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Clinical Research Computing
A Practitioner's Handbook
- 1st Edition - April 27, 2016
- Author: Prakash Nadkarni
- Language: English
- Paperback ISBN:9 7 8 - 0 - 1 2 - 8 0 3 1 3 0 - 8
- eBook ISBN:9 7 8 - 0 - 1 2 - 8 0 3 1 4 5 - 2
Clinical Research Computing: A Practitioner’s Handbook deals with the nuts-and-bolts of providing informatics and computing support for clinical research. The subjects that the… Read more
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Request a sales quoteClinical Research Computing: A Practitioner’s Handbook deals with the nuts-and-bolts of providing informatics and computing support for clinical research. The subjects that the practitioner must be aware of are not only technological and scientific, but also organizational and managerial. Therefore, the author offers case studies based on real life experiences in order to prepare the readers for the challenges they may face during their experiences either supporting clinical research or supporting electronic record systems. Clinical research computing is the application of computational methods to the broad field of clinical research. With the advent of modern digital computing, and the powerful data collection, storage, and analysis that is possible with it, it becomes more relevant to understand the technical details in order to fully seize its opportunities.
- Offers case studies, based on real-life examples where possible, to engage the readers with more complex examples
- Provides studies backed by technical details, e.g., schema diagrams, code snippets or algorithms illustrating particular techniques, to give the readers confidence to employ the techniques described in their own settings
- Offers didactic content organization and an increasing complexity through the chapters
Practitioners and clinical researchers involved in health IT systems; graduate students studying medical and health informatics; students in health IT programs.
- Foreword
- Chapter 1: An Introduction to Clinical Research Concepts
- Abstract
- 1.1. Introduction
- 1.2. The level of evidence hierarchy
- 1.3. A bird’s-eye view of statistics in clinical research
- 1.4. Clinical studies of investigational therapies
- 1.5. Clinical studies of established therapies
- 1.6. Experimental design of comparative-effectiveness studies
- 1.7. Evaluation of medical software
- 1.8. Further reading
- Chapter 2: Supporting Clinical Research Computing: Technological and Nontechnological Considerations
- Abstract
- 2.1. Technological aspects: software development
- 2.2. Nontechnical factors: overview
- 2.3. Attitude: service versus research
- 2.4. Technical skills
- 2.5. General skills and breadth of knowledge
- 2.6. Communication skills
- 2.7. Managing people and projects
- 2.8. Personality traits
- 2.9. Negotiation skills
- 2.10. Choosing your collaborators
- 2.11. Topics in clinical research support
- Chapter 3: Core Informatics Technologies: Data Storage
- Abstract
- 3.1. Types of data elements: databases 101
- 3.2. Transactional databases versus analytical databases
- 3.3. Database indexes
- 3.4. Managing integrated (structured + unstructured) data
- 3.5. Nonrelational approaches to data management: “NoSQL” systems
- 3.6. Final words
- Chapter 4: Core Technologies: Machine Learning and Natural Language Processing
- Abstract
- 4.1. Introduction to machine learning
- 4.2. The bridge between traditional statistics and machine learning
- 4.3. A basic glossary of machine learning
- 4.4. Regression-based methods
- 4.5. Regression-type methods for categorical outcome variables
- 4.6. Artificial neural networks
- 4.7. Bayes’ theorem and naïve bayes methods
- 4.8. Methods for sequential data
- 4.9. Introduction to natural language processing
- 4.10. Further reading
- Chapter 5: Software for Patient Care Versus Software for Clinical Research Support: Similarities and Differences
- Abstract
- 5.1. Introduction
- 5.2. Similarities between EHRs and CSDMSs
- 5.3. EHRs are specialized for clinical care and workup
- 5.4. CSDMSs: study participants (subjects) are not necessarily patients
- 5.5. Study protocol: overview
- 5.6. Configuration information
- 5.7. Recruitment and eligibility
- 5.8. Study calendar
- 5.9. Multiinstitutional or multinational research scenarios
- Chapter 6: Clinical Research Information Systems: Using Electronic Health Records for Research
- Abstract
- 6.1. Biospecimen management systems
- 6.2. Grants management systems
- 6.3. Clinical research workflow support systems
- 6.4. Clinical study data management systems
- 6.5. Using EHRs for research
- 6.6. Effective interoperation between a CSDMS and EHR-related software
- Chapter 7: Computer Security, Data Protection, and Privacy Issues
- Abstract
- 7.1. Security basics
- 7.2. Special concerns related to personal data
- 7.3. Protecting data
- 7.4. Institutional preparedness
- 7.5. HIPAA matters: calibrating the level of privacy to the level of acceptable risk
- 7.6. A primer on electronic intrusion
- 7.7. State of healthcare systems with respect to intrusion resistance
- 7.8. Role of the US government
- Chapter 8: Mobile Technologies and Clinical Computing
- Abstract
- 8.1. Introduction
- 8.2. Uses of mobile devices: historical and recent
- 8.3. Applications in biomedical research
- 8.4. Limitations of mobile devices
- Chapter 9: Clinical Data Repositories: Warehouses, Registries, and the Use of Standards
- Abstract
- 9.1. Introduction
- 9.2. Operational data store
- 9.3. Data warehouses and data marts
- 9.4. Clinical registries
- 9.5. Encoding data prior to warehousing: standardization challenges
- 9.6. Relationships between healthcare IT and health informatics groups
- Chapter 10: Core Technologies: Data Mining and “Big Data”
- Abstract
- 10.1. Introduction
- 10.2. An overview of data-mining methodology
- 10.3. Limitations and caveats
- 10.4. The human component
- 10.5. Conclusions
- 10.6. Additional resources for learning
- Chapter 11: Conclusions: The Learning Health System of the Future
- Abstract
- 11.1. Introduction
- 11.2. Origin and inspiration for the LHS proposal
- 11.3. Challenges of KM/BPR for US healthcare
- Subject index
- No. of pages: 240
- Language: English
- Edition: 1
- Published: April 27, 2016
- Imprint: Academic Press
- Paperback ISBN: 9780128031308
- eBook ISBN: 9780128031452
PN
Prakash Nadkarni
Dr. Nadkarni has been working in the field of biomedical informatics since 1989, with over 100 peer-reviewed publications in the field. He is the lead developer of TrialDB, an open-source clinical study data management system, which is used at multiple locations nationally and internationally. He is an Associate Editor of the Journal of the American Medical Informatics Association (JAMIA) since 2005, and was elected Fellow of the American College of Medical Informatics (ACMI) in 2002.
Affiliations and expertise
Research Professor, University of Iowa School of Medicine, Iowa City, IA, USARead Clinical Research Computing on ScienceDirect