Business Health

Clinical Decision Support Systems Market: Opportunities and Challenges

Press Release

The Clinical Decision Support Systems Market is projected to reach $1,752.0 million by 2023 from $901.0 Million in 2017, at a CAGR of 11.8%.

Technological advancements in healthcare IT solutions

The healthcare marketplace is being transformed by a wave of technological advancements. The adoption of new digital health information technology (HIT) advances, such as EHRs, mHealth applications, and predictive analytics, are equipping healthcare providers to deliver high-quality care to patients. Digital innovations, such as wireless scales, wearable devices, and other types of sensors are enabling data collection and integration, data analysis, and evidence-based decision-making. Technological advancements are also connecting developed and emerging markets and participants along the healthcare value chain.

Furthermore, the high penetration of internet and social media is highlighting cases of medication errors, adverse drug events, and drug interactions. This is bound to increase the adoption of HCIT solutions such as CDSS to reduce errors, legal implications such as medical malpractice and negligence cases, and healthcare costs.

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Moreover, social media data can also be leveraged to support CDSS. For instance, the cloud-based Smart Clinical Decision Support System (Smart CDSS) developed by private researchers integrates social media data captured for a patient with a chronic condition and combines it with clinical observations from real encounters in healthcare facilities. The system monitors health conditions, emotions, and interests of patients from their social media interactions.

It extracts keywords, concepts, and sentiments from Twitter, e-mail analysis, and other social media platforms and supplies patient-specific data to healthcare providers. This helps health practitioners to understand the behavior and lifestyle of patients for better decision-making about treatment. The input is further used by Smart CDSS to suggest patient-specific recommendations (Source: Health and Technology, June 2013, Volume 3, Issue 2, pp 153–175).

Moreover, recent studies of implementing pharmacogenomics in clinical care has the potential to revolutionize the healthcare system, it challenges the traditional method of prescribing medications. Thus, technological advancements and the growing popularity of social media provide opportunities for growth of the clinical decision support systems market.

Integration of CDSS solutions within healthcare organizations

The healthcare industry is highly information-intensive, wherein patient information is generated in all departments and at all points of care within a healthcare organization. However, the usability of this information is very low if it is not integrated properly to create an exhaustive and accurate patient record. Since CDSS is used within healthcare systems, there is a greater need to integrate CDSS, in order to aid accurate decision-making by healthcare professionals at different points of care delivery.

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Currently, many healthcare organizations have invested in various information management applications, such as imaging systems, email management systems, database management systems, form management systems, clinical information systems, workforce management systems, asset management systems, content management systems, revenue cycle management systems, clinical and non-clinical workflow systems, and customer relation management systems. As healthcare organizations are increasingly adopting CDSS tools, there is a greater need for integrating different information technology systems into the IT architecture of an organization for ensuring their optimal utilization. As a result, the successful integration of CDSS with other systems is a major area of focus for IT infrastructure development projects.

However, integrating a new healthcare IT system with a healthcare organization’s existing legacy information management systems is a daunting task for market players. With differences in data communication standards, a number of information systems are unable to exchange data. This is limiting the successful utilization of CDSS by healthcare organizations, thereby lowering their adoption in the clinical decision support systems market.

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