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Clinical Decision Support for Pharmacogenomic Precision Medicine
Foundations and Implementation
- 1st Edition - June 14, 2022
- Editors: Beth Devine, Richard David Boyce, Kristin Wiisanen
- Language: English
- Paperback ISBN:9 7 8 - 0 - 1 2 - 8 2 4 4 5 3 - 1
- eBook ISBN:9 7 8 - 0 - 1 2 - 8 2 4 4 5 4 - 8
Clinical Decision Support for Pharmacogenomic Precision Medicine: Foundations and Implementation offers overviews, methods and strategies for translating genomic medicine to clinic… Read more
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Request a sales quoteClinical Decision Support for Pharmacogenomic Precision Medicine: Foundations and Implementation offers overviews, methods and strategies for translating genomic medicine to clinical practice. The book's authors explore incorporating pharmacogenetics into electronic health records, CDS methods and infrastructure for delivery, economic evaluation, the hospital administrations’ role and needs in integration, and patient counseling aspects. The book empowers clinicians, researchers, translational scientists, and data and IT experts to effectively navigate the complex landscape of CDS for pharmacogenomic precision medicine. Illustrative case studies of existing gene networks include CSER, eMERGE, the IGNITE network, DIGITIZE, the CDS Learning Network (RTI), ClinGen, Ubiquitous and CDS Hooks.
- Offers an applied, case-driven discussion of CDS for pharmacogenomic precision medicine
- Illustrates key concepts, contemporary developments, and future directions using examples of existing gene networks
- Features contributions from leading voices in precision medicine and clinical decision support
Active researchers, basic and translational scientists, and IT professionals in the areas of human genomics, bioinformatics, pharmacology, prenatal testing, and electronic healthcare records; genetic counselors; hospital administrators, clinicians and students of life science, genetics, and medicine
- Cover image
- Title page
- Table of Contents
- Copyright
- Contributors
- About the editors
- Section One. Foundations of clinical decision support and pharmacogenomic precision medicine
- Chapter One. Overview of effective pharmacogenomic clinical decision support
- Introduction
- Pharmacogenomics and precision medicine
- Potential benefits of CDS
- Role of CDS in pharmacogenomic precision medicine
- Developing and implementing CDS for pharmacogenomic precision medicine
- Other considerations for pharmacogenomic CDS
- Overview of this book
- Conclusion
- Chapter Two. Scientific evidence and sources of knowledge for pharmacogenomics
- Introduction
- Sources of scientific evidence of pharmacogenomic associations
- Sources of pharmacogenomic knowledge
- Pharmacogene variation consortium
- Pharmacogenomics knowledgebase
- PharmGKB annotations
- PharmGKB levels of evidence
- PharmGKB pathways
- Very important pharmacogene summaries
- Drug label annotations
- Pharmacogenomic guideline annotations
- Dutch Pharmacogenetics Working Group of the Royal Dutch Pharmacists Association (KNMP)
- Clinical Pharmacogenetics Implementation Consortium
- Allele definition table
- Allele functionality table
- Diplotype–phenotype table
- Allele frequency table
- Pre- and post-test alerts
- PharmCAT
- Conclusion
- Chapter Three. Laboratory considerations for pharmacogenomic testing
- Introduction
- Clinical laboratory regulation
- Genetic terminology and nomenclature
- Determining genes and variants to test
- Obtaining, tracking, and assessing DNA quality of samples
- Testing platforms
- Copy number assessment
- Conclusion
- Chapter Four. Advancing equity in the promise of pharmacogenomics
- Introduction
- Pharmacogenomic CDS to advance healthcare equity
- Potential for pharmacogenomics to increase healthcare disparities
- Maximizing benefit and minimizing harm with pharmacogenomic CDS
- Conclusion
- Section Two. Developing and building clinical decision support for pharmacogenomic precision medicine
- Chapter Five. Clinical decision support methods and infrastructure
- Introduction
- Modes of information delivery in CDS
- Vendor-specific electronic health record systems CDS capabilities
- Third-party clinical decision support systems and application programming interfaces
- Storage and access of genomic data
- Conclusion
- Chapter Six. The role of machine learning to predict treatment response and target drug therapies
- Introduction
- P4 medicine and deep phenotyping to target drug therapies
- Machine learning to identify groups and predict treatment response
- Data preparation and data to inform clinical decision support
- Validation and evaluation of machine learning–driven CDS
- Explanation and interpretation of machine learning–driven CDS
- Implementation and dissemination of machine learning–driven CDS
- Polygenic risk profiling
- Conclusion
- Chapter Seven. Usability and human-centered design
- Introduction
- Why is pharmacogenomics usability hard?
- Evaluation
- Human-centered design in pharmacogenomics: selected examples
- Conclusion
- Chapter Eight. Clinical considerations for precision medicine clinical decision support
- Introduction
- CDS design: the five rights
- Implementing and maintaining manually developed rules
- Predictive algorithms in pharmacogenomics
- Clinical considerations for healthcare disparities
- Conclusion
- Section Three. Adoption and delivery of clinical decision support for pharmacogenomic precision medicine
- Chapter Nine. Patient-facing clinical decision support for pharmacogenomic precision medicine
- Introduction
- Foundational concepts of patient clinical decision support for pharmacogenomics
- Regulatory issues surrounding patient-facing CDS for pharmacogenomics
- Current landscape of patient-facing clinical decision support for pharmacogenomics
- Opportunities and challenges with patient-facing CDS
- Conclusion
- Chapter Ten. Role of the genetic counselor in pharmacogenomic precision medicine
- Introduction
- Genetic counseling in pharmacogenomic precision medicine
- Genetic counselor practices and training
- Patient counseling considerations and challenges for pharmacogenomic precision medicine
- Conclusion
- Chapter Eleven. A learning health system approach to delivery and adoption of clinical decision support
- Introduction
- Operationalizing the LHS approach
- Requirements of the LHS approach
- Delivery and adoption of CDS
- The LHS approach to pharmacogenomics CDS in action: a hypothetical case study of Stellar Health
- Conclusion
- Chapter Twelve. Integration of clinical decision support infrastructure and translating into real-world applications
- Introduction
- Challenges with documenting test results in the electronic health record (EHR)
- Applying pharmacogenomic test results throughout a patient's lifetime
- Conclusion
- Index
- No. of pages: 296
- Language: English
- Edition: 1
- Published: June 14, 2022
- Imprint: Academic Press
- Paperback ISBN: 9780128244531
- eBook ISBN: 9780128244548
BD
Beth Devine
Beth Devine is Research Assistant Professor in The Comparative Health Outcomes, Policy and Economics (CHOICE) Institute; Formerly Pharmaceutical, Outcomes Research and Policy Program (PORPP), Department of Pharmacy, University of Washington, USA.
Affiliations and expertise
Research Assistant Professor; The Comparative Health Outcomes, Policy and Economics (CHOICE) Institute; Formerly Pharmaceutical, Outcomes Research and Policy Program (PORPP), Department of Pharmacy, University of Washington, USARB
Richard David Boyce
Dr. Richard D. Boyce is an Assistant Professor of Biomedical Informatics in the University of Pittsburgh School of Medicine. His research studies the use of informatics and pharmacoepidemiology to support safe and effective medication therapy for older adults. He has published more than a dozen peer-reviewed papers including a systematic review of the effectiveness of antidepressants for nursing home residents, a review of pharmacokinetic drug interactions affecting antidepressants, a study concordance between various sources of psychotropic drug-drug interaction information, and a pilot study of an innovation to enhance drug product label information on drug safety, efficacy. His current research studies active monitoring interventions for patient exposed to drug-drug interactions in the nursing home, and a how to best present clinical pharmacogenomics statements to clinicians and patients.
Affiliations and expertise
Assistant Professor of Biomedical Informatics in the University of Pittsburgh School of Medicine, PA, USARead Clinical Decision Support for Pharmacogenomic Precision Medicine on ScienceDirect