Clinical Decision Support Systems Market: By Decision (Knowledge, Non-Knowledge Based); By Application (Alerts, Protocol Support, Others); By Timing (Pre, During & Post Diagnosis); By Device (Stand Alone, IS); By User interactivity (Active, Passive); By Delivery Mode (Cloud based, Web based, On Premise); By Component (Hardware, Software, Services); By End-User (Clinic, Pharmacy, Others); By Geography - Forecast (2018-2023)

Report Code : HCR 0007 Format Type: PDF+ Excel Database

The Global CDSS Market is estimated to grow at a CAGR of 9.5% during the forecast period 2018-2023. The North American region dominates the CDSS market and is expected to rise further due to the availability of sophisticated infrastructure, government support and flexible healthcare policies. In 2017, the knowledge based CDSS forms the larger segment of the total CDSS market and earned the revenue of $419.8m and is estimated to grow at a CAGR of 8.6% during 2018-2023. The opportunities in the current environment hold promise for increased use CDS as there are growing concerns about quality of care and awareness of healthcare tools among the clinicians. 

What is Clinical Decision Support System?
Clinical decision support is an important tool that provides information to the members of the care team which includes clinicians, nurses, patients, administrative staff or other members. The healthcare information obtained is filtered or targeted to a specific person or situation. CDSS is designed with an intention to improve care quality, avoid adverse events, and aids the care team members to be more efficient. As the volume of available data is increasing, the clinical decision support system has become an essential tool for healthcare providers. CDSS is widely used in pre-diagnosis, during diagnosis and post diagnostics as it helps the clinicians in making critical decisions.

What are the major applications of Clinical Decision Support System?
The major applications of Clinical Decision Support System includes patient safety, drug dosage calculations, obtaining the drug formulary guidelines, using severity indexes for specific illnesses, identifying reportable conditions based on EHR inputs, using time reminders for medication delivery or dosage changes, identifying needed preventive care screenings and accessing information or educational materials. Clinical decision support tools are designed in a way which suggests the type of test to be carried out, next steps for treatments, alert providers to available information they may not have seen, catch potential problems such as dangerous medication interactions.

Market Research and Market Trends of Clinical Decision Support System 
  • Researchers from MIT developed a deep learning tool that uses bedside monitors, clinical notes, and other data sources to predict the condition of the ICU patients in order to alter their care plans for highly complex patients. As AI and machine learning are gaining a wide scope in healthcare, more and more CDS tools are being built based on these analytical methods.
  • Scientists from University of Pennsylvania have discovered a CDS tool that reduces the time to detect a life threatening infection sepsis, by 12 hours, which could save the lives of several the difference between life and death for many individuals. It involves machine learning and the algorithm used data from approximately 160,000 patients for training and was further validated on a sample of 10,000 individuals.
  • In April 2018, Point of Care Decision Support, who are the leaders in the development and implementation of anticoagulation clinical decision support software announced the release of a new version of their AC software.  This application was developed with the help of clinical thrombosis experts to address the complex challenges of managing both warfarin and non-vitamin K antagonist oral anticoagulants and enables healthcare provider teams to provide evidence based quality of care for patients on anticoagulants.
  • In April 2018, Apple announced that 39 health systems have signed on to enable access to patient’s health data through the company’s Health Record EHR patient data viewer. These companies are now able to view their health records from iOS devices including iPhones and iPads. The updated Health Records section within the Apple Health app allows patients to attain medical information from various healthcare organizations. The patients also receive notifications whenever their health data is updated and can further help to work with clinicians for better-informed clinical decision making.
  • MedCurrent has been qualified by the Centers for Medicare and Medicaid Services for its clinical decision support mechanism ‘OrderWise’. OrderWise is up to date and guides the healthcare providers to order the right imaging tests for the patients by obtaining information from Intermountain Healthcare, Sage Evidence-based Medicine & Practice Institute (SEMPI), National Comprehensive Cancer Network (NCCN) and the American College of Cardiology (ACC).

Who are the Major Players in Clinical Decision Support System market?
The companies referred in the market research report includes Alere Inc., Autonomy Corporation plc, Cerner Multum, Inc., EBSCO Industries, Inc., Elsevier Clinical Decision Support, Evidera/ Archimedes Inc., FirstDataBank, Inc. and more than 10 other companies.

What is our report scope?
The report incorporates in-depth assessment of the competitive landscape, product market sizing, product benchmarking, market trends, product developments, financial analysis, strategic analysis and so on to gauge the impact forces and potential opportunities of the market. Apart from this the report also includes a study of major developments in the market such as product launches, agreements, acquisitions, collaborations, mergers and so on to comprehend the prevailing market dynamics at present and its impact during the forecast period 2018-2024.

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Key Takeaways from this Report
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