
Artificial Intelligence (AI) in Clinical Practice - Patient Perspective - Thematic Intelligence
Description
Artificial Intelligence (AI) in Clinical Practice - Patient Perspective - Thematic Intelligence
Summary
In this AI in Clinical Practice: Patient Perspective – 2023 report, GlobalData examines the patient perspective on the use of AI in healthcare settings in the US, France, Germany, Italy, Spain, the UK, Japan, Brazil, Canada, India, and Mexico.
Key takeaways from this report include -
- Younger patients were more confident that they understand artificial intelligence (AI) compared to older generations.
- Lack of in-person interaction was the number one patient concern associated with physicians using AI in clinical practice.
- Faster healthcare delivery and mitigation of healthcare staff shortages were selected as the main benefits associated with AI use in clinical practice.
- Patients familiar with AI were more convinced that AI could improve patients’ care.
- Most patients felt more comfortable with physicians using AI to automate administrative tasks compared to directing patient care.
- Patents who were familiar with AI were more comfortable visiting healthcare practices that were using this technology.
- Physicians who had previous AI experience were more positive about patients being comfortable with the use of AI to support clinical decisions.
- AI implementation can improve patient monitoring technologies that are already used in healthcare.
Scope
This report combines information obtained from secondary sources and primary research with patients suffering from conditions such as heart diseases, diabetes, multiple sclerosis (MS), cancer, chronic respiratory conditions, rheumatoid arthritis (RA), psoriasis, and inflammatory bowel disease (IBD). The patient survey was fielded between July–August 2023. The interviews and surveys with physicians and KOLs were conducted during March–June 2023.
Study objectives
- Assess patients’ comfort level with physicians’ using AI.
- Capture patients’ opinions on AI use in clinical setting.
- Identify the processes within clinical practice that AI can improve the most.
- Explore the perceived advantages and disadvantages of AI.
- Compare patients’ and physicians’ opinions on the use of AI.
- This report combines information obtained from secondary sources and primary research with patients, healthcare industry professionals, key opinion leaders (KOLs), and physicians from different therapy areas.
- It assesses the current use of AI in clinical practice.
- Captures physicians’ and patients’ opinions on the use of AI.
- Identifies the processes within clinical practice that AI can improve the most – according to both patients and physicians.
- Explores patients comfort level with visiting healthcare practices that use AI.
- Includes AI case studies.
Table of Contents
52 Pages
- 1 Executive Summary
- 1.1 Executive Summary
- 2 Study Design
- 2.1 Objectives and Design
- 2.2 Respondent Mix
- 2.3 Respondent Profiles
- 3 Patient Perception of AI
- 3.1 Patient Familiarity Level with AI
- 3.2 Patient Concerns Associated with HCPs Using AI – by Geography
- 3.3 Perceived Benefits of AI – by Geography
- 3.4 Patients’ Agreement Level with AI Improving Care
- 3.5 Patients’ Agreement Level with AI Improving Care – by Geography
- 4 Patient Comfort with AI
- 4.1 Patient Comfort Level with Physicians Using AI
- 4.2 Patient Comfort Level with Physicians Using AI – by Geography
- 4.3 Patient Comfort with Visiting Practice that Uses AI
- 4.4 Patient Comfort with Visiting Practice that Uses AI – by Condition
- 5 Comfort with AI: Patients vs. Physicians
- 5.1 Physician Comfort Level with Using AI
- 5.2 Physician and Patients Comfort Level with Using AI
- 5.3 Physician Comfort Level with Using AI
- 6 Digital Health, Telemedicine, and AI
- 6.1 Patient Use of Digital and Connected Devices
- 6.2 Patient Use of Telemedicine
- 7 Use Cases
- 7.1 AI Tasked with a Challenge to Identify Breast Cancer
- 7.2 AI Helps to Organize Electronic Healthcare Records
- 7.3 AI’s Bid on Tackling and Easing NHS Pressure
- 7.4 Revolutionizing Public Health Management with Big Data and AI
- 7.5 AI Proves to Be Helpful in Diabetic Care
- 8 Summary of Key Findings
- 8.1 Key Findings
- 9 Appendix
- 9.1 Bibliography
- 9.2 Abbreviations
- 9.3 Related Reports
- 10 About the Authors
- 10.1 About the Authors
- 11 Our Thematic Research Methodology
- 11.1 Our Thematic Research Methodology
- 12 Contact Us
- 12.1 About GlobalData
- 12.2 A Connected Platform for a Dynamic World
- 12.3 Contact Us
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