June 27, 2024
PACS and RIS Market

Picture Archiving and Communication Systems (PACS) and Radiology Information Systems (RIS) Market propelled by growing demand for advanced healthcare IT systems

PACS and RIS are information systems that are used by healthcare providers to manage medical imaging and radiology reports and workflow. PACS is used to store and retrieve medical images securely and digitally, while RIS manages radiology workflow and billing tasks. These systems have become increasingly necessary in hospitals and imaging centers to improve diagnostic efficiency and streamline workflow. With rising healthcare costs and workloads, there is a growing demand for advanced IT systems that can facilitate faster access to patient data and optimize resources.

The global PACS and RIS Market is estimated to be valued at US$ 3657 Mn in 2023 and is expected to exhibit a CAGR of 6.7% over the forecast period 2023 to 2030, as highlighted in a new report published by Coherent Market Insights.

Market key trends:
The growing demand for PACS and RIS systems is primarily being propelled by the rising integration of artificial intelligence (AI) and cloud technology. AI has the potential to revolutionize medical imaging by enabling advanced image analysis, automated report generation, and diagnostic assistance. Many leading system developers are now integrating AI into their solutions to provide more accurate and timely diagnosis. Cloud deployment of PACS and RIS is also gaining traction as it allows healthcare providers to access radiology data from any location and share images and reports within integrated healthcare networks seamlessly. The cloud-based model eliminates hardware and maintenance costs and ensures reliable storage and streamlined operations. Rising investments by major players in AI- and cloud-integrated systems are expected to significantly drive the growth of the global PACS and RIS market during the forecast period.

SWOT Analysis
Strength: PACS and RIS provide centralized access to radiological images and reports which improves workflow efficiency. It also reduces operation costs by eliminating the need for costly physical storage and delivery of reports.
Weakness: High upfront investment costs associated with PACS and RIS implementation and maintenance can be prohibitive for small healthcare facilities. Interoperability issues between different vendor products can hamper seamless data sharing.
Opportunity: Growing geriatric population and rising incidence of chronic diseases will increase healthcare workload and drive demand for PACS and RIS solutions to manage radiology departments efficiently. Integration of artificial intelligence and cloud technologies offers new opportunities.
Threats: Cybersecurity threats from data breaches and hacking attempts pose a major challenge. Switching costs and vendor lock-ins can slow adoption of new and innovative products.

Key Takeaways
The Global PACS And RIS Market Size is expected to witness high growth over the forecast period of 2023 to 2030. The global PACS and RIS Market is estimated to be valued at US$ 3657 Mn in 2023 and is expected to exhibit a CAGR of 6.7% over the forecast period 2023 to 2030.

North America currently dominates the global market due to rapid technological advancements and high healthcare infrastructure in countries like the US and Canada. Asia Pacific is expected to be the fastest growing market with increasing healthcare investments in China, India and other developing countries.

Key players operating in the PACS and RIS market are Daihen Corporation, Yaskawa Motoman Robotics, Denso Corporation, Universal Robots, Epson America, Inc., Panasonic Corporation, Epson America, Inc., Nachi Robotic Systems, Inc., FANUC Ltd., Mitsubishi Electric Corporation, Kawasaki Heavy Industries Ltd., and KUKA Robotics Corporation. Growth strategies adopted by these key players include new product launches, partnerships and mergers & acquisitions to strengthen their product portfolio and geographical presence.

*Note:
1. Source: Coherent Market Insights, Public sources, Desk research
2. We have leveraged AI tools to mine information and compile it