Health Data Processing
Systemic Approaches

Focuses on the value, efficiency and problems associated with medical informatics and public health

Marius Fieschi (Author)

9781785482878, Elsevier Science

Hardback, published 3 July 2018

340 pages
22.9 x 15.1 x 2.4 cm, 0.67 kg

Health Data Processing: Systemic Approaches focuses on the design of health information systems and touches on the main themes of medical informatics and public health. The book is written for health professionals in practice or training, and is especially useful for decision-makers or future decision-makers in the field of health information systems. Users will find sections on the question of reusing data for other purposes, protection of individual liberties that this data and technologies make more acute, and the irruption of large masses of genetic data and its related problems. This book develops the methodological and conceptual aspects related to these issues.

1. Understanding the Fundamental Nature of Information and its Processing 2. A Few Questions on Information Sharing 3. The Place of Healthcare Delivery Processes in Information Systems 4. The Quality of the Urbanization of the Information System is Central to its Performance 5. Reference Terminologies in Healthcare Information Systems 6. Patient Identification in Healthcare Information Systems 7. Information System Security and Data Protection 8. Knowledge Management and Medical Decision Support 9. Managing and Integrating Clinical Data: Health Records 10. Managing and Integrating Laboratory Data and Functional Investigations 11. Managing and Integrating Medical Images 12. Managing and Integrating Telemedicine and Telehealth 13. Integrating Extra-hospital Care Data 14. Reusing Data in Healthcare 15. Integrating Data for Management and Decision Analysis 16. Data for Epidemiology and Public Health, and Big Data 17. Integrating Bioinformatics Data 18. Clinical Research Data 19. Evaluating Information Systems 20. The Governance of Healthcare Information Systems, the Hospital, Outpatient and Industrial Contexts

Subject Areas: Biomedical engineering [MQW]