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Intro; Dedication; Foreword; Preface; Epilogue; Contents; Part I: Research Design and Methodologies; Chapter 1: Design Science Research Opportunities in Health Care; 1.1 Design Science Research Concepts; 1.2 Healthcare Challenges and Design Science Research; 1.3 A Survey of Recent DSR Projects in Health Care; 1.3.1 Medical Systems; 1.3.2 Clinical Protocols; 1.3.3 Medical Devices; 1.3.4 Electronic Medical Records (EMRs); 1.3.5 Healthcare Data Analytics; 1.3.6 Healthcare Governance; 1.3.7 Healthcare Delivery Services; 1.3.8 Public Health and Preventive Care; 1.3.9 Pharmaceutical Systems.
1.3.10 Miscellaneous1.4 Healthcare Case Vignettes; 1.4.1 Vignette A: Sensors for Monitoring Blood Glucose; 1.4.2 Vignette B: Calorie Cruncher; 1.5 Discussion; 1.6 Conclusions; References; Chapter 2: Using a Survey Methodology to Measure User Satisfaction with Clinical Information Systems; 2.1 Introduction; 2.2 Methods; 2.3 Results; 2.3.1 CIS User Satisfaction; 2.3.2 Training and Technical Support Satisfaction; 2.4 Discussion; 2.5 Conclusion; References; Chapter 3: Application of Hermeneutics in Understanding New Emerging Technologies in Health Care: An Example from mHealth Case Study.
3.1 Introduction3.2 Hermeneutics; 3.3 An Example of Hermeneutics in an mHealth Case Study Research; 3.4 Conclusion; References; Chapter 4: IS/IT Governance in Health Care: An Integrative Model; 4.1 Introduction; 4.2 Literature Review; 4.2.1 IS/IT Governance; 4.2.2 Value and Business Value; 4.3 Research Objective and Research Questions; 4.4 Research Design and Methodology; 4.4.1 Research Methodology; 4.4.2 Research Strategy: Case Study; 4.4.3 Data Collection and Analysis; 4.5 Findings; 4.5.1 The IS/IT Governance Structure in Place; 4.5.2 The Impact of Adopting This IS/IT Governance Approach.
4.5.3 The Factors That Affect IS/IT Governance in Health Care4.5.3.1 People Factors; 4.5.3.2 Process Factors; 4.5.3.3 Technology Factors; 4.6 How to Build Robust IS/IT Governance Practices; 4.7 Discussion; 4.8 Conclusion; References; Chapter 5: Predictive Analytics in Health Care: Methods and Approaches to Identify the Risk of Readmission; 5.1 Introduction; 5.2 Background; 5.2.1 Predictive Analytics; 5.2.2 Application Areas; 5.2.2.1 Sales and Marketing; 5.2.2.2 Insurance; 5.2.2.3 Finance; 5.2.2.4 Law Enforcement; 5.2.2.5 Health Care; 5.3 Risk Prediction Models in Health Care; 5.3.1 Overview.
5.3.1.1 Sample Size5.3.1.2 Split Ratio; 5.3.1.3 Object of Investigation; 5.3.1.4 Readmission Period; 5.3.1.5 Independent Variables; 5.3.1.6 Issues; 5.3.2 Methods; 5.3.2.1 Regression Analysis; 5.3.2.2 Support Vector Machines (SVMs); 5.3.2.3 Decision Trees (DT); 5.3.2.4 Random Forests (RF); 5.3.2.5 Artificial Neural Networks (ANN); 5.3.3 Evaluation of Methods; 5.4 Discussion; References; Chapter 6: An Ontology for Capturing Pervasive Mobile Solution Benefits in Diabetes Care: Insights from a Longitudinal Multi-country Study; 6.1 Background.
1.3.10 Miscellaneous1.4 Healthcare Case Vignettes; 1.4.1 Vignette A: Sensors for Monitoring Blood Glucose; 1.4.2 Vignette B: Calorie Cruncher; 1.5 Discussion; 1.6 Conclusions; References; Chapter 2: Using a Survey Methodology to Measure User Satisfaction with Clinical Information Systems; 2.1 Introduction; 2.2 Methods; 2.3 Results; 2.3.1 CIS User Satisfaction; 2.3.2 Training and Technical Support Satisfaction; 2.4 Discussion; 2.5 Conclusion; References; Chapter 3: Application of Hermeneutics in Understanding New Emerging Technologies in Health Care: An Example from mHealth Case Study.
3.1 Introduction3.2 Hermeneutics; 3.3 An Example of Hermeneutics in an mHealth Case Study Research; 3.4 Conclusion; References; Chapter 4: IS/IT Governance in Health Care: An Integrative Model; 4.1 Introduction; 4.2 Literature Review; 4.2.1 IS/IT Governance; 4.2.2 Value and Business Value; 4.3 Research Objective and Research Questions; 4.4 Research Design and Methodology; 4.4.1 Research Methodology; 4.4.2 Research Strategy: Case Study; 4.4.3 Data Collection and Analysis; 4.5 Findings; 4.5.1 The IS/IT Governance Structure in Place; 4.5.2 The Impact of Adopting This IS/IT Governance Approach.
4.5.3 The Factors That Affect IS/IT Governance in Health Care4.5.3.1 People Factors; 4.5.3.2 Process Factors; 4.5.3.3 Technology Factors; 4.6 How to Build Robust IS/IT Governance Practices; 4.7 Discussion; 4.8 Conclusion; References; Chapter 5: Predictive Analytics in Health Care: Methods and Approaches to Identify the Risk of Readmission; 5.1 Introduction; 5.2 Background; 5.2.1 Predictive Analytics; 5.2.2 Application Areas; 5.2.2.1 Sales and Marketing; 5.2.2.2 Insurance; 5.2.2.3 Finance; 5.2.2.4 Law Enforcement; 5.2.2.5 Health Care; 5.3 Risk Prediction Models in Health Care; 5.3.1 Overview.
5.3.1.1 Sample Size5.3.1.2 Split Ratio; 5.3.1.3 Object of Investigation; 5.3.1.4 Readmission Period; 5.3.1.5 Independent Variables; 5.3.1.6 Issues; 5.3.2 Methods; 5.3.2.1 Regression Analysis; 5.3.2.2 Support Vector Machines (SVMs); 5.3.2.3 Decision Trees (DT); 5.3.2.4 Random Forests (RF); 5.3.2.5 Artificial Neural Networks (ANN); 5.3.3 Evaluation of Methods; 5.4 Discussion; References; Chapter 6: An Ontology for Capturing Pervasive Mobile Solution Benefits in Diabetes Care: Insights from a Longitudinal Multi-country Study; 6.1 Background.