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Clinical Decision Support
The Road to Broad Adoption
- 2nd Edition - March 26, 2014
- Editor: Robert Greenes
- Language: English
- Paperback ISBN:9 7 8 - 0 - 1 2 - 8 1 0 0 2 4 - 0
- Hardback ISBN:9 7 8 - 0 - 1 2 - 3 9 8 4 7 6 - 0
- eBook ISBN:9 7 8 - 0 - 1 2 - 8 0 0 5 4 2 - 2
With at least 40% new or updated content since the last edition, Clinical Decision Support, 2nd Edition explores the crucial new motivating factors poised to accelerate Clinical… Read more
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Request a sales quoteWith at least 40% new or updated content since the last edition, Clinical Decision Support, 2nd Edition explores the crucial new motivating factors poised to accelerate Clinical Decision Support (CDS) adoption. This book is mostly focused on the US perspective because of initiatives driving EHR adoption, the articulation of 'meaningful use', and new policy attention in process including the Office of the National Coordinator for Health Information Technology (ONC) and the Center for Medicare and Medicaid Services (CMS). A few chapters focus on the broader international perspective. Clinical Decision Support, 2nd Edition explores the technology, sources of knowledge, evolution of successful forms of CDS, and organizational and policy perspectives surrounding CDS.
Exploring a roadmap for CDS, with all its efficacy benefits including reduced errors, improved quality, and cost savings, as well as the still substantial roadblocks needed to be overcome by policy-makers, clinicians, and clinical informatics experts, the field is poised anew on the brink of broad adoption. Clinical Decision Support, 2nd Edition provides an updated and pragmatic view of the methodological processes and implementation considerations. This book also considers advanced technologies and architectures, standards, and cooperative activities needed on a societal basis for truly large-scale adoption.
- At least 40% updated, and seven new chapters since the previous edition, with the new and revised content focused on new opportunities and challenges for clinical decision support at point of care, given changes in science, technology, regulatory policy, and healthcare finance
- Informs healthcare leaders and planners, health IT system developers, healthcare IT organization leaders and staff, clinical informatics professionals and researchers, and clinicians with an interest in the role of technology in shaping healthcare of the future
Health care professionals, medical informatics researchers and students, policy makers, IT development managers, and various clinical investigators
- Foreword
- Preface
- Preface to the first edition
- Section I: Computer-based Clinical Decision Support: Overview, Status, and Challenges
- Section I. Computer-based Clinical Decision Support: Overview, Status, and Challenges
- Chapter 1. Definition, Scope, and Challenges
- 1.1 Introduction
- 1.2 Definition of computer-based clinical decision support
- 1.3 Features of CDS
- 1.4 The tale of a relationship
- 1.5 Scope and plan of this book
- References
- Chapter 2. A Brief History of Clinical Decision Support: Technical, Social, Cultural, Economic, and Governmental Perspectives
- 2.1 Primary research methodologies that have been pursued and extended
- 2.2 Driving forces for CDS
- 2.3 Conclusion
- References
- Chapter 3. Features of Computer-Based Clinical Decision Support
- 3.1 CDS and the human
- 3.2 Design and structure of CDS
- 3.3 Other considerations
- References
- Chapter 4. The Role of Quality Measurement and Reporting Feedback as a Driver for Care Improvement
- 4.1 Introduction
- 4.2 Quality measures and clinical decision support: similarities and differences
- 4.3 Creating a quality measure
- 4.4 Constructing the quality measure equation
- 4.5 Identifying CDS interventions based on the quality measure
- 4.6 A CDS rule component taxonomy
- 4.7 The details about the CDS rules component taxonomy
- 4.8 The CDS rules component taxonomy as a driver for quality measurement and care improvement
- 4.9 Assuring the quality of a measure
- 4.10 Driving care improvement
- References
- Section II: Experience with CDS Development and Adoption: Case Studies, National Initiatives, and Lessons Learned
- Section II. Experience with CDS Development and Adoption: Case Studies, National Initiatives, and Lessons Learned
- Chapter 5. Regenstrief Medical Informatics: Experiences with Clinical Decision Support Systems
- 5.1 Introduction
- 5.2 History
- 5.3 Expanding roles for decision support
- 5.4 Conclusion
- References
- Chapter 6. Patients, Doctors, and Information Technology Clinical Decision Support at Brigham and Women’s Hospital and Partners HealthCare
- 6.1 Introduction
- 6.2 History
- 6.3 Clinical decision support and inpatient CPOE at BWH
- 6.4 Decision support delivered using the outpatient electronic health record
- 6.5 Overarching studies
- 6.6 Overarching lessons
- 6.7 Future directions
- References
- Chapter 7. Computer-Based Approaches to Improving Healthcare Quality and Safety at LDS Hospital: Intermountain Healthcare Experience
- 7.1 Overview
- 7.2 Introduction
- 7.3 Tools for information management
- 7.4 Tools for focusing attention
- 7.5 Tools for patient-specific consultation
- 7.6 Conclusions and lessons learned
- References
- Chapter 8. International Dimensions of Clinical Decision Support
- 8.1 Introduction
- 8.2 CDS experience in the UK
- 8.3 CDS experience in low and middle income countries
- 8.4 Conclusions
- References
- Chapter 9. Current State of CDS Utilization
- 9.1 Introduction
- 9.2 Academic prototypes
- 9.3 Standards and sharing of interoperable content and tools
- 9.4 Users
- 9.5 Other considerations
- References
- Section III: Sources of Knowledge for Clinical Decision Support
- Section III. Sources of Knowledge for Clinical Decision Support
- Chapter 10. Human-Intensive Techniques
- 10.1 Introduction
- 10.2 Theoretical basis for knowledge acquisition
- 10.3 Cognitive task analysis
- 10.4 History and current status of computer-based knowledge acquisition
- 10.5 Conclusions
- References
- Chapter 11. Generation of Knowledge for Clinical Decision Support: Statistical and Machine Learning Techniques
- 11.1 Introduction
- 11.2 Learning from data
- 11.3 Overview of logistic regression
- 11.4 Overview of some machine learning models
- 11.5 Prediction models in medicine
- 11.6 Conclusions
- References
- Chapter 12. Modernizing Evidence Synthesis for Evidence-Based Medicine
- 12.1 Introduction
- 12.2 Systematic reviews and meta-analysis: the premise and promise
- 12.3 The systematic review pipeline
- 12.4 Statistical methods in meta-analysis
- 12.5 Meta-analysis of complex datasets
- 12.6 Accessing systematic reviews, meta-analyses and field synopses
- 12.7 Conclusion
- References
- Chapter 13. Big Data and Population-Based Decision Support
- 13.1 Introduction
- 13.2 Core concepts
- 13.3 Population health data
- 13.4 Decision support to improve identification and response to population health needs
- 13.5 Decision support to implement interventions to address specific population health needs
- 13.6 Quantitative methods
- 13.7 Examples of population health decision support
- 13.8 Challenges
- Acknowledgments
- References
- Chapter 14. Clinical Decision Support for Personalized Medicine
- 14.1 Introduction
- 14.2 Challenges to adoption of genomic and personalized medicine
- 14.3 Clinical decision support as a solution to achieving genomic and personalized medicine
- 14.4 Focal areas of CDS for personalized medicine
- 14.5 Complexities and considerations
- 14.6 Conclusions
- References
- Section IV: The Technology of Clinical Decision Support
- Section IV. The Technology of Clinical Decision Support
- Chapter 15. Decision Rules and Expressions
- 15.1 Introduction
- 15.2 Procedural knowledge
- 15.3 Knowledge as production rules
- 15.4 The hybrid approach for knowledge transfer: Arden Syntax
- 15.5 Expression languages
- 15.6 Standard data models for decision rules
- 15.7 Toward further standardization: quality measures and health e-decisions
- 15.8 Future work
- 15.9 Conclusions
- References
- Chapter 16. Guidelines and Workflow Models
- 16.1 Introduction
- 16.2 Supporting knowledge acquisition
- 16.3 Formal methods for modeling and specifying CIGs
- 16.4 Integration of guidelines with workflow
- 16.5 CIG and workflow verification and exception-handling
- 16.6 CIG and careflow enactment tools
- 16.7 Process mining and improvement
- 16.8 Discussion
- Acknowledgment
- References
- Recommended resources
- Chapter 17. Ontologies, Vocabularies and Data Models
- 17.1 Introduction
- 17.2 Referencing data in decision logic
- 17.2.1 The curly braces problem
- 17.3 The need for coded data
- 17.3.1 Advantages of coded data
- 17.3.2 Enabling a “Learning Health System” environment
- 17.3.3 The opportunity and challenges of “Big Data”
- 17.3.4 The challenge from REDCap
- 17.4 Modeling formalisms
- 17.5 Issues of pre- and postcoordination
- 17.6 Placing information in the terminology model or the information model
- 17.7 Iso-semantic models
- 17.8 Data representation using name-value pairs
- 17.9 Terminology and the implementation of clinical decision support interventions
- 17.10 Contextual restrictions within the terminology
- 17.11 What needs to be done to allow sharing of decision logic?
- 17.12 Conclusions
- References
- Chapter 18. Grouped Knowledge Elements
- 18.1 Introduction
- 18.2 Clinical documentation
- 18.3 Order sets
- 18.4 Current standards for grouped knowledge elements
- 18.5 Conclusions
- References
- Chapter 19. Infobuttons and Point of Care Access to Knowledge
- 19.1 Introduction
- 19.2 Understanding and addressing clinician information needs
- 19.3 Infobuttons
- 19.4 Question answering systems
- 19.5 The HL7 standard for context-aware decision support
- 19.6 Ongoing and future research
- 19.7 Conclusions
- References
- Chapter 20. Formal Representations and Semantic Web Technologies
- 20.1 Introduction
- 20.2 Background
- 20.3 Semantics of terminologies: taxonomies, ontologies, classification, thesauri, and other hierarchical structures
- 20.4 A brief introduction to logic-based ontologies and OWL
- 20.5 Other issues in terminology
- 20.6 Introduction to RDF, SKOS, SPARQL and network formalisms
- 20.7 Basics of rules
- 20.8 Ontologies and rules
- 20.9 Reasoning algorithms
- 20.10 Conclusions
- References
- Chapter 21. The Role of Standards: What We Can Expect and When
- 21.1 The case for standards
- 21.2 CDS development with and without standards
- 21.3 Areas in need of standardization
- 21.4 Assessment of current state of CDS standards and needed future work
- 21.5 Beyond the standards – what is needed for widespread CDS adoption?
- 21.6 How important are standards?
- 21.7 Vision for potential future impact of standards
- References
- Section V: Adoption of Clinical Decision Support
- Section V. Adoption of Clinical Decision Support
- Chapter 22. Cognitive Considerations for Health Information Technology
- 22.1 Introduction
- 22.2 Challenges for cognitive support in health care
- 22.3 Developing cognitive support: distributed cognition
- 22.4 Building systems with distributed cognition in mind
- 22.5 Developing tools to support cognition
- 22.6 Summary
- References
- Chapter 23. Organizational and Cultural Change
- 23.1 Introduction
- 23.2 Organizational issues related to clinical decision support
- 23.3 Planning with these issues in mind
- 23.4 Development, implementation, and modification
- 23.5 Evaluation and maintenance
- 23.6 Summary and conclusions
- Acknowledgments
- Resources
- References
- Chapter 24. Managing the Investment in Clinical Decision Support
- 24.1 Introduction
- 24.2 Clinical knowledge management
- 24.3 Organization of the effort
- 24.4 Key IT strategies and considerations
- 24.5 Evaluation of the impact and value of knowledge management
- 24.6 Conclusions
- References
- Chapter 25. A Clinical Decision Support Implementation Guide: Practical Considerations
- 25.1 Introduction
- 25.2 Foundational issues
- 25.3 Implementation issues
- 25.4 Conclusions
- Acknowledgment
- References
- Chapter 26. Legal and Regulatory Issues Related to the Use of Clinical Software in Health Care Delivery
- 26.1 Introduction
- 26.2 Legal issues related to using embedded and free-standing decision support software in clinical settings
- 26.3 Responsibility for CDS software at the institutional level and potential governmental regulation
- 26.4 Conclusion
- Acknowledgment
- References
- Chapter 27. Consumers and Clinical Decision Support
- 27.1 Introduction
- 27.2 Clinical decision support
- 27.3 Opportunities to improve consumer clinical decision support
- References
- Section VI: The Journey to Widespread Use of Clinical Decision Support
- Section VI. The Journey to Widespread Use of Clinical Decision Support
- Chapter 28. A Clinical Knowledge Management Program
- 28.1 Introduction and program overview
- 28.2 Knowledge engineering process
- 28.3 Software infrastructure
- 28.4 Integration with clinical systems
- 28.5 Future directions
- 28.6 Conclusions
- Acknowledgments
- References
- Chapter 29. Integration of Knowledge Resources into Applications to Enable CDS: Architectural Considerations
- 29.1 Introduction
- 29.2 Generic system architectures, examples, and their pros and cons
- 29.3 Philosophy on role of knowledge resources
- 29.4 Role of the EHR/CIS architecture
- 29.5 Scaling considerations for CDS
- 29.6 Other issues to be considered
- 29.7 Examples of specific approaches
- 29.8 Conclusions
- References
- Chapter 30. Looking Ahead: The Road to Broad Adoption
- 30.1 Where we are now
- 30.2 Impediments still with us
- 30.3 Need for new mechanisms
- 30.4 Organization of process
- 30.5 A possible paradigm for future CDS
- 30.6 Looking ahead: epilogue as prologue
- References
- Index
- No. of pages: 930
- Language: English
- Edition: 2
- Published: March 26, 2014
- Imprint: Academic Press
- Paperback ISBN: 9780128100240
- Hardback ISBN: 9780123984760
- eBook ISBN: 9780128005422
RG
Robert Greenes
Robert Greenes, MD, PhD, holds an MD and a PhD in Computer Science from Harvard. Dr Greenes is an expert in health care information technology/informatics and has made contributions to the field over many years, initially at Harvard and more recently at Arizona State University in partnership with Mayo Clinic. His passion is the use of information technology in health care to make "the right thing the easy thing to do". He is Ira A. Fulton Chair of Biomedical Informatics at the ASU, a member of the National Academy of Medicine and of the International Academy of Health Sciences Informatics, and a Fellow of the American College of Radiology, American College of Medical Informatics, and the Society for Imaging Informatics in Medicine. He was the 2008 recipient of the Morris F. Collen Award for lifetime impact on the field of biomedical informatics, from the American College of Medical Informatics.
Affiliations and expertise
Emeritus Professor of Biomedical Informatics, Arizona State University, Phoenix, AZ, United StatesRead Clinical Decision Support on ScienceDirect