Australia Artificial Intelligence in Healthcare Market Report 2022 to 2030

Australia Artificial Intelligence (AI) in Healthcare Market Analysis

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Australia's Artificial Intelligence (AI) in the healthcare market is projected to grow from $0.08 Bn in 2022 to $1.78 Bn by 2030, registering a CAGR of 46.72% during the forecast period of 2022-30. The market will be driven by the increasing demand for efficient and effective healthcare delivery and the availability of healthcare data. The market is segmented by healthcare components & by healthcare applications. Some of the major players include IBM Watson Health, Google Health, HealthMatch & Clevertar.

ID: IN10AUDH003 CATEGORY: Digital Health GEOGRAPHY: Australia AUTHOR: Vidhi Upadhyay

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Australia Artificial Intelligence (AI) In Healthcare Market Executive Summary

The Australia Artificial Intelligence (AI) In Healthcare Market is projected to grow from $0.08 Bn in 2022 to $1.78 Bn by 2030, registering a CAGR of 46.72% during the forecast period of 2022-2030. Australia's world-class healthcare system and significant healthcare practice standards seek to promote unified and cost-effective availability of excellent medical, pharmaceutical, and hospital services. Australians have one of the world's highest life expectancies, ranking seventh among OECD countries - 80.7 years for males and 84.9 years for females. However, Australia is facing a challenging chronic disease burden and its consequent effect on disability and death. Asthma, cancer, diabetes, cardiovascular disease, stroke, vascular heart disease, osteoarthritis, rheumatoid arthritis, and osteoporosis are all common conditions.

In Australia, the use of AI in healthcare is increasing, with healthcare providers and organizations highly relying on AI-powered solutions to improve patient outcomes and reduce costs. Artificial intelligence (AI) is employed in a variety of areas of the healthcare system, including clinical diagnosis, drug development, and patient care. The Australian government has launched several initiatives to promote the use of AI in healthcare, including the AI in Healthcare Roadmap and the Medical Research Future Fund's Emerging Priorities and Consumer-Driven Research Initiative, which funds research into AI-powered healthcare solutions. In Australia, the use of AI in healthcare is rapidly expanding, with the government and the private sector investing in research and development and the adoption of AI-powered solutions to improve patient outcomes.

australia-artificial-intelligence-in-healthcare-market

Market Dynamics

Market Growth Drivers

One of the main growth drivers of AI in healthcare in Australia is the raising demand for efficient and effective healthcare provision. The country's aging population and rising number of chronic illnesses have put a burden on the healthcare system, necessitating the development of innovative solutions that can enhance care for patients while lowering costs. Another growth driver of AI in healthcare in Australia is the increasing availability of healthcare data. The country has a strong healthcare data infrastructure, with electronic health records and other health information systems producing vast amounts of data. Artificial intelligence (AI) tools can assist in leveraging this data to provide additional insight that can guide clinical decision-making, disease management, and population health management.

Market Restraints

There are several other barriers to AI adoption in healthcare in Australia. One of the notable restraints is the lack of standardization and interoperability of healthcare data. Despite the availability of healthcare data, it is often decentralized and fragmented, making it difficult to incorporate and analyze efficiently. Standardization and interoperability efforts are critical for enabling seamless data sharing across different systems and stakeholders, which is critical for AI's success in healthcare. The regulatory environment is another constraint. The use of AI in healthcare raises ethical, legal, and social issues, such as data privacy, transparency, accountability, and bias. The lack of clear regulatory guidelines and frameworks could really lead to uncertainty and stymie AI adoption in healthcare.

Competitive Landscape

Key Players

IBM Watson Health
Google Health
Microsoft Healthcare
Philips Healthcare
HealthMatch (AUS)
Clevertar (AUS)
Maxwell Plus (AUS)
Harrison (AUS)
Omniscient (AUS)
HealthMatch (AUS)
Provectus Algae (AUS)
Oscer’s (AUS)

Notable Insights

January 2023, Health charity Skin Check Champions, the University of South Australia, and The Hospital Research Foundation have partnered up to release a pop-up clinic that uses AI to diagnose skin cancer.

In November 2022, Caption Health, a pioneer in the use of artificial intelligence and services to improve access to heart ultrasound diagnostics, announced new regulatory approvals for its Caption AI technology platform from Health Canada's Medical Devices Directorate and Australia's Therapeutic Goods Administration.

1. Executive Summary
1.1 Digital Health Overview
1.2 Global Scenario
1.3 Country Overview
1.4 Healthcare Scenario in Country
1.5 Digital Health Policy in Country
1.6 Recent Developments in the Country

2. Market Size and Forecasting
2.1 Market Size (With Excel and Methodology)
2.2 Market Segmentation (Check all Segments in Segmentation Section)

3. Market Dynamics
3.1 Market Drivers
3.2 Market Restraints

4. Competitive Landscape
4.1 Major Market Share

4.2 Key Company Profile (Check all Companies in the Summary Section)

4.2.1 Company
4.2.1.1 Overview
4.2.1.2 Product Applications and Services
4.2.1.3 Recent Developments
4.2.1.4 Partnerships Ecosystem
4.2.1.5 Financials (Based on Availability)

5. Reimbursement Scenario
5.1 Reimbursement Regulation
5.2 Reimbursement Process for Diagnosis
5.3 Reimbursement Process for Treatment

6. Methodology and Scope

Artificial Intelligence (AI) in Healthcare Market Segmentation

Artificial Intelligence (AI) in Healthcare Market is segmented as mentioned below:

By Healthcare Component (Revenue, USD Billion):

Software Solutions
Hardware
Services

By Healthcare Applications (Revenue, USD Billion):

Robot-Assisted Suregery
Virtual Assistants
Administrative Workflow Assistants
Connected Machines
Diagnosis
Clinical Trials
Fraud Detection
Cybersecurity
Dosage Error Reduction

Methodology for Database Creation

Our database offers a comprehensive list of healthcare centers, meticulously curated to provide detailed information on a wide range of specialties and services. It includes top-tier hospitals, clinics, and diagnostic facilities across 30 countries and 24 specialties, ensuring users can find the healthcare services they need.

Additionally, we provide a comprehensive list of Key Opinion Leaders (KOLs) based on your requirements. Our curated list captures various crucial aspects of the KOLs, offering more than just general information. Whether you're looking to boost brand awareness, drive engagement, or launch a new product, our extensive list of KOLs ensures you have the right experts by your side. Covering 30 countries and 36 specialties, our database guarantees access to the best KOLs in the healthcare industry, supporting strategic decisions and enhancing your initiatives.

How Do We Get It?

Our database is created and maintained through a combination of secondary and primary research methodologies.

1. Secondary Research

With many years of experience in the healthcare field, we have our own rich proprietary data from various past projects. This historical data serves as the foundation for our database. Our continuous process of gathering data involves:

Analyzing historical proprietary data collected from multiple projects.
Regularly updating our existing data sets with new findings and trends.
Ensuring data consistency and accuracy through rigorous validation processes.

With extensive experience in the field, we have developed a proprietary GenAI-based technology that is uniquely tailored to our organization. This advanced technology enables us to scan a wide array of relevant information sources across the internet. Our data-gathering process includes:

Searching through academic conferences, published research, citations, and social media platforms
Collecting and compiling diverse data to build a comprehensive and detailed database
Continuously updating our database with new information to ensure its relevance and accuracy

2. Primary Research

To complement and validate our secondary data, we engage in primary research through local tie-ups and partnerships. This process involves:

Collaborating with local healthcare providers, hospitals, and clinics to gather real-time data.
Conducting surveys, interviews, and field studies to collect fresh data directly from the source.
Continuously refreshing our database to ensure that the information remains current and reliable.
Validating secondary data through cross-referencing with primary data to ensure accuracy and relevance.

Combining Secondary and Primary Research

By integrating both secondary and primary research methodologies, we ensure that our database is comprehensive, accurate, and up-to-date. The combined process involves:

Merging historical data from secondary research with real-time data from primary research.
Conducting thorough data validation and cleansing to remove inconsistencies and errors.
Organizing data into a structured format that is easily accessible and usable for various applications.
Continuously monitoring and updating the database to reflect the latest developments and trends in the healthcare field.

Through this meticulous process, we create a final database tailored to each region and domain within the healthcare industry. This approach ensures that our clients receive reliable and relevant data, empowering them to make informed decisions and drive innovation in their respective fields.