[333 Pages Report] The global clinical decision support systems market is projected to have a moderate-paced CAGR of 10.4% during the forecast period. The current valuation of the clinical decision support systems market is US$ 5.46 Bn in 2023. The value of the clinical decision support systems market is anticipated to reach a high of US$ 14.69 Bn by the year 2033.
This growth in the sales of clinical decision support systems is supported by the following:
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The growth of the cloud-based sector of the market is being fuelled primarily by rising healthcare costs and the widespread use of cloud computing. Governments across Europe are taking steps to encourage the expansion of healthcare IT. For instance, in February 2021, nearly two million National Health Services (NHS) mail mailboxes were migrated to Exchange Online, which is a part of Microsoft's Azure Cloud, as part of the UK government's aim to embrace a fully linked cloud-driven health service. Staff across NHS organizations and departments is expected to be able to communicate with one another more effectively and have easier access to relevant data as a result of this. Because of this, the need for HCIT Change Management services in the United Kingdom is likely to rise, driving the industry forward.
Additionally, clinical decision support solutions that rely on local knowledge management may incur substantial running expenses due to the large amounts of processing power and storage space that may be required. Unlike locally hosted apps, cloud-based ones are hosted on remote servers and don't necessitate a lot of processing power or storage space on the user's end.
By design, cloud-based apps are more secure than their web-based counterparts since they don't rely on browsers. The processing nodes of cloud-based clinical decision support solutions reside on distant servers, which may be in several different data centres across the world. Over the forecast period, cloud-based CDSS adoption is likely to rise in tandem with the proliferation of cloud technologies due to their many advantages.
Attributes | Details |
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Market Value (2023) | US$ 5.46 Billion |
Market Value (2033) | US$ 14.69 Billion |
CAGR | 10.4% |
Increasing technological sophistication and the growing influence of social media.
Another developing pattern in CDSS products is providing access to many media outlets. For instance, social media data acquired for patients with chronic diseases have been included in the cloud-based Smart Clinical Decision Support System (Smart CDSS) established by independent researchers. This information is combined with clinical observations from actual patient experiences. Patient health, mood, and hobbies are tracked through their social media activity by the system. It gathers patient-specific information from Twitter, e-mail analysis, and other social media platforms by mining for keywords, concepts, and feelings. As a result, doctors are better able to make treatment decisions based on the individual patient's behaviour and way of life. The data is then used by the Smart CDSS to make personalised suggestions for each individual patient.
Problems with cloud based CDSS data security
Data hosted by the vendor is not as secure as on-premises data, which is a big problem with cloud-based CDSS. The confidentiality of patient records is of the utmost importance to ensure that data is only accessed by those who have a legitimate need to know. Data privacy regulations regulated under HIPAA, for example, are constantly under review by legal frameworks (Health Insurance Portability and Accountability Act). The EU Data Protection Regulation also has ramifications for the security of personal health information in the European Union. The healthcare business is uncertain about the efficacy of private clouds, despite their offering of additional access methods and health information technology systems.
A severe lack of competent information technology specialists is plaguing the healthcare sector.
Strong IT infrastructure and support, both inside the company and from the solution vendor, are required for the effective use of healthcare IT solutions. It is essential for a healthcare business to have reliable technical assistance in order to keep its server and network running smoothly, which is essential for clinical workflows and healthcare IT system interface performance. Poor server or network maintenance can cause screen loads, which in turn can impede down clinical workflow. Adoption and deployment of health information technology systems, whether cloud-based or installed on-premises, are hampered by a lack of educated and qualified labor in key markets.
In 2021, standalone CDSS had more than 31.00% of the market because of its widespread adoption, low cost, and ease of use. As a result of its superior usability in healthcare facilities, it has taken the lead in most of these applications. Throughout the anticipated time frame, the solo subsegment is expected to maintain its dominant position. CDSS solutions can function alone or can be integrated with an electronic health record system or computerized provider order entry system.
By 2030, the market for integrated EHR and CDSS is expected to have grown substantially. The percentage of CDSS that is integrated with EHR is likely to change as more and more multi-specialty healthcare units become familiar with and use EHR. These health information technology systems collect patient data and send it to a clinical decision support system (CDSS), which then automates the clinical workflow by providing the doctor with clinical solutions and prescription recommendations. Integration between CDSS and EHRs is commonplace to facilitate the utilization of existing data sets and improve efficiency. The increasing integration of CDSS features into EHR systems is a factor that bodes well for the development of this market.
In 2021, drug allergy alerts had more than 26.0% share of the market. Since many people have life-threatening reactions to even the smallest amounts of some medications, it's crucial to have early warning systems in place. Allergies, especially those to medication, are becoming more of a problem. Accidental pharmaceutical administration to a patient with a known allergy, for example, is an example of a medicine error that can have serious consequences at any stage of the drug's life cycle.
During the foreseeable future, the market for clinical guidelines should expand at a profitable rate. The CDS provides recommendations for both diagnosis and treatment. It accesses information stored in a database and applies it to patient care, giving the doctor or nurse specific instructions to follow when they provide treatment.
Market Value (2023) | US$ 5.92 Billion |
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Market Value (2033) | US$ 14.41 Billion |
CAGR | 9.3% |
USA market is expected to reach a valuation of US$ 14.41 Billion by 2033 from US$ 5.92 Bn in 2023. The growth rate is likely to be 9.3%.
One of the key factors in the region's rising market revenue is the development of information technology in the medical sector. The use of electronic health record (EHR)-equipped clinical decision support system platforms is expected to rise in the United States throughout the healthcare industry in the next years, as reported by the Office of the National Coordinator for Health Information Technology (ONC). A rise in adoption can be seen in areas such as pediatric healthcare (68%) and specialty industries (43%). The increasing need for CDSS that integrates with electronic health records is driving the market expansion in this area. This region's governments are likewise making investments in an automated healthcare environment powered by AI.
Furthermore, governments are implementing programmes to raise awareness among hospitals of the uses and benefits of CDSS, as well as the wide range of innovative CDSS technologies currently available. For instance, the U.S. Centers for Medicare & Medicaid Services (CMS) announced on November 18, 2020, that it would offer incentives to doctors who use certain clinical decision-support devices when making a diagnosis. Incentives for the use of Viz.ai's ContaCT and Digital Diagnostics' IDX-DR have been announced by CMS. There has been a rise in market revenue in this area thanks to these strategic activities.
In 2021, Europe remained a reliable source of revenue. The clinical decision support system market is growing as a result of rising investments in the digitalization and automation of healthcare services. UK-based NHS provider Global Digital Exemplar reports that the government of the United Kingdom invested GBP 395 million to facilitate greater integration of clinical decision support solutions across the healthcare sector. Clinical decision systems in healthcare that are integrated with artificial intelligence have been established with funding from the governments of France (EUR 500 million) and Germany (EUR 3.4 billion). It is anticipated that these funds would be used to enhance Europe's clinical decision support system platform's information technology infrastructure and related services.
Demand for clinical decision support system hardware is growing in this area for several reasons, including the region's growing elderly population. European Union (EU) estimates suggest that by 2021, one in five Europeans is expected to be 65 or older. The percentage of the EU's population that is 80 or older is projected to rise from 6% in 2021 to 14.6% in 2100. Moreover, an aging population means an increase in patient load, which should boost demand for clinical decision support systems in the future.
High rates of medication errors, the rising popularity of big data and mobile health applications, the rising adoption of cloud computing in healthcare, rising returns on investment for CDSS solutions, and collaborations between clinical decision support businesses and medical research organisations are the primary factors propelling the CDSS market. However, the industry could be hampered by skepticism about mobile CDSS, worries about cloud-based CDSS's security, the need for costly IT infrastructure, and a lack of interoperability. Increases in healthcare IT solution innovation and the emergence of new healthcare IT markets present promising prospects.
Significant clinical decision support systems market revenue growth in this region is being driven by an increase in the number of patients and an increase in the need for AI-enabled automated equipment. There has been a recent uptick in the number of healthcare and IT company mergers, which bodes well for the market's future revenue growth. Elsevier and Gramin Health Care launched their artificial intelligence (AI)-powered platform ClinicalPath Primary Care India in the fall of 2021. A clinical decision support tool, it automates clinical guidelines for antenatal care, allowing for more individualized care for mothers experiencing complications during pregnancy. Additionally, it gives first responders in the field of mother and infant health access to automated medical prescriptions and counseling.
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New Entrants to Foster Innovation in the Global Market
The startups in the clinical decision support systems market are adding a new edge to the properties of excavators by curating innovations beyond the imagination. They are continually upgrading the Clinical Decision Support Systems with advanced technology, and manufacturers and sellers are continuously attempting to reduce costs for greater accessibility to the market share. Startup firms are triggering the expansion of the clinical decision support systems market with their unique attempts.
Top startups operating in the market are:
Name | Description |
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DXS International | As a clinical decision support provider, DXS International has been serving the primary care and retail pharmacy industries. A Clinical Decision Support System, DXS Point-of-Care (DXS PoC) (CDSS). Best Triage is a triage management solution that helps prioritise patients for medical treatment based on the severity of the condition or injury and acts as a referral peer review platform; Best Script is a medicine database; and Best Pathways is a care protocol that includes NHS Best Evidence guidance for each stage of the management of a patient with a specific condition. DXS Directory-of-Services (DoS) is an up-to-date resource for primary care physicians and nurses looking for referral information. |
Agathos | Clinicians' decision-making software. The company's web interface and analytics platform compile a wide range of clinical, claims, and economic data; define objectives by blending external standards with administrator and physician incentives; deliver timely, relevant, and actionable insights to physicians; and modify content to maximise user engagement and the attainment of objectives. Most of the the company's income comes from monthly subscription fees charged to doctors by system administrators for using the software as a service. |
As with many industries, competition in the global demand for clinical decision support systems is fierce. Market leaders include companies like McKesson, Philips, Wolters Kluwer, Cerner, Siemens, and Wolters Kluwer NU. To differentiate themselves from the competition, these companies create new products, develop improved versions of existing ones, merge with others, and form strategic alliances.
To give one specific example, in April 2021, Change Healthcare introduced InterQual 2021, the latest edition of the company's main CDS product. New guidelines for COVID-19 patients, consideration of socioeconomic determinants of health, and appropriate telehealth use are just a few of the evidence-based content updates and additions that accompany this release's four novel Medicare criterion elements.
In addition, a CDSS for the detection of COVID-19 was announced to be developed in collaboration with DHIndia, EHRC@IIITB, and Healthelife in May 2020. The collaboration also resulted in the development of a basic triage program for use by emergency room physicians.
Market leaders in clinical decision support systems worldwide include:
The growth outlook for the Clinical Decision Support Systems market is predicted to advance at a CAGR of 10.4% from 2023 to 2033.
The North American region is anticipated to lead the Clinical Decision Support Systems market during the forecast period.
The market valuation of the Clinical Decision Support Systems market stands at US$ 5.46 Bn in 2023.
The Clinical Decision Support Systems market is likely to hold a valuation of US$ 14.69 Bn by 2033.
1. Executive Summary 1.1. Global Market Outlook 1.2. Demand-side Trends 1.3. Supply-side Trends 1.4. Technology Roadmap Analysis 1.5. Analysis and Recommendations 2. Market Overview 2.1. Market Coverage / Taxonomy 2.2. Market Definition / Scope / Limitations 3. Market Background 3.1. Market Dynamics 3.1.1. Drivers 3.1.2. Restraints 3.1.3. Opportunity 3.1.4. Trends 3.2. Scenario Forecast 3.2.1. Demand in Optimistic Scenario 3.2.2. Demand in Likely Scenario 3.2.3. Demand in Conservative Scenario 3.3. Opportunity Map Analysis 3.4. Investment Feasibility Matrix 3.5. PESTLE and Porter’s Analysis 3.6. Regulatory Landscape 3.6.1. By Key Regions 3.6.2. By Key Countries 3.7. Regional Parent Market Outlook 4. Global Market Analysis 2017-2021 and Forecast, 2022-2032 4.1. Historical Market Size Value (US$ Mn) Analysis, 2017-2021 4.2. Current and Future Market Size Value (US$ Mn) Projections, 2022-2032 4.2.1. Y-o-Y Growth Trend Analysis 4.2.2. Absolute $ Opportunity Analysis 5. Global Market Analysis 2017-2021 and Forecast 2022-2032, By Product 5.1. Introduction / Key Findings 5.2. Historical Market Size Value (US$ Mn) Analysis By Product, 2017-2021 5.3. Current and Future Market Size Value (US$ Mn) Analysis and Forecast By Product, 2022-2032 5.3.1. Standalone CDSS 5.3.2. Integrated CPOE with CDSS 5.3.3. Integrated E.H.R. with CDSS 5.3.4. Integrated CDSS with CPOE & E.H.R. 5.4. Y-o-Y Growth Trend Analysis By Product, 2017-2021 5.5. Absolute $ Opportunity Analysis By Product, 2022-2032 6. Global Market Analysis 2017-2021 and Forecast 2022-2032, By Application 6.1. Introduction / Key Findings 6.2. Historical Market Size Value (US$ Mn) Analysis By Application , 2017-2021 6.3. Current and Future Market Size Value (US$ Mn) Analysis and Forecast By Application , 2022-2032 6.3.1. Drug-drug interactions 6.3.2. Drug allergy alerts 6.3.3. Clinical reminders 6.3.4. Clinical guidelines 6.3.5. Drug dosing support 6.3.6. Others 6.4. Y-o-Y Growth Trend Analysis By Application , 2017-2021 6.5. Absolute $ Opportunity Analysis By Application , 2022-2032 7. Global Market Analysis 2017-2021 and Forecast 2022-2032, By Delivery Mode 7.1. Introduction / Key Findings 7.2. Historical Market Size Value (US$ Mn) Analysis By Delivery Mode , 2017-2021 7.3. Current and Future Market Size Value (US$ Mn) Analysis and Forecast By Delivery Mode , 2022-2032 7.3.1. Web Delivery 7.3.2. Cloud Delivery 7.3.3. On Premises Delivery 7.4. Y-o-Y Growth Trend Analysis By Delivery Mode , 2017-2021 7.5. Absolute $ Opportunity Analysis By Delivery Mode , 2022-2032 8. Global Market Analysis 2017-2021 and Forecast 2022-2032, By Component 8.1. Introduction / Key Findings 8.2. Historical Market Size Value (US$ Mn) Analysis By Component , 2017-2021 8.3. Current and Future Market Size Value (US$ Mn) Analysis and Forecast By Component , 2022-2032 8.3.1. Hardware 8.3.2. Software 8.3.3. Services 8.4. Y-o-Y Growth Trend Analysis By Component , 2017-2021 8.5. Absolute $ Opportunity Analysis By Component , 2022-2032 9. Global Market Analysis 2017-2021 and Forecast 2022-2032, By Region 9.1. Introduction 9.2. Historical Market Size Value (US$ Mn) Analysis By Region, 2017-2021 9.3. Current Market Size Value (US$ Mn) Analysis and Forecast By Region, 2022-2032 9.3.1. North America 9.3.2. Latin America 9.3.3. Europe 9.3.4. South Asia 9.3.5. East Asia 9.3.6. Oceania 9.3.7. MEA 9.4. Market Attractiveness Analysis By Region 10. North America Market Analysis 2017-2021 and Forecast 2022-2032, By Country 10.1. Historical Market Size Value (US$ Mn) Trend Analysis By Market Taxonomy, 2017-2021 10.2. Market Size Value (US$ Mn) Forecast By Market Taxonomy, 2022-2032 10.2.1. By Country 10.2.1.1. U.S. 10.2.1.2. Canada 10.2.2. By Product 10.2.3. By Application 10.2.4. By Delivery Mode 10.2.5. By Component 10.3. Market Attractiveness Analysis 10.3.1. By Country 10.3.2. By Product 10.3.3. By Application 10.3.4. By Delivery Mode 10.3.5. By Component 10.4. Key Takeaways 11. Latin America Market Analysis 2017-2021 and Forecast 2022-2032, By Country 11.1. Historical Market Size Value (US$ Mn) Trend Analysis By Market Taxonomy, 2017-2021 11.2. Market Size Value (US$ Mn) Forecast By Market Taxonomy, 2022-2032 11.2.1. By Country 11.2.1.1. Brazil 11.2.1.2. Mexico 11.2.1.3. Rest of Latin America 11.2.2. By Product 11.2.3. By Application 11.2.4. By Delivery Mode 11.2.5. By Component 11.3. Market Attractiveness Analysis 11.3.1. By Country 11.3.2. By Product 11.3.3. By Application 11.3.4. By Delivery Mode 11.3.5. By Component 11.4. Key Takeaways 12. Europe Market Analysis 2017-2021 and Forecast 2022-2032, By Country 12.1. Historical Market Size Value (US$ Mn) Trend Analysis By Market Taxonomy, 2017-2021 12.2. Market Size Value (US$ Mn) Forecast By Market Taxonomy, 2022-2032 12.2.1. By Country 12.2.1.1. Germany 12.2.1.2. U.K. 12.2.1.3. France 12.2.1.4. Spain 12.2.1.5. Italy 12.2.1.6. Rest of Europe 12.2.2. By Product 12.2.3. By Application 12.2.4. By Delivery Mode 12.2.5. By Component 12.3. Market Attractiveness Analysis 12.3.1. By Country 12.3.2. By Product 12.3.3. By Application 12.3.4. By Delivery Mode 12.3.5. By Component 12.4. Key Takeaways 13. South Asia Market Analysis 2017-2021 and Forecast 2022-2032, By Country 13.1. Historical Market Size Value (US$ Mn) Trend Analysis By Market Taxonomy, 2017-2021 13.2. Market Size Value (US$ Mn) Forecast By Market Taxonomy, 2022-2032 13.2.1. By Country 13.2.1.1. India 13.2.1.2. Malaysia 13.2.1.3. Singapore 13.2.1.4. Thailand 13.2.1.5. Rest of South Asia 13.2.2. By Product 13.2.3. By Application 13.2.4. By Delivery Mode 13.2.5. By Component 13.3. Market Attractiveness Analysis 13.3.1. By Country 13.3.2. By Product 13.3.3. By Application 13.3.4. By Delivery Mode 13.3.5. By Component 13.4. Key Takeaways 14. East Asia Market Analysis 2017-2021 and Forecast 2022-2032, By Country 14.1. Historical Market Size Value (US$ Mn) Trend Analysis By Market Taxonomy, 2017-2021 14.2. Market Size Value (US$ Mn) Forecast By Market Taxonomy, 2022-2032 14.2.1. By Country 14.2.1.1. China 14.2.1.2. Japan 14.2.1.3. South Korea 14.2.2. By Product 14.2.3. By Application 14.2.4. By Delivery Mode 14.2.5. By Component 14.3. Market Attractiveness Analysis 14.3.1. By Country 14.3.2. By Product 14.3.3. By Application 14.3.4. By Delivery Mode 14.3.5. By Component 14.4. Key Takeaways 15. Oceania Market Analysis 2017-2021 and Forecast 2022-2032, By Country 15.1. Historical Market Size Value (US$ Mn) Trend Analysis By Market Taxonomy, 2017-2021 15.2. Market Size Value (US$ Mn) Forecast By Market Taxonomy, 2022-2032 15.2.1. By Country 15.2.1.1. Australia 15.2.1.2. New Zealand 15.2.2. By Product 15.2.3. By Application 15.2.4. By Delivery Mode 15.2.5. By Component 15.3. Market Attractiveness Analysis 15.3.1. By Country 15.3.2. By Product 15.3.3. By Application 15.3.4. By Delivery Mode 15.3.5. By Component 15.4. Key Takeaways 16. MEA Market Analysis 2017-2021 and Forecast 2022-2032, By Country 16.1. Historical Market Size Value (US$ Mn) Trend Analysis By Market Taxonomy, 2017-2021 16.2. Market Size Value (US$ Mn) Forecast By Market Taxonomy, 2022-2032 16.2.1. By Country 16.2.1.1. GCC Countries 16.2.1.2. South Africa 16.2.1.3. Israel 16.2.1.4. Rest of MEA 16.2.2. By Product 16.2.3. By Application 16.2.4. By Delivery Mode 16.2.5. By Component 16.3. Market Attractiveness Analysis 16.3.1. By Country 16.3.2. By Product 16.3.3. By Application 16.3.4. By Delivery Mode 16.3.5. By Component 16.4. Key Takeaways 17. Key Countries Market Analysis 17.1. U.S. 17.1.1. Pricing Analysis 17.1.2. Market Share Analysis, 2021 17.1.2.1. By Product 17.1.2.2. By Application 17.1.2.3. By Delivery Mode 17.1.2.4. By Component 17.2. Canada 17.2.1. Pricing Analysis 17.2.2. Market Share Analysis, 2021 17.2.2.1. By Product 17.2.2.2. By Application 17.2.2.3. By Delivery Mode 17.2.2.4. By Component 17.3. Brazil 17.3.1. Pricing Analysis 17.3.2. Market Share Analysis, 2021 17.3.2.1. By Product 17.3.2.2. By Application 17.3.2.3. By Delivery Mode 17.3.2.4. By Component 17.4. Mexico 17.4.1. Pricing Analysis 17.4.2. Market Share Analysis, 2021 17.4.2.1. By Product 17.4.2.2. By Application 17.4.2.3. By Delivery Mode 17.4.2.4. By Component 17.5. Germany 17.5.1. Pricing Analysis 17.5.2. Market Share Analysis, 2021 17.5.2.1. By Product 17.5.2.2. By Application 17.5.2.3. By Delivery Mode 17.5.2.4. By Component 17.6. U.K. 17.6.1. Pricing Analysis 17.6.2. Market Share Analysis, 2021 17.6.2.1. By Product 17.6.2.2. By Application 17.6.2.3. By Delivery Mode 17.6.2.4. By Component 17.7. France 17.7.1. Pricing Analysis 17.7.2. Market Share Analysis, 2021 17.7.2.1. By Product 17.7.2.2. By Application 17.7.2.3. By Delivery Mode 17.7.2.4. By Component 17.8. Spain 17.8.1. Pricing Analysis 17.8.2. Market Share Analysis, 2021 17.8.2.1. By Product 17.8.2.2. By Application 17.8.2.3. By Delivery Mode 17.8.2.4. By Component 17.9. Italy 17.9.1. Pricing Analysis 17.9.2. Market Share Analysis, 2021 17.9.2.1. By Product 17.9.2.2. By Application 17.9.2.3. By Delivery Mode 17.9.2.4. By Component 17.10. India 17.10.1. Pricing Analysis 17.10.2. Market Share Analysis, 2021 17.10.2.1. By Product 17.10.2.2. By Application 17.10.2.3. By Delivery Mode 17.10.2.4. By Component 17.11. Malaysia 17.11.1. Pricing Analysis 17.11.2. Market Share Analysis, 2021 17.11.2.1. By Product 17.11.2.2. By Application 17.11.2.3. By Delivery Mode 17.11.2.4. By Component 17.12. Singapore 17.12.1. Pricing Analysis 17.12.2. Market Share Analysis, 2021 17.12.2.1. By Product 17.12.2.2. By Application 17.12.2.3. By Delivery Mode 17.12.2.4. By Component 17.13. Thailand 17.13.1. Pricing Analysis 17.13.2. Market Share Analysis, 2021 17.13.2.1. By Product 17.13.2.2. By Application 17.13.2.3. By Delivery Mode 17.13.2.4. By Component 17.14. China 17.14.1. Pricing Analysis 17.14.2. Market Share Analysis, 2021 17.14.2.1. By Product 17.14.2.2. By Application 17.14.2.3. By Delivery Mode 17.14.2.4. By Component 17.15. Japan 17.15.1. Pricing Analysis 17.15.2. Market Share Analysis, 2021 17.15.2.1. By Product 17.15.2.2. By Application 17.15.2.3. By Delivery Mode 17.15.2.4. By Component 17.16. South Korea 17.16.1. Pricing Analysis 17.16.2. Market Share Analysis, 2021 17.16.2.1. By Product 17.16.2.2. By Application 17.16.2.3. By Delivery Mode 17.16.2.4. By Component 17.17. Australia 17.17.1. Pricing Analysis 17.17.2. Market Share Analysis, 2021 17.17.2.1. By Product 17.17.2.2. By Application 17.17.2.3. By Delivery Mode 17.17.2.4. By Component 17.18. New Zealand 17.18.1. Pricing Analysis 17.18.2. Market Share Analysis, 2021 17.18.2.1. By Product 17.18.2.2. By Application 17.18.2.3. By Delivery Mode 17.18.2.4. By Component 17.19. GCC Countries 17.19.1. Pricing Analysis 17.19.2. Market Share Analysis, 2021 17.19.2.1. By Product 17.19.2.2. By Application 17.19.2.3. By Delivery Mode 17.19.2.4. By Component 17.20. South Africa 17.20.1. Pricing Analysis 17.20.2. Market Share Analysis, 2021 17.20.2.1. By Product 17.20.2.2. By Application 17.20.2.3. By Delivery Mode 17.20.2.4. By Component 17.21. Israel 17.21.1. Pricing Analysis 17.21.2. Market Share Analysis, 2021 17.21.2.1. By Product 17.21.2.2. By Application 17.21.2.3. By Delivery Mode 17.21.2.4. By Component 18. Market Structure Analysis 18.1. Competition Dashboard 18.2. Competition Benchmarking 18.3. Market Share Analysis of Top Players 18.3.1. By Regional 18.3.2. By Product 18.3.3. By Application 18.3.4. By Delivery Mode 18.3.5. By Component 19. Competition Analysis 19.1. Competition Deep Dive 19.1.1. McKesson Corporation 19.1.1.1. Overview 19.1.1.2. Product Portfolio 19.1.1.3. Profitability by Market Segments 19.1.1.4. Sales Footprint 19.1.1.5. Strategy Overview 19.1.1.5.1. Marketing Strategy 19.1.2. Cerner Corporation 19.1.2.1. Overview 19.1.2.2. Product Portfolio 19.1.2.3. Profitability by Market Segments 19.1.2.4. Sales Footprint 19.1.2.5. Strategy Overview 19.1.2.5.1. Marketing Strategy 19.1.3. Siemens Healthineers GmbH 19.1.3.1. Overview 19.1.3.2. Product Portfolio 19.1.3.3. Profitability by Market Segments 19.1.3.4. Sales Footprint 19.1.3.5. Strategy Overview 19.1.3.5.1. Marketing Strategy 19.1.4. Allscripts Healthcare, LLC 19.1.4.1. Overview 19.1.4.2. Product Portfolio 19.1.4.3. Profitability by Market Segments 19.1.4.4. Sales Footprint 19.1.4.5. Strategy Overview 19.1.4.5.1. Marketing Strategy 19.1.5. athenahealth, Inc. 19.1.5.1. Overview 19.1.5.2. Product Portfolio 19.1.5.3. Profitability by Market Segments 19.1.5.4. Sales Footprint 19.1.5.5. Strategy Overview 19.1.5.5.1. Marketing Strategy 19.1.6. NextGen Healthcare Inc. 19.1.6.1. Overview 19.1.6.2. Product Portfolio 19.1.6.3. Profitability by Market Segments 19.1.6.4. Sales Footprint 19.1.6.5. Strategy Overview 19.1.6.5.1. Marketing Strategy 19.1.7. Koninklijke Philips N.V. (Royal Philips) 19.1.7.1. Overview 19.1.7.2. Product Portfolio 19.1.7.3. Profitability by Market Segments 19.1.7.4. Sales Footprint 19.1.7.5. Strategy Overview 19.1.7.5.1. Marketing Strategy 19.1.8. IBM Corporation 19.1.8.1. Overview 19.1.8.2. Product Portfolio 19.1.8.3. Profitability by Market Segments 19.1.8.4. Sales Footprint 19.1.8.5. Strategy Overview 19.1.8.5.1. Marketing Strategy 19.1.9. Agfa-Gevaert Group 19.1.9.1. Overview 19.1.9.2. Product Portfolio 19.1.9.3. Profitability by Market Segments 19.1.9.4. Sales Footprint 19.1.9.5. Strategy Overview 19.1.9.5.1. Marketing Strategy 19.1.10. Wolters Kluwer N.V. 19.1.10.1. Overview 19.1.10.2. Product Portfolio 19.1.10.3. Profitability by Market Segments 19.1.10.4. Sales Footprint 19.1.10.5. Strategy Overview 19.1.10.5.1. Marketing Strategy 20. Assumptions & Acronyms Used 21. Research Methodology
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