliative Medicine reviews the ethical foundations that drive our approach, data collection (public data, private data and data privacy), data stratification methodologies to support marginalized and intersectional populations, analysis techniques, algorithmic development to maintain privacy, survival analysis, result interpretation, LHS development, and LHS implementation. These methodologies address the HIPAA Privacy Rule, which clearly establishes the standard to protect digitally held health care data.

      Informing both research and practice, Data Ethics and Digital Privacy in Learning Health Systems for Palliative Medicine brings attention to an important issue that lies at the intersection of medicine, science, and digital technology and communication.



      Table of Contents

      Chapter 1. Making the Case; Daniel J. Miori
      Chapter 2. Privacy and Learning Health Systems; Daniel J. Miori
      Chapter 3. Shaping the Continuum of Care Through Public Policy and Data; Thomas R. Martin
      Chapter 4. Public Data Sources: Cleaning and Wrangling; Virginia M Miori
      Chapter 5. Public Data Sources: Sizing the Palliative Population; Virginia M Miori
      Chapter 6. Private Data Sources, Data Privacy and Data Simulations for Palliative LHS; Virginia M Miori
      Chapter 7. Synthea Descriptive Analysis; Virginia M Miori
      Chapter 8. Palliative LHS Analysis; Virginia M Miori
      Chapter 9. Data Repository Design for Public Data Analysis; Brian W. Segulin
      Chapter 10. Palliative LHS Development and API to Ensure Data Privacy; Brian W. Segulin
      Chapter 11. Learning Health Systems Ethics Review; Daniel J. Miori

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