Ai in healthcare : How artificial intelligence is changing IT operations and infrastructure / Robert Shimonski.

By: Shimonski, Robert [author.]
Language: English Publisher: Indianapolis : John Wiley and Sons, 2021Description: 1 online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9781119680017Subject(s): Artificial intelligence -- Medical applications | Medical informatics | -- Medical applicationsGenre/Form: Electronic books.DDC classification: 610.28563 Online resources: Full text is available at Wiley Online Library Click here to view
Contents:
TABLE OF CONTENTS Introduction xvii Chapter 1 Healthcare IT and the Growing Need for AI Operations 1 A Brief History of AI and Healthcare 3 Healthcare IT Expansion and Growth 4 Data Overload 5 Digital Transformation of Healthcare 7 The Science of Healthcare Innovation 9 Artificial Intelligence in Healthcare 10 Healthcare IT Operations 14 AIOps Platform Strategy 18 Platform Types 19 Customer Experience and AIOps 20 AIOps Considerations and Goals 22 Summary 23 Chapter 2 AI Healthcare Operations (Clinical) 25 Clinical Impact of AIOps 26 Gaining a Competitive Edge with Intelligent Cloud, Data Analytics, and AI 27 Design and Innovation 29 AIOps for Healthcare Delivery 33 AIOps for Service Performance 38 Clinical AI, AIOps, and Future Platform Convergence 39 Security and Privacy 41 Why Security is Paramount in AIOps 41 HIPAA, PHI, and PII Protection 43 Summary 45 Chapter 3 AI Healthcare Operations (Operational Infrastructure) 47 Getting Started with AIOps 48 Strategy of AIOps Deployments 50 Creating a Scope 51 AIOps Platforms, Products, and Services Selection 54 AIOps Product Selection: General Topics 54 Product Review: AIOps Tool Splunk 57 Product Review: AIOps Tool ServiceNow 60 Product Review: AIOps Tool Dynatrace 64 Workflow and Event Management Design 67 Service Design with AIOps 67 Day-to-Day Operational Management 69 Summary 70 Chapter 4 Project Planning for AIOps 73 Project Planning Requirements 74 Assigning a Project Manager 75 Creating a Project Plan 77 Building the Project Plan 78 Planning a Healthcare System Project 83 Deploying AIOps 85 Deploying AIOps into the Environment 86 Configuring AIOps in the Environment 88 Summary 91 Chapter 5 Using AI for Metrics, Performance, and Reporting 93 System Performance Metrics 94 Information Technology Metrics 94 Using AI for Metrics, Performance, and Reporting 98 Strategy and Goals for AI Deployment 101 Benefits of Healthcare AIOps Service Performance Reporting 102 Developing Usable AIOps Metrics 104 Helpful Tools You Can Use 105 Gathering Usable Metrics 107 Using Dynatrace 108 Using Splunk 110 Using ServiceNow 117 Clinical and IT Metrics and Collective Actions 123 Usable Healthcare AIOps Dashboards 127 Summary 128 Chapter 6 AIOps and Automation in Healthcare Operations 131 Automation, Workflow, Process, and Intelligence Design 132 Designing the Framework for Automation 132 Understanding Automation 133 Improved User Experience 134 Designing Workflow and Process Engineering 135 Quality Control and Assurance 138 Foundational and Required Design Items 139 Configuring and Using AIOps Automation 146 Monitoring and Operating Event Management Services 148 Creating and Realizing Automation, ML, and AI 152 Automating Splunk and IT Service Analyzer 155 Splunk IT Service Intelligence 160 When Should You Use AI and ML? 162 Summary 163 Chapter 7 Cloud Operations and AIOps 165 Understanding the Cloud 166 Understanding Cloud Computing 166 Cloud as a Service 172 Hybrid Cloud Solutions 175 When You Should (and Shouldn’t) Consider the Cloud 178 Deploying to the Cloud 179 Conducting a Request for Proposal 182 Additional Deployment Options 184 Managing in the Cloud 186 Cloud Management and Monitoring Solutions 189 Summary 191 Chapter 8 The Future of Healthcare AI 193 The Dynamically Changing World of AI 194 The Future of AI 198 Artificial Intelligence and Healthcare Innovation 201 Big Data, DataOps, Analytics, and Informatics 201 Telehealth (Telemedicine) 204 Telehealth Innovations 206 Telehealth AI 209 Future Innovation Merging Clinical and IT Operations 212 The Future and Beyond 214 AIOps, the Cloud, and Security 218 Summary 218 Chapter 9 The Convergence of Healthcare AI Technology 221 Overview of Convergence 222 Systems Integration 225 Convergence of AI, HIT, and HIE 228 IoT and AI 230 IoT Management 237 AIOps Management and Security 239 Summary 245 Appendix Sample AIOps Use Cases and Examples 247 Index 259
Summary: The best source for cutting-edge insights into AI in healthcare operations AI in Healthcare: How Artificial Intelligence Is Changing IT Operations and Infrastructure Services collects, organizes and provides the latest, most up-to-date research on the emerging technology of artificial intelligence as it is applied to healthcare operations. Written by a world-leading technology executive specializing in healthcare IT, this book provides concrete examples and practical advice on how to deploy artificial intelligence solutions in your healthcare environment. AI in Healthcare reveals to readers how they can take advantage of connecting real-time event correlation and response automation to minimize IT disruptions in critical healthcare IT functions.
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ABOUT THE AUTHOR
ROB SHIMONSKI is a technology executive specializing in healthcare IT for Northwell Health, one of the largest health systems in America. He is responsible for modernizing operational support with new technologies like cloud computing and storage and artificial intelligence. He currently focuses on AI Operations. He has written more than 20 books on IT topics, including penetration testing, incident handling, and cyberwarfare.

TABLE OF CONTENTS
Introduction xvii

Chapter 1 Healthcare IT and the Growing Need for AI Operations 1

A Brief History of AI and Healthcare 3

Healthcare IT Expansion and Growth 4

Data Overload 5

Digital Transformation of Healthcare 7

The Science of Healthcare Innovation 9

Artificial Intelligence in Healthcare 10

Healthcare IT Operations 14

AIOps Platform Strategy 18

Platform Types 19

Customer Experience and AIOps 20

AIOps Considerations and Goals 22

Summary 23

Chapter 2 AI Healthcare Operations (Clinical) 25

Clinical Impact of AIOps 26

Gaining a Competitive Edge with Intelligent Cloud, Data Analytics, and AI 27

Design and Innovation 29

AIOps for Healthcare Delivery 33

AIOps for Service Performance 38

Clinical AI, AIOps, and Future Platform Convergence 39

Security and Privacy 41

Why Security is Paramount in AIOps 41

HIPAA, PHI, and PII Protection 43

Summary 45

Chapter 3 AI Healthcare Operations (Operational Infrastructure) 47

Getting Started with AIOps 48

Strategy of AIOps Deployments 50

Creating a Scope 51

AIOps Platforms, Products, and Services Selection 54

AIOps Product Selection: General Topics 54

Product Review: AIOps Tool Splunk 57

Product Review: AIOps Tool ServiceNow 60

Product Review: AIOps Tool Dynatrace 64

Workflow and Event Management Design 67

Service Design with AIOps 67

Day-to-Day Operational Management 69

Summary 70

Chapter 4 Project Planning for AIOps 73

Project Planning Requirements 74

Assigning a Project Manager 75

Creating a Project Plan 77

Building the Project Plan 78

Planning a Healthcare System Project 83

Deploying AIOps 85

Deploying AIOps into the Environment 86

Configuring AIOps in the Environment 88

Summary 91

Chapter 5 Using AI for Metrics, Performance, and Reporting 93

System Performance Metrics 94

Information Technology Metrics 94

Using AI for Metrics, Performance, and Reporting 98

Strategy and Goals for AI Deployment 101

Benefits of Healthcare AIOps Service Performance Reporting 102

Developing Usable AIOps Metrics 104

Helpful Tools You Can Use 105

Gathering Usable Metrics 107

Using Dynatrace 108

Using Splunk 110

Using ServiceNow 117

Clinical and IT Metrics and Collective Actions 123

Usable Healthcare AIOps Dashboards 127

Summary 128

Chapter 6 AIOps and Automation in Healthcare Operations 131

Automation, Workflow, Process, and Intelligence Design 132

Designing the Framework for Automation 132

Understanding Automation 133

Improved User Experience 134

Designing Workflow and Process Engineering 135

Quality Control and Assurance 138

Foundational and Required Design Items 139

Configuring and Using AIOps Automation 146

Monitoring and Operating Event Management Services 148

Creating and Realizing Automation, ML, and AI 152

Automating Splunk and IT Service Analyzer 155

Splunk IT Service Intelligence 160

When Should You Use AI and ML? 162

Summary 163

Chapter 7 Cloud Operations and AIOps 165

Understanding the Cloud 166

Understanding Cloud Computing 166

Cloud as a Service 172

Hybrid Cloud Solutions 175

When You Should (and Shouldn’t) Consider the Cloud 178

Deploying to the Cloud 179

Conducting a Request for Proposal 182

Additional Deployment Options 184

Managing in the Cloud 186

Cloud Management and Monitoring Solutions 189

Summary 191

Chapter 8 The Future of Healthcare AI 193

The Dynamically Changing World of AI 194

The Future of AI 198

Artificial Intelligence and Healthcare Innovation 201

Big Data, DataOps, Analytics, and Informatics 201

Telehealth (Telemedicine) 204

Telehealth Innovations 206

Telehealth AI 209

Future Innovation Merging Clinical and IT Operations 212

The Future and Beyond 214

AIOps, the Cloud, and Security 218

Summary 218

Chapter 9 The Convergence of Healthcare AI Technology 221

Overview of Convergence 222

Systems Integration 225

Convergence of AI, HIT, and HIE 228

IoT and AI 230

IoT Management 237

AIOps Management and Security 239

Summary 245

Appendix Sample AIOps Use Cases and Examples 247

Index 259

The best source for cutting-edge insights into AI in healthcare operations

AI in Healthcare: How Artificial Intelligence Is Changing IT Operations and Infrastructure Services collects, organizes and provides the latest, most up-to-date research on the emerging technology of artificial intelligence as it is applied to healthcare operations.

Written by a world-leading technology executive specializing in healthcare IT, this book provides concrete examples and practical advice on how to deploy artificial intelligence solutions in your healthcare environment. AI in Healthcare reveals to readers how they can take advantage of connecting real-time event correlation and response automation to minimize IT disruptions in critical healthcare IT functions.

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