Austria Artificial Intelligence (AI) in Diagnostics Market Analysis

Austria Artificial Intelligence (AI) in Diagnostics Market Analysis


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Austria's Artificial Intelligence (AI) in the diagnostics market is projected to grow from $4.0 Mn in 2022 to $xx Mn by 2030, registering a CAGR of xx% during the forecast period of 2022 - 2030. The market will be driven by the aging population with the associated growing ailment burden and the strong-paced technical advancement. The market is segmented by component & by diagnosis. Some of the major players include IBM Watson Health, Siemens Healthineers, and Contextflow.

ID: IN10ATDH002 CATEGORY: Digital Health GEOGRAPHY: Austria AUTHOR: Vidhi Upadhyay

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Austria Artificial Intelligence (AI) in Diagnostics Market Executive Summary

Austria's Artificial Intelligence (AI) in the diagnostics market is projected to grow from $4.0 Mn in 2022 to $xx Mn by 2030, registering a CAGR of xx% during the forecast period of 2022 - 2030. Austria's healthcare system is essentially universal, and service accessibility is typically strong, with full financial protection for deprived areas provided through several exemptions from expense regulations. The Austrian healthcare system is intricately regulated. Austria's healthcare system consists of 271 hospitals and clinics with around 64,800 accessible beds. General hospitals provide for around 64% of hospital beds, specialty clinics and rehabilitation facilities account for 26.6%, and sanatoriums or long-term care institutions account for 7%.

Artificial intelligence (AI) has the potential to transform the area of medical diagnostics in Austria by enhancing diagnosis accuracy, effectiveness, and speed. AI systems can scan massive volumes of medical data, such as patient histories, laboratory results, and medical imaging, to detect trends and make predictions. AI examines medical pictures like X-rays, CT scans, and MRIs to discover and diagnose diseases including cancer, heart disease, and neurological problems. Many hospitals and research organizations in Austria, including the Medical University of Vienna, the Vienna General Hospital, and the Center for Medical Statistics, Informatics, and Intelligent Systems at the Medical University of Vienna are investigating the application of AI in medical imaging.

austria artificial intelligence in diagnostics market analysis

Market Dynamics

Market Growth Drivers

The aging population and associated growing ailment burden, universal health insurance, the strong pace of technical advancement, and bad lifestyle choices, especially high smoking, and alcohol use rates, are the four key drivers in Austria's medical device industry. Moreover, The Institute of Bioinformatics at Johannes Kepler University Linz is working on AI algorithms to forecast the risk of different diseases like cancer, cardiovascular disease, and diabetes. AI is being utilized by the Institute of Pathology at the Medical University of Graz to examine tissue samples of breast cancer patients in order to uncover biomarkers that may be used to predict therapy response. Some hospitals and healthcare institutions in Austria, notably the Vienna General Hospital and the Austrian Health Institute, are employing AI to evaluate electronic health information. Such advances in Austria are expected to drive market expansion in the future.

Market Restraints

The European Union (EU) Medical Device Regulation (2017), which set new, considerably tighter registration, licensing, and auditing standards for all medical devices, is the most major market limitation. Obtaining reimbursement may be a big hurdle for firms developing novel medicines. There is a lack of centralized, standardized data-sharing infrastructure in Austria, which might make accessing and analyzing medical data challenging. There are other technological constraints that might make developing and deploying AI diagnostic tools challenging, such as the requirement for strong computer infrastructure and specific knowledge in machine learning and data processing. There may be doubts about how AI diagnostic tools access and use patient data, which can make gaining regulatory clearance and public confidence challenging.

Competitive Landscape

Key Players

  • GE Healthcare
  • IBM Watson Health
  • Siemens Healthineers
  • Philips Healthcare
  • Google Health
  • AliveCor, Inc.
  • Riverain Technologies
  • Contextflow (AUT)
  • Medicus AI (AUT)
  • ImageBiopsy Lab (AUT)

Notable Deals

February 2023, GE HealthCare to Acquire Caption Health The acquisition adds AI-enabled image guiding to the ultrasound device portfolios of GE HealthCare's $3 billion Ultrasound division.

Healthcare Policies and Regulatory Landscape

The Federal Ministry of Health is in charge of developing and implementing healthcare legislation in Austria, including those governing the use of AI in medical diagnosis. The ministry collaborates with other government agencies and professional groups to ensure that AI diagnostic tools fulfill high safety and effectiveness criteria. The Austrian Agency for Health and Food Safety (AGES) is a government body in Austria that is in charge of ensuring the safety and quality of medical equipment and diagnostic instruments.

Reimbursement Scenario

The statutory national health insurance policy in Austria covers 99% of the population and is based on 21 separate statutory insurance carriers, each with some rather varying price and coverage structures. In general, insurance carriers cover treatment considered essential and effective, with a moderate to considerable co-payment for dental and eye care, as well as health aids. Diagnostic equipment developed for use in a hospital environment must be formally recognized as a reimbursable treatment under the Austrian LKF (Austria's disease-related group points system). The reimbursement decision is based on the findings of a panel convened by the Ministry of Health, which includes physicians, insurance companies, and public officials.

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 Diagnostics Market Segmentation

  • By Component Outlook Type (Revenue, USD Billion):
    • Software
    • Hardware
    • Services
  • By Diagnosis Outlook Type (Revenue, USD Billion):
    • Cardiology
    • Oncology
    • Pathology 
    • Radiology
    • Chest and Lung
    • Neurology
    • Others

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.

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Last updated on: 24 February 2023
Updated by: Dhruv Joshi

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