Hui Yang & Eva K. Lee 
Healthcare Analytics [PDF ebook] 
From Data to Knowledge to Healthcare Improvement

LIST OF CONTRIBUTORS xvii
PREFACE xxi
PART I ADVANCES IN BIOMEDICAL AND HEALTH INFORMATICS 1
1 Recent Development in Methodology for Gene Network Problems and Inferences 3
Sung W. Han and Hua Zhong
1.1 Introduction 3
1.2 Background 5
1.3 Genetic Data Available 7
1.4 Methodology 7
1.5 Search Algorithm 13
1.6 PC Algorithm 15
1.7 Application/Case Studies 16
1.8 Discussion 23
1.9 Other Useful Softwares 23
Acknowledgments 24
References 24
2 Biomedical Analytics and Morphoproteomics: An Integrative Approach for Medical Decision Making for Recurrent or Refractory Cancers 31
Mary F. Mc Guire and Robert E. Brown
2.1 Introduction 31
2.2 Background 32
2.3 Methodology 37
2.4 Case Studies 46
2.5 Discussion 51
2.6 Conclusions 52
Acknowledgments 53
References 53
3 Characterization and Monitoring of Nonlinear Dynamics and Chaos in Complex Physiological Systems 59
Hui Yang, Yun Chen, and Fabio Leonelli
3.1 Introduction 59
3.2 Background 61
3.3 Sensor-Based Characterization and Modeling of Nonlinear Dynamics 65
3.4 Healthcare Applications 80
3.5 Summary 88
Acknowledgments 90
References 90
4 Statistical Modeling of Electrocardiography Signal for Subject Monitoring and Diagnosis 95
Lili Chen, Changyue Song, and Xi Zhang
4.1 Introduction 95
4.2 Basic Elements of ECG 96
4.3 Statistical Modeling of ECG for Disease Diagnosis 99
4.4 An Example: Detection of Obstructive Sleep Apnea from a Single ECG Lead 115
4.5 Materials and Methods 115
4.6 Results 118
4.7 Conclusions and Discussions 121
4.8 Conclusion 121
References 121
5 Modeling and Simulation of Measurement Uncertainty in Clinical Laboratories 127
Varun Ramamohan, James T. Abbott, and Yuehwern Yih
5.1 Introduction 127
5.2 Background and Literature Review 129
5.3 Model Development Guidelines 138
5.4 Implementation of Guidelines: Enzyme Assay Uncertainty Model 141
5.5 Discussion and Conclusions 152
References 154
6 Predictive Analytics: Classification in Medicine and Biology 159
Eva K. Lee
6.1 Introduction 159
6.2 Background 161
6.3 Machine Learning with Discrete Support Vector Machine Predictive Models 163
6.4 Applying DAMIP to Real-World Applications 170
6.5 Summary and Conclusion 182
Acknowledgments 183
References 183
7 Predictive Modeling in Radiation Oncology 189
Hao Zhang, Robert Meyer, Leyuan Shi, Wei Lu, and Warren D’Souza
7.1 Introduction 189
7.2 Tutorials of Predictive Modeling Techniques 191
7.3 Review of Recent Predictive Modeling Applications in Radiation Oncology 194
7.4 Modeling Pathologic Response of Esophageal Cancer to Chemoradiotherapy 199
7.5 Modeling Clinical Complications after Radiation Therapy 205
7.6 Modeling Tumor Motion with Respiratory Surrogates 211
7.7 Conclusion 215
References 215
8 Mathematical Modeling of Innate Immunity Responses of Sepsis: Modeling and Computational Studies 221
Chih-Hang J. Wu, Zhenshen Shi, David Ben-Arieh, and Steven Q. Simpson
8.1 Background 221
8.2 System Dynamic Mathematical Model (SDMM) 223
8.3 Pathogen Strain Selection 224
8.4 Mathematical Models of Innate Immunity of Air 239
8.5 Discussion 247
8.6 Conclusion 254
References 254
PART II ANALYTICS FOR HEALTHCARE DELIVERY 299
9 Systems Analytics: Modeling and Optimizing Clinic Workflow and Patient Care 301
Eva K. Lee, Hany Y. Atallah, Michael D. Wright, Calvin Thomas IV, Eleanor T. Post, Daniel T. Wu, and Leon L. Haley Jr
9.1 Introduction 302
9.2 Background 304
9.3 Challenges and Objectives 305
9.4 Methods and Design of Study 306
9.5 Computational Results, Implementation, and ED Performance Comparison 323
9.6 Benefits and Impacts 330
9.7 Scientific Advances 335
Acknowledgments 336
References 337
10 A Multiobjective Simulation Optimization of the Macrolevel Patient Flow Distribution 341
Yunzhe Qiu and Jie Song
10.1 Introduction 341
10.2 Literature Review 343
10.3 Problem Description and Modeling 346
10.4 Methodology 350
10.5 Case Study: Adjusting Patient Flow for a Two-Level Healthcare System Centered on the Puth 354
10.6 Conclusions and the Future Work 367
Acknowledgments 368
References 369
11 Analysis of Resource Intensive Activity Volumes in us Hospitals 373
Shivon Boodhoo and Sanchoy Das
11.1 Introduction 373
11.2 Structural Classification of Hospitals 375
11.3 Productivity Analysis of Hospitals 377
11.4 Resource and Activity Database for us Hospitals 379
11.5 Activity-Based Modeling of Hospital Operations 382
11.6 Resource use Profile of Hospitals from HUC Activity Data 389
11.7 Summ

HUI YANG, Ph D, is Associate Professor in the Harold and Inge Marcus Department of Industrial and Manufacturing Engineering at The Pennsylvania State University. His research interests include sensor-based modeling and analysis of complex systems for process monitoring/control; system diagnostics/ prognostics; quality improvement; and performance optimization with special focus on nonlinear stochastic dynamics and the resulting chaotic, recurrence, self-organizing behaviors.
EVA K. LEE, Ph D, is Professor in the H. Milton Stewart School of Industrial and Systems Engineering at the Georgia Institute of Technology, Director of the Center for Operations Research in Medicine and Health Care, and Distinguished Scholar in Health System, Health Systems Institute at both Emory University School of Medicine and Georgia Institute of Technology. Her research interests include health-risk prediction; early disease prediction and diagnosis; optimal treatment strategies and drug delivery; healthcare outcome analysis and treatment prediction; public health and medical preparedness; large-scale healthcare/medical decision analysis and quality improvement; clinical translational science; and business intelligence and organization transformation.