Reasons Why the Continuing Education for Medical Analytics is Important

In 2017, North America is expected to dominate the medical analytics market followed closely by Europe. This is one of the reasons why there has to be a Continuing Education for Medical Analytics. The rising importance of medical analytics in the North American market can be attributed to factors such as the growing federal healthcare mandates to curb rising healthcare costs and provide quality care; increasing regulatory requirements; growing EHR adoption; and rising government initiatives focusing on personalized medicine, population health management, and value-based reimbursements.

The clinical and medical analytics segment is projected to grow at the highest CAGR during the forecast period. By applications, the healthcare/medical analytics market is segmented into clinical analytics, financial analytics, operational and administrative analytics, and population health analytics. The clinical analytics segment is expected to grow at the highest rate during the forecast period. The high growth of this segment is attributed to the growing adoption of analytics by healthcare providers due to the rising pressure to curb healthcare costs, federal mandates such as the implementation of ICD-10 code sets, increasing adoption of electronic healthcare records, need to improve patient outcomes and reduce hospital readmission rates, and rising focus on personalized medicine-based analytics.

Continuing Education
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Medical analytics is used by providers to be able to identify clinically meaningful outcomes in relation to costs through investigational mining of electronic patient records for identifying inherent medical inaccuracies in the system so as to offer cost-effective treatments to patients while reducing the number of resources wasted. The uses are varied and new ways of application are being discovered every day. This is why medical professionals need to continue to educate themselves and stay up to date on the important updates. Medical Analytics can be used to reduce time to treatment, improve the performance of healthcare providers, there is risk mitigation, reduced rate of hospital readmissions, increasing use of personalized medicine, it eliminates the need of conducting additional diagnostic tests.

Advanced methods such as predictive analytics are widely used in government organizations such as healthcare financing systems primarily to avoid frauds in payments. For instance, in 2011, the Centers of Medicare and Medicaid Services (CMS) reported that under its Fraud Prevention System (FPS), predictive analytics helped in saving USD 1.5 billion through improper payments. Moreover, the CMS is developing next-generation predictive analytics, which is expected to boost the use of predictive analytics.

The healthcare analytics market is expected to reach USD 29.84 billion by 2022 from USD 8.92 billion in 2017, at a CAGR of 27.3%. The market is highly competitive with the presence of several small and big players. Some of the players in the healthcare analytics market include Allscripts (US), Cerner (US), Health Catalyst (US), and IBM (US). These are all United States Based Firms.

Limitations of Growth

Increasing government initiatives to increase EHR adoption, growing pressure to curb healthcare costs, availability of big data in healthcare, increasing venture capital investments, rising focus on improving patient outcomes, and technological advancements are driving the growth of the healthcare analytics market. On the other hand, factors like the lack of skilled analysts (that limits the use of healthcare solutions), the high cost of these solutions, and operational gaps between payers and providers, are expected to limit the growth of this market to a certain extent.

Types of Predictive Analytics

Continuing Education

By type, the healthcare analytics market is segmented into descriptive, predictive, and prescriptive analytics. The prescriptive analytics segment is expected grow at a highest CAGR during the forecast period. The high growth of this segment is attributed to the ability of prescriptive analytics to ensure the synergistic integration of predictions and prescriptions.

Based on application, the healthcare analytics market is segmented into clinical analytics, financial analytics, operational and administrative analytics, and population health analytics. Financial analytics market is segmented into revenue cycle management; claims processing; payment integrity and fraud, waste, & abuse (FWA); and risk adjustment and risk assessment. Due to the rising focus of payers on the early detection of fraud and reducing preventable costs, the market for fraud analytics is expected to register a significant growth during the forecast period, therefore driving the market for financial analytics.