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The Clinical Decision Support Systems Market is segmented By Model, By Mode of Delivery (Web-Based, Cloud-Based, and On-premise), By Component, By Product, By Application, and Geography.
Study Period:
2017-2025
Base Year:
2019
Fastest Growing Market:
Asia Pacific
Largest Market:
North America
CAGR:
12.5 %
The Clinical Decision Support Systems Market is expected to register a CAGR of 12.5% during the forecast period. The increasing need for reducing human errors, rising demand for reducing healthcare expenditure, need for improvement in the quality of care, surging chronic disease population, and high adoption rates in the emerging economies are the major factors that are likely to boost the growth of the clinical decision support systems (CDSS) market.
Moreover, according to the Organization for Economic Co-operation and Development (OECD) survey report, in 2018 average per capita health expenditure in the United States was about USD 10,586.
However, lack of trust in the systems, as CDSS are in the initial stages of development, lack of skilled labour, and suggestions from CDSS for unnecessary diagnostic testing hinders the market growth.
As per the scope of the report, clinical decision support systems refer to healthcare IT systems, designed specifically to assist clinical decision support for healthcare professionals and physicians. They include various tools that help enhance decision-making in the clinical workflow. Additionally, they provide computerized alerts and reminders to care providers and patients, clinical guidelines, focused patient data reports and summaries, diagnostic support, and documentation templates, among other tools. The clinical decision support systems market is segmented by model, mode of delivery, component, product, application, and geography.
By Model | |
Knowledge-based CDSS | |
Non-knowledge CDSS |
By Mode of Delivery | |
Cloud-based | |
On-premise |
By Component | |
Hardware | |
Software | |
Services |
By Product | |
Integrated System | |
Stand-alone System | |
Standard-based | |
Service Model-based | |
Other Products |
By Application | |
Medical Diagnosis | |
Alerts and Reminders | |
Prescription Decision Support | |
Information Retrieval | |
Image Recognition and Interpretation | |
Therapy Critiquing and Planning | |
Other Applications |
Geography | ||||||||
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The increasing adoption of cloud computing is the major driver for the expansion of the cloud-based segment of the market. According to a survey by RightScale (2016), nearly 95% of organizations run cloud-based applications. The hardware of electronic medical record (EMR) systems offered by different vendors are different. Hence, developing a standard CDSS software, which can run on multiple EMR systems, is a major challenge. Moreover, cloud-based applications are not dependent on web browsers, which makes them scalable and inherently safer than web-based applications.
Furthermore, according to the Organization for Economic Co-operation and Development (OECD) survey report, in 2018 average per capita health expenditure in Switerzland was about USD 7,317 in Norway USD 6,187 and Australia USD 5,005 respectively. Due to high healthcare expenditure across the world, the rising demand to reduce healthcare expenditure which shows a positive impact on the market.
In a cloud-based clinical decision support system, processing units are hosted on remote servers, which can be located in multiple data centers across the world, making them less vulnerable to cyberattacks. Besides, the increasing availability of cloud technology, coupled with its flexibility and scalability, is expected to drive the usage of cloud-based CDSS, over the forecast period.
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Factors, such as the rise in technological advancement in the CDSS market, high awareness among patients, and increasing investments in HCIT solutions in North America, are expected to boost the growth of the CDSS market over the forecast period.
In 2016, the Agency for Healthcare Research and Quality (AHRQ) launched a new initiative to disseminate and implement the findings of patient-centred outcomes research (PCOR) through clinical decision support (CDS). The two major goals of the initiative were to accelerate the movement of evidence into practice through CDS and to make CDS more shareable, standards-based, and publicly available. Such research efforts help engage relevant stakeholders, such as patients, clinicians, provider organizations, guideline and quality measurement developers, and information technology professionals, to improve decision making in healthcare with the help of CDSS. Such initiatives are expected to propel the growth of the CDSS market, over the forecast period, in North America.
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The Clinical Decision Support Systems Market is consolidated competitive. The market players are continuously focusing on acquisitions, mergers, provision of customized solutions, and expansion in the untapped commercial markets. Moreover, companies are also investing huge amounts on developing new products and platforms, with enhanced and improved features, as a part of commercialization strategy.
For instance, in 2018, the US Food and Drug Administration (FDA) announced marketing clearance for Viz.AI's Contact application, the first artificial intelligence-based clinical decision support (CDS) solution, in the United States. Viz.AI Contact is designed to analyze computed tomography (CT) results.
1. INTRODUCTION
1.1 Study Deliverables
1.2 Study Assumptions
1.3 Scope of the Study
2. RESEARCH METHODOLOGY
3. EXECUTIVE SUMMARY
4. MARKET DYNAMICS
4.1 Market Overview
4.2 Market Drivers
4.2.1 Need for Reducing Human Errors
4.2.2 Rising Demand to Reduce Healthcare Expenditure
4.2.3 Need for Improvement in Quality of Care
4.3 Market Restraints
4.3.1 Lack of Trust in the System due to CDSS Being in the Initial Stages of Development
4.3.2 Lack of Skilled Professionals
4.4 Porter's Five Forces Analysis
4.4.1 Threat of New Entrants
4.4.2 Bargaining Power of Buyers/Consumers
4.4.3 Bargaining Power of Suppliers
4.4.4 Threat of Substitute Products
4.4.5 Intensity of Competitive Rivalry
5. MARKET SEGMENTATION
5.1 By Model
5.1.1 Knowledge-based CDSS
5.1.2 Non-knowledge CDSS
5.2 By Mode of Delivery
5.2.1 Cloud-based
5.2.2 On-premise
5.3 By Component
5.3.1 Hardware
5.3.2 Software
5.3.3 Services
5.4 By Product
5.4.1 Integrated System
5.4.2 Stand-alone System
5.4.3 Standard-based
5.4.4 Service Model-based
5.4.5 Other Products
5.5 By Application
5.5.1 Medical Diagnosis
5.5.2 Alerts and Reminders
5.5.3 Prescription Decision Support
5.5.4 Information Retrieval
5.5.5 Image Recognition and Interpretation
5.5.6 Therapy Critiquing and Planning
5.5.7 Other Applications
5.6 Geography
5.6.1 North America
5.6.1.1 United States
5.6.1.2 Canada
5.6.1.3 Mexico
5.6.2 Europe
5.6.2.1 Germany
5.6.2.2 United Kingdom
5.6.2.3 France
5.6.2.4 Italy
5.6.2.5 Spain
5.6.2.6 Rest of Europe
5.6.3 Asia-Pacific
5.6.3.1 China
5.6.3.2 Japan
5.6.3.3 India
5.6.3.4 Australia
5.6.3.5 South Korea
5.6.3.6 Rest of Asia-Pacific
5.6.4 Middle-East & Africa
5.6.4.1 GCC
5.6.4.2 South Africa
5.6.4.3 Rest of Middle-East & Africa
5.6.5 South America
5.6.5.1 Brazil
5.6.5.2 Argentina
5.6.5.3 Rest of South America
6. COMPETITIVE LANDSCAPE
6.1 Company Profiles
6.1.1 Cerner Corporation
6.1.2 EPIC
6.1.3 IBM
6.1.4 Change Healthcare
6.1.5 Meditech
6.1.6 Koninklijke Philips NV
6.1.7 Siemens Healthcare
7. MARKET OPPORTUNITIES AND FUTURE TRENDS
**Competitive Landscape Covers - Business Overview, Financials, Products and Strategies, and Recent Developments