In AI in Healthcare: How Artificial Intelligence Is Changing IT Operations and Infrstructure Services, author Rob Shimonski delves into the emerging field of AI and Operations (AIOps). He explores what can be through the connection of real-time event correlation and automation of responses to help minimize disruptions in critical IT functions in healthcare organizations. He demonstrates how other benefits can be found in the way the customer (both patient and clinician) experiences outcomes. Book topics include:

• Healthcare IT
• AI Clinical Operations
• AI Operational Infrastucture
• Project Planning
• Metrics, Reporting, and Service Performance
• AIOps in Automation
• AIOps Cloud Operations

Today’s systems, networks, data, and critical infrastructure are all dependent on becoming more efficient and “self-aware,” but also “self-healing.” Artificial Intelligence in operational models has become the de facto standard of how services are designed and deployed. This is especially true in highly critical services such as those delivered by healthcare where lost time, mistakes and administrative red tape impact the patient experience negatively. With more push towards “zero” downtime and less impact on 24x7x365 systems, having the “intelligence” to continuously deliver accurate results is one of the most exciting technological developments in our time. This book will help you  learn about AI and its importance n healthcare, and provide practical examples and advice on how to actually deploy it in your environment to achieve positive outcomes.

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.

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