Features of statistical and operational research methods and tools being used to improve the healthcare industry
With a focus on cutting-edge approaches to the quickly growing field of healthcare,Healthcare Analytics: From Data to Knowledge to Healthcare Improvementprovides an integrated and comprehensive treatment on recent research advancements in data-driven healthcare analytics in an effort to provide more personalized and smarter healthcare services. Emphasizing data and healthcare analytics from an operational management and statistical perspective, the book details how analytical methods and tools can be utilized to enhance healthcare quality and operational efficiency.
Organized into two main sections,Part Ifeatures biomedical and health informatics and specifically addresses the analytics of genomic and proteomic data; physiological signals from patient-monitoring systems; data uncertainty in clinical laboratory tests; predictive modeling; disease modeling for sepsis; and the design of cyber infrastructures for early prediction of epidemic events.Part IIfocuses on healthcare delivery systems, including system advances for transforming clinic workflow and patient care; macro analysis of patient flow distribution; intensive care units; primary care; demand and resource allocation; mathematical models for predicting patient readmission and postoperative outcome; physicianpatient interactions; insurance claims; and the role of social media in healthcare.Healthcare Analytics: From Data to Knowledge to Healthcare Improvementalso features:
Contributions from well-known international experts who shed light on new approaches in this growing area
Discussions on contemporary methods and techniques to address the handling of rich and large-scale healthcare data as well as the overall optimization of healthcare system operations
Numerous real-world examples and case studies that emphasize the vast potential of statistical and operational research tools and techniques to address the big data environment within the healthcare industry
Plentiful applications that showcase analytical methods and tools tailored for successful healthcare systems modeling and improvement
The book is an ideal reference for academics and practitioners in operations research, management science, applied mathematics, statistics, business, industrial and systems engineering, healthcare systems, and economics.Healthcare Analytics: From Data to Knowledge to Healthcare Improvementis also appropriate for graduate-level courses typically offered within operations research, industrial engineering, business, and public health departments.
HUI YANG, PhD,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, PhD,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 HealthCare, 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
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. McGuire 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 DSouza
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
9 Analytics for Health: Design of Cyber-infrastructures for Multiscale and Real-Time Cholera Outbreak Predictions 261
Matteo Convertino, Arabi Mouhaman, Glenn Morris Jr, and Song Liang
9.1 Introduction 261
9.2 Materials and Methods 267
9.3 Analytics of Global Sensitivity and Uncertainty Analyses 277
9.4 Results 279
9.5 Discussions 287
9.6 Conclusions 289
Acknowledgments 290
Appendix 290
Metamodels 290
References 292
PART II ANALYTICS FOR HEALTHCARE DELIVERY 299
10 Systems Analytics: Modeling and Optimizing ClinicWorkflow 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
10.1 Introduction 302
10.2 Background 304
10.3 Challenges and Objectives 305
10.4 Methods and Design of Study 306
10.5 Computational Results, Implementation, and ED Performance Comparison 323
10.6 Benefits and Impacts 330
10.7 Scientific Advances 335
Acknowledgments 336
References 337
11 A Multiobjective Simulation Optimization of the Macrolevel Patient Flow Distribution 341
Yunzhe Qiu and Jie Song
11.1 Introduction 341
11.2 Literature Review 343
11.3 Problem Description and Modeling 346
11.4 Methodology 350
11.5 Case Study: Adjusting Patient Flow for a Two-Level Healthcare System Centered on the Puth 354
11.6 Conclusions and the Future Work 367
Acknowledgments 368
References 369
12 Analysis of Resource Intensive Activity Volumes in us Hospitals 373
Shivon Boodhoo and Sanchoy Das
12.1 Introduction 373
12.2 Structural Classification of Hospitals 375
12.3 Productivity Analysis of Hospitals 377
12.4 Resource and Activity Database for us Hospitals 379
12.5 Activity-Based Modeling of Hospital Operations 382
12.6 Resource use Profile of Hospitals from HUC Activity Data 389
12.7 Summary 395
References 396
13 Discrete-Event Simulation for Primary Care Redesign: Review and a Case Study 399
Xiang Zhong, Molly Williams, Jingshan Li, Sally A. Kraft, and Jeffrey S. Sleeth
13.1 Introduction 399
13.2 Review of Relevant Literature 400
13.3 A Simulation Case Study at a Pediatric Clinic 407
13.4 WhatIf Analyses 414
13.5 Conclusions 420
References 420
14 Temporal and Spatiotemporal Models for Ambulance Demand 427
Zhengyi Zhou and David S. Matteson
14.1 Introduction 427
14.2 Temporal Ambulance Demand Estimation 429
14.3 Spatiotemporal Ambulance Demand Estimation 436
14.4 Conclusions 447
References 448
15 Mathematical Optimization and Simulation Analyses for Optimal Liver Allocation Boundaries 451
Naoru Koizumi, Monica Gentili, Rajesh Ganesan, Debasree DasGupta, Amit Patel, Chun-Hung Chen, Nigel Waters, and Keith Melancon
15.1 Introduction 452
15.2 Methods 454
15.3 Results 461
15.4 Conclusions 471
Acknowledgment 473
References 473
16 Predictive Analytics in 30-Day Hospital Readmissions for Heart Failure Patients 477
Si-Chi Chin, Rui Liu, and Senjuti B. Roy
16.1 Introduction 478
16.2 Analytics in Prediction Hospital Readmission Risk 479
16.3 Analytics in Recommending Intervention Strategies 485
16.4 Related Work 495
16.5 Conclusion 497
References 497
17 Heterogeneous Sensing and Predictive Modeling of Postoperative Outcomes 501
Yun Chen, Fabio Leonelli, and Hui Yang
17.1 Introduction 501
17.2 Research Background 504
17.3 Research Methodology 512
17.4 Materials and Experimental Design 529
17.5 Experimental Results 529
17.6 Discussion and Conclusions 536
Acknowledgments 537
References 537
18 Analyzing PatientPhysician Interaction in Consultation for Shared Decision Making 541
Thembi Mdluli, Joyatee Sarker, Carolina Vivas-Valencia, Nan Kong, and Cleveland G. Shields
18.1 Introduction 541
18.2 Literature Review 543
18.3 Our Recent Data Mining Studies 548
18.4 Future Directions 553
18.5 Concluding Remarks 557
References 558
19 The History and Modern Applications of Insurance Claims Data in Healthcare Research 561
Margrét V. Bjarndóttir, David Czerwinski, and Yihan Guan
19.1 Introduction 561
19.2 Healthcare Cost Predictions 569
19.3 Measuring Quality of Care 578
19.4 Conclusions 586
References 586
20 Understanding the Role of Social Media in Healthcare via Analytics: a Health Plan Perspective 593
Sinjini Mitra and Rema Padman
20.1 Introduction 593
20.2 Literature Review 594
20.3 Case Study Description 600
20.4 Research Methods and Analytics Tools 602
20.5 Results and Discussions 606
20.6 Conclusions 622
References 623
INDEX 627
