Global Healthcare Business Intelligence Market is accounted for $3.75billion in 2017 and is expected to reach $15.88billion by 2026 growing at a CAGR of 17.4% during the forecast period. Growing pressure to restrict healthcare expenses and recover patient outcomes, rising amount of patient registries and increasing adoption of data-driven decision-making are some of the key factors propelling the market growth. However, requirement of high investments and lack of flexibility are restraining the market growth.
Healthcare Business Intelligence can assist healthcare providers gain the insight they need to decrease expenses, augment revenue and recover patient safety and outcomes while complying with rules and standards. By providing a base for evidence-based clinical decision-making, Business Intelligence (BI) can help to recover patient outcomes and enable physicians to better monitor and forecast patient diagnoses.
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Based on Application, Clinical Analysis segment holds the major growth during the forecast period owing to the increasing pressure to restrict healthcare spending, growing government incentives for getting better quality and falling the cost of care, rising implementation of EHRs, and building patient registries.
By Geography, North America holds the significant market share during the forecast period due to the rising implementation of healthcare intelligence solutions and services by healthcare providers to offer enhanced quality care and inferior healthcare expenses. In addition Federal mandates and regulatory reforms are expected to drive the market in this region.
Some of the key players in global Healthcare Business Intelligence market are Microsoft, IBM, Accenture, Information Builders, Board International, Oracle, SAP AG, Qlik Technologies, Microstrategy, SAS Institute, Tableau Software, Sisense, Yellowfin International, Agilum Healthcare Intelligence, TIBCO Software Inc., Perficient, Inc. and Siemens Healthcare.
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Functions Covered:
– Query and Reporting
– Performance Management
– Online Analytics Processing (OLAP) & Visualization
– Ad-hoc Analysis
– Data Mining
– Data Warehousing
– Datamarts
– Dashboards
– Prescriptive Analytics
– Predictive Analytics
– Other Functions
Components Covered:
– Software
– Platforms
– Services
Technologies Covered:
– Cloud Business Intelligence
– Mobile Business Intelligence
– Typical Architecture Business Intelligence
– Traditional Business Intelligence
– Other Technologies
Deployment Models Covered:
– Cloud-Based Model
– On-Premise Model
– Hybrid Model
Applications Covered:
– Operational Analysis
– Financial Analysis
– Clinical Analysis
– Quality Performance & Safety Analysis
– Patient Care Analysis
– Marketing Analysis
– Operational Performance & Cost Management
– Other Applications
End Users Covered:
– Providers
– Payers
– Other End Users
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