Description

The global clinical decision support systems market size is estimated to grow from USD 2.0 billion in 2021 to USD 3.7 billion by 2030, at a CAGR of 6.7% from 2022 to 2030. CDS provides health care professionals and patients with the knowledge and person-specific information, intelligently filtered or presented at the appropriate times, to enhance health and healthcare. The core CDSS ecosystem comprises raw data providers, technology providers, software/CDSS developers, and end-users. The raw data is obtained from hospital operations data, patient information, medical images, and lab data. The latest technology is provided by tech giants or startups dealing with specific niches such as big data, artificial intelligence, and cloud service. The software/CDSS developers provide the CDSS platform or the system used by physicians, lab professionals, and nurses, among others.

The CDSS technology emerged due to the urgent need to check deaths due to medical errors that can be prevented across the globe. Preventable deaths due to medical errors claim approximately 400,000 lives every year. The cost associated with medical errors is approximately $1 trillion every year, which poses a substantial financial burden on the healthcare system. The CDSS technology emerged due to the urgent need to check deaths due to medical errors that can be prevented across the globe. Preventable deaths due to medical errors claim approximately 400,000 lives every year, and the cost associated with medical errors is approximately $1 trillion every year, which poses a substantial financial burden on the healthcare system.

COVID-19 Impact on the Global Clinical Decision Support Systems Market

Immediately after the outbreak of COVID-19, the focus of healthcare systems across the globe switched to managing the crisis caused by the pandemic. This led to hospital budgets shrinking, and consequently, the growth of the CDSS market seemed grim. However, various instances across healthcare applications where CDSS solutions have played a major role in the COVID-19 pandemic. Established players, emerging startups, hospitals, and research facilities have used CDSS solutions to solve the challenges posed by the COVID-19 pandemic.

The application of CDSS in healthcare in the pre-COVID-19 period has been driven by the growing need to reduce medical errors and improve patient outcomes. Also, rapid technology innovation, especially technologies such as AI and cloud computing, has been extremely influential in developing intelligent software solutions and can assist healthcare providers throughout the clinical workflow. The COVID-19 pandemic has caused a massive disturbance in North America, with the U.S. being the most affected country globally in terms of the number of COVID-19 cases as of December 2020. The adoption of CDSS has been promoted in the region to check the pandemic.

Global Clinical Decision Support Systems Market Dynamics

Drivers: Technological Advancements in the Field of Information Technology

Technologies such as EHR systems, business intelligence tools, and big data analytics are constantly evolving and aiding healthcare providers in the better management and analysis of patient data for making effective clinical decisions. According to the office of the National Coordinator for Health Information Technology, as of 2017, nearly 9 in 10 (86%) of office-based physicians had adopted some form of an electronic health record (EHR), and nearly 4 in 5 (80%) had adopted a certified EHR.

AI is another technological advancement playing a big part in transforming clinical decision support systems. There are ample complexities in clinical decision-making either at the level of diagnosis or at the level of designing a treatment regimen and ultimately increase the risk of disease-associated mortality.

Restraints: The Reluctance of Clinicians to use CDSS Systems due to Computer Illiteracy

Due to the lack of computer illiteracy, physicians in emerging countries often perceive the usage of CDSS as a threat to their professional autonomy. It is a concern amongst physicians that CDSS may erode the natural flow of their work routines and may not be in sync with their practice patterns. It is also a belief among some physicians that using CDSS, their years of medical experience may get decrypted distributed among peers and other non-professionals. However, this can be overcome by maximizing the engagement and participation of a physician in the decision-making process.

Opportunities: Integration of CDSS with Blockchain

Blockchain can play a critical role in eliminating the interoperability challenge in healthcare and enhancing data security for health information exchanges (HIEs). Blockchain could be employed as a reservoir of a growing volume of patient data from different sources and also be used to exchange information securely. For instance, each time a patient visits a doctor, the doctor would update the patients’ health data on a blockchain-enabled HIE, which could be accessed later by both the patient and the doctor through a private key. Patients would limit data access on approved blockchains and share only the relevant parts of their medical records with their doctors or other clinics. The distributed and immutable nature of blockchain would reduce the likelihood of security breaches and facilitate the secure exchange of information. There have been notable initiatives taken for the integration of blockchain in healthcare. For instance, in October 2017, IBM Watson Health (a subsidiary of International Business Machines Corporation) partnered with the Center for Disease Control and Prevention (CDC) to explore new healthcare applications for blockchain.

Scope of the Clinical Decision Support Systems

The study categorizes the clinical decision support systems market based on product type, delivery mode, type, model, user interactivity, end-users, and application at the regional and global levels.

By Product Type Outlook (Revenue, USD Million, 2017-2030)

• Integrated
• Standalone

By Delivery Mode Outlook (Revenue, USD Million, 2017-2030)

• On-Premise CDSS
• Cloud-Based CDSS

By Type Outlook (Revenue, USD Million, 2017-2030)

• Conventional
• Advanced

By Model Outlook (Sales, USD Million, 2017-2030)

• Knowledge-Based
• Non-Knowledge Based

By Users Interactivity Outlook (Revenue, USD Million, 2017-2030)

• Active
• Passive

By End-Users Outlook (Revenue, USD Million, 2017-2030)

• Hospitals and Clinics
• ASCs
• Others

By Application Outlook (Revenue, USD Million, 2017-2030)

• Preventive Care
• Diagnostics
• Follow-Up Management
• Others
  • Planning
  • Implementation

By Region Outlook (Revenue, USD Million, 2017-2030)

• North America (US, Canada, Mexico)
• South America (Brazil, Argentina, Colombia, Peru, Rest of Latin America)
• Europe (Germany, Italy, France, UK, Spain, Poland, Russia, Slovenia, Slovakia, Hungary, Czech Republic, Belgium, the Netherlands, Norway, Sweden, Denmark, Rest of Europe)
• Asia Pacific (China, Japan, India, South Korea, Indonesia, Malaysia, Thailand, Vietnam, Myanmar, Cambodia, the Philippines, Singapore, Australia & New Zealand, Rest of Asia Pacific)
• The Middle East & Africa (Saudi Arabia, UAE, South Africa, Northern Africa, Rest of MEA)

The integrated segment is projected to account for the largest market share, by product type

The global clinical decision support systems market has been segmented into two categories based on product type: integrated and standalone. In 2021, the integrated segment accounted for the largest market share in the global clinical decision support systems market. Integrated CDSS can be integrated with both the EHR and the medical devices in a healthcare setting. Healthcare delivery is becoming more interconnected and personalized by the day. After passing through large knowledge bases, most decisions are taken, and integrated CDSS makes the process more streamlined. As integrated CDSS can be incorporated into the EHR and medical devices in a professional setting, they are expected to have a maximum adoption rate due to quicker response time and smooth workflow.

Asia Pacific accounts for the highest CAGR during the forecast period

Based on the regions, the global clinical decision support systems market has been segmented across North America, Asia-Pacific, Europe, South America, and the Middle East & Africa. Globally, Asia Pacific is estimated to hold the highest CAGR of 7.0% in the global clinical decision support systems market during the forecast period. In many emerging countries in the Asia-Pacific region, the healthcare sector is getting more attention than before. Countries such as India and China have several digital health initiatives which have witnessed accelerated implementation during the COVID-19 pandemic. Hospitals and clinics are expected to account for the largest share of 2021-2030. Large hospital chains in the region focus on providing quality patient-specific care, and CDSS is witnessing increased adoption rates.

The CDSS market in China is at a nascent stage. The adoption rate is expected to increase during the next three-four years as AI becomes more integrated with the deployed healthcare systems. China is among the top countries with numerous R&D projects in AI in healthcare. The CDSS market in China is at a nascent stage. The adoption rate is expected to increase during the next three-four years as AI becomes more integrated with the deployed healthcare systems. China is among the top countries with numerous R&D projects in the field of AI in healthcare.

Key Market Players

The clinical decision support systems market is mildly concentrated in nature with few numbers of global players operating in the market, such as Allscripts Healthcare Solutions, Inc., Cerner Corporation, Change Healthcare, General Electric Company, International Business Machines Corporation, McKesson Corporation, RELX Group, Wolters Kluwer N.V., Epic Systems Corporation, Hearst Corporation, Inferscience, Inc., Medical Information Technology, Inc. (MEDITECH), Oncology Analytics, Inc., Persivia Inc., and VisualDx.

Recent Developments

• In March 2020, IBM Watson Health (a subsidiary of International Business Machines Corporation) and EBSCO Information Services collaborated to offer an integrated clinical decision support solution. The solution involves integrating cloud-based tools natural language processing with disease and drug content to make the clinical decision-making process more efficient.
• In December 2020, Allscripts Healthcare Solutions, Inc. launched the Sunrise 20.0 electronic health record, an evidence-based platform for clinicians. The platform offers integrated analytics, enabling healthcare practices to deliver better health outcomes. The new version runs on Microsoft Azure and is powered with features for improved performance.
• In December 2020, Elsevier B.V. (a subsidiary of RELX Group) acquired Shadow Health, a developer of virtual simulations in healthcare education. The acquisition has enhanced Elsevier B.V.’s virtual education and clinical practice solutions for healthcare providers.
• In May 2020, Oncology Analytics, Inc. raised $28 million in its Series C funding round. The round was led by Baird Capital and joined existing investors, including McKesson Ventures, Oak HC/FT, and The Blue Venture Fund.

Key Issues Addressed

• What is the market size by various segmentation of the region's clinical decision support systems and their respective countries?
• What are the customer buying behavior, key takeaways, and Porter's five forces of the clinical decision support systems market?
• What are the key opportunities and trends for manufacturers in the clinical decision support systems supply chain?
• What are the market's fundamental dynamics (drivers, restraints, opportunities, and challenges)?
• What and how are regulations, schemes, patents, and policies impacting the market's growth?
• What are the upcoming technological solutions influencing market trends? How will existing companies adapt to the new change in technology?
• The market player positioning, top winning strategies by years, company product developments, and launches will be?
• How has COVID-19 impacted the demand and sales of clinical decision support systems in the global market? Also, the expected BPS drop or rise count of the market and market predicted recovery period.
• Detailed analysis of the competitors and their latest launch, and what are the prominent startups introduced in the target market? Also, detailed company profiling of 25+ leading and prominent companies in the market.