A new report collated by Fact.MR projects the global big data analytics in healthcare market to exhibit a high double-digit CAGR through the forecast period 2017 to 2026. Over US$ 45,000 Mn revenues will be reaped from worldwide sales of big data analytics in the healthcare market by 2026-end.
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Big Data Analytics to Boost Precision Medicine Research
Precision medicine holds potential to shift from the one-size-fits-all approach toward using patient-specific therapeutics by using large amount of data gathered from tools including genomics, mobile biometric sensors, and smartphone apps. Health data is enabling doctors in building predictive models and better patient profiles for more effective anticipation, diagnosis and treatment of various diseases. In addition, partnerships and collaborations between healthcare organizations and researchers have resulted into the development of data pools, which can be used for constructing better personalized healthcare models. Such new capabilities are yet at a nascent phase, and big data capabilities & policies are expected to expand for enabling patient data to constantly inform health research.
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Big Data Analytics to help Healthcare Organizations in Cutting Costs
Several healthcare organizations are already using big data analytics, and majority among these believe big data analytics would save them over 25% in annual costs in the upcoming years. One of the several ways that big data analytics can enable cost reduction is by curtailing the hospital readmission rate. The big data analytics approach is adhered by healthcare organizations while seeking relationships consistent with readmissions, which they could not predict or understand before. Once these relationships are identified, healthcare organizations can set up protocols for dealing with patients and prevent readmission. In addition, big data analytics can enable forecasting operating room demands, optimizing staffing, streamlining patient care, and creating measures for improving pharmaceutical supply chain.
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6 Key Takeaways from Fact.MR’s Report on Big Data Analytics in Healthcare Market
- Asia-Pacific excluding Japan (APEJ) is anticipated to remain the fast-expanding as well as the most remunerative market for big data analytics in healthcare. North America and Europe will also remain lucrative regions for expansion of the market, with revenues projected to increase at an approximately equal CAGR through 2026. The markets in Latin America and Japan will reflect a relatively higher CAGR than those in North America and Europe, although accounting for relatively lower revenues during the forecast period.
- Healthcare provider is expected to remain the dominant spender in the global big data analytics in healthcare market. However, revenues from healthcare payer will increase at a significantly higher CAGR than those from healthcare provider during 2017 to 2026.
- CRM analytics is expected to remain preferred among tools for big data analytics in healthcare, followed by financial analytics and production reporting. Sales of visual analytics will exhibit the fastest expansion through 2026, based on tool type.
- Access operational information is anticipated to remain the largest application of big data analytics in healthcare, in terms of revenues.
- Although on-premises deployment will remain sought-after in the market, sales of cloud-based deployment will register a relatively faster expansion through 2026.
- In this highly competitive market, healthcare settings are expected to be the highest gainers. In current market scenario, vendors are increasingly competing to outdo the others, and focusing more on offering innovative healthcare services. Key companies profiled by Fact.MR’s report include Denodo Technologies Inc., Alteryx, SAP SE, SAS Instiute, Infosys, Cisco Systems Inc., Zephyr Health, Cerner Corp, Oracle Corp, MEDai’s Health, McKesson, Microsoft Corp, and OptumHealth Care Solutions.
Market Taxonomy
| Region | North AmericaLatin AmericaEuropeJapanAPEJMEA |
| Spender Type | Healthcare PayerHealthcare Provider |
| Tool Type | Data Warehouse AnalyticsFinancial AnalyticsProduction ReportingCRM AnalyticsPredictive AnalyticsVisual AnalyticsRisk Management AnalyticsSupply chain AnalyticsTest Analytics |
| Application Type | Access Clinical InformationAccess Operational InformationAccess Transactional DataOther Applications |
| Deployment Type | Cloud-basedOn-premises |
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