Newark, July 30, 2024 (GLOBE NEWSWIRE) -- The Brainy Insights estimates that the USD 1.74 billion in 2023 global clinical decision support system (CDSS) market will reach USD 3.63 billion by 2033. The next step in addressing the advancement of CDSS is integrating advanced technologies like artificial intelligence and machine learning. Data science techniques can process large amounts of clinical data and mine useful information in real time to assist clinicians in healthcare decision-making across many disciplines, such as radiology, genomics, and precision medicine. In addition, predictive analytics in developing CDSS can help identify patients at high risk of chronicities, identify disease markers, and take preventive measures against adverse events such as disease progression. Analytical strategies of different types, such as statistical patterns and machine learning algorithms, often work with data from EHRs, wearable devices, and population health databases to classify risks, implement effective care pathways, and enhance the quality of outcomes. Moreover, investment in CDSS applications allows blockchain technology to offer data security, integrity, and interconnectivity solutions. By leveraging blockchain technology in developing CDSS platforms, patient data can remain private and resistant to tampering, and data sharing among the different stakeholders in the healthcare systems can be friendly and secure. In contrast, integration of multiple and often silo healthcare systems can be possible hence leading to increased trust and interoperability in the healthcare sector.
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Key Insight of the global Clinical Decision Support System (CDSS) market
Asia Pacific is expected to witness the highest market growth over the forecast period.
Currently, this region is experiencing a boom in the expansion of health systems, brought about by economic growth, population size, and elevated levels of health expenditure. Implementation of health information systems, Health IT, plus investments in healthcare facilities and technology for the digital care of patients, establish chances for the practice of CDSS to enhance the clinical decisions and treatments for patients. Notably, there is an increasing appreciation of the significance of health information technologies in supporting the current and future supply of healthcare and improving patients’ experiences in APAC. Governments and healthcare organizations are committing significant resources to EHRs, telemedicine, and health information exchange networks, upon which to launch and develop CDSS integration and adoption. Also, the threat of cardiovascular diseases, diabetes, and cancer in Asia Pacific is increasing due to demographic shifts, growing urbanization, and changed habits of the population. This aspect can be used in managing the incipient complicated chronic diseases, enhancing disease management, and averting complications that lead to the increased demand for CDSS solutions within the specified region.
In 2023, the services segment dominated the market with the largest share of 43.18% and revenue of 0.75 billion.
The component segment is divided into hardware, software and services. In 2023, the services segment dominated the market with the largest share of 43.18% and revenue of 0.75 billion.
In 2023, the standalone CDSS segment dominated the market with the largest share of 32.16% and revenue of 0.56 billion.
The product segment is classified into integrated CPOE with CDSS, integrated EHR with CDSS, integrated CDSS with CPOE & EHR, and standalone CDSS. In 2023, the standalone CDSS segment dominated the market with the largest share of 32.16% and revenue of 0.56 billion.
In 2023, the on-premise segment dominated the market with the largest share of 43.10% and revenue of 0.75 billion.
The delivery mode segment includes web-based systems, cloud-based systems and on-premise systems. In 2023, the on-premise segment dominated the market with the largest share of 43.10% and revenue of 0.75 billion.
In 2023, the drug allergy alerts segment dominated the market with the largest share of 26.21% and revenue of 0.46 billion.
The application segment is divided into clinical reminders, clinical guidelines, drug allergy alerts, drug dosing support and others. In 2023, the drug allergy alerts segment dominated the market with the largest share of 26.21% and revenue of 0.46 billion.
Advancement in market
In August 2023: As a CDS application that can be tailored for a specific person, CardioVisio for Atrial Fibrillation was recently launched by GE Healthcare for precision care. This approach can be described as cutting-edge as it allows healthcare givers to provide insight-driven care to patients suffering from atrial fibrillation.
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Market Dynamics
Driver: Growing awareness of patient safety.
Protecting patients from harm is one of the most important goals across spheres of practice in healthcare in the global community. This is where the Clinical Decision Support System plays a major role. The elements of CDSS include notification, decision support and recommendations, and recommendations based on research findings. These systems consider individual patient data and medical evidence and deliver timely patient-specific recommendations for clinicians. Further, alerts in real-time help the healthcare professionals involved in dispensing the medicines to inform them of certain risks or variations in prescribed dosages ahead of time. Clinical guidelines offered by CDSS help practitioners maintain the quality and standard measures necessary for a good delivery. Also, evidence-based recommendations are instrumental in enabling those responsible for treating ill patients to make decisions related to healthcare consistent with current knowledge and practice. As an application of recent developments in health-doctor knowledge, CDSS helps to improve the course of safe and appropriate therapies and to reduce the severity and frequency of unfavourable cases.
Restraint: Cost and return on investment (ROI) concerns.
The expense involved in CDSS adoption at a basic level would be buying licenses of the software platforms or applications that would, in turn, support decision-support functionalities. These licenses may require initial payments and yearly charges based on the CDSS vendors who adopt this option for billing customers. Furthermore, investment in hardware equipment like storage devices, servers, and network components in healthcare organizations is needed to support CDSS deployment and execution. Other implementation costs related to training costs are another area of expenditure that constitutes considerable costs towards implementing CDSS. Clinicians need training on how to use CDSS, which involves teaching them the various features of CDSSs, how to interpret the outputs that the CDSS provides, and how best to incorporate the CDSS into their daily work routines. Five additional costs may include trainer fees, training aids, resources, and time used to facilitate training programs, educational workshops or other training services. However, there are still challenges that healthcare organizations face when it comes to generating ROI in CDSS due to its possession of the potential to enhance HC decision-making and, consequently, patient care. The effectiveness of CDSS interventions in terms of clinical outcomes, costs, and time has been established. However, the extent of the benefits and how they can be achieved may vary depending on the setting or a given scenario. Failing to provide a substantive argument that points to such improvement, CDSS may lack the support needed to garner vested healthcare decision-makers' support in funding CDSS implementation initiatives.
Opportunity: Population health management.
Clinical Decision Support System (CDSS) can provide tangible help for defined population health management efforts relying on big clinical data, define at-risk populations, and provide improvements focused on the overall health status and cost decrease. Large data sets from EHRs, claim databases, health registries and others could be collected and analyzed to define the clinical signal within the population's health, which can be linked to risky behaviours, conditions and outcomes. The technological tools include employing advanced analytics and machine learning to sort the demography, disease, and socio-economic details to categorize the population, estimate future health outcomes and target the most suitable interventions. Additionally, CDSS helps address timely issues and implement prioritisations, delivering treatment and care to high-risk populations. Decision support algorithms can then produce specific and individualized care, subsequent screenings and potential treatment due to the algorithm's integration of evidence-based and best practice protocols and patient-specific information. It can also engage patients, construct communication tactics, and schedule care management tasks to help early intervention and meaningful follow-up care. Also, CDSS facilitated population health management aimed at disease prevention interventions to decrease the number and impact of chronic diseases and enhance the healthcare outcomes of targeted populations. CDSS can recognize impatient who require lectures for consistent preventional examinations, vaccinations or lifestyle changes according to their age, gender, prominent risks and rigid clinical norms, helping to provide effective preventional and promotion interventions. In addition, CDSS enhances the management of chronic diseases, as it can help identify disease patterns early enough or even prevent them and arrange treatment care for patients with chronic diseases. A clinical decision support system brings information about disease state, medication use, and its effectiveness in patient outcomes. It informs caregivers about compliance or non-compliance with established care pathways and suggests changes to plans or interventions when indicated. Furthermore, the population health interventions recommended by CDSS enhance the use of healthcare resources in various health sectors by defining resource efficiency, resource-saving, and quality enhancement opportunities. CDSS analytics can determine a number of aspects of healthcare usage, differences in care, or resource management issues that healthcare organizations can employ in solutions to improve resource allocation and the care delivery processes and to decrease the instances of unnecessary healthcare services received.
Challenge: User interface design and usability.
The research has found that two major aspects, namely UI design and usability, are crucial aspects that can determine the level of acceptance and, thus, adoption of CDSS among healthcare professionals. The user interface should improve usability and allow the workflow to fit into the application's structure. An extended best practice also benefits the user; conversely, a bad evidence-based interface design adversely affects usability, results in higher cognitive load, and hinders clinicians from implementing CDSS in their work. Standard CDSS with low-quality interfaces may have serious problems related to the information space of an application, including such common obstacles as overfilled screens full of various widgets, tables and buttons organized in an unstructured way, or switch panels that do not follow intuitive logic. Holders of clinical practice may require assistance in identifying the information to use, comprehending certain outputs generated by the CDSS and performing specific tasks within the interface. This aspect contributes to frustration and diminished docketed clinical assessment and decision-making productivity.
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Some of the major players operating in the global Clinical Decision Support System (CDSS) market are:
• Allscripts Healthcare, LLC
• Athenahealth
• Agfa-Gevaert Group
• Cerner Corporation
• Epic Systems Corporation
• Elsevier B.V.
• IBM Corporation
• Koninklijke Philips N.V
• McKesson Corporation
• MEDITECH
• NextGen Healthcare Inc.
• Oracle (Cerner Corporation)
• Siemens Healthineers GmbH
• Wolters Kluwer N.V.
• Zynx Health
Key Segments cover in the market:
By Component
• Hardware
• Software
• Services
By Product
• Integrated CPOE with CDSS
• Integrated EHR with CDSS
• Integrated CDSS with CPOE & EHR
• Standalone CDSS
By Delivery Mode
• Web-based Systems
• Cloud-based Systems
• On-premise Systems
By Application
• Clinical Reminders
• Clinical Guidelines
• Drug Allergy Alerts
• Drug Dosing Support
• Others
By Region
• North America (U.S., Canada, Mexico)
• Europe (Germany, France, the UK, Italy, Spain, Rest of Europe)
• Asia-Pacific (China, Japan, India, Rest of APAC)
• South America (Brazil and the Rest of South America)
• The Middle East and Africa (UAE, South Africa, Rest of MEA)
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About the report:
The market is analyzed based on value (USD Billion). All the segments have been analyzed worldwide, regional, and country basis. The study includes the analysis of more than 30 countries for each part. The report analyses driving factors, opportunities, restraints, and challenges to gain critical market insight. The study includes Porter's five forces model, attractiveness analysis, Product analysis, supply, and demand analysis, competitor position grid analysis, distribution, and marketing channels analysis.
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