Global Healthcare Analytics Market 2020-2027 | Know about Emerging Growth with Top Players like IBM, Wipro Limited, Allscripts, Cerner Corporation, Health Catalyst, Inovalon

Global Healthcare Analytics Market is projected to register a healthy CAGR of 15.4% in the forecast period of 2019 to 2026. Global Healthcare Analytics Market, By Type (Prescriptive Analytics, Predictive Analytics, Descriptive Analytics), Component (Services, Software, Hardware), Delivery Model (On-Demand, On-Premise), Application (Clinical Analytics, Population Health Analytics, Operational and Administrative Analytics, Financial Analytics), End User (Healthcare Payers, Healthcare Providers and ACOS, HIES, MCOS, AND TPAS) Industry Trends and Forecast to 2026), Geography (North America, Europe, Asia-Pacific, South America, Middle East and Africa)- Industry Trends and Forecast to 2026

Competitive Analysis:�

Some of the prominent participants operating in this market are IBM, Wipro Limited, Allscripts, Cerner Corporation, Health Catalyst, Inovalon, McKesson Corporation, MEDEANALYTICS, INC., Optum, Inc., Oracle, SAS Institute Inc., SCIOInspire, Corp., Verscend Technologies Pvt. Ltd, CitiusTech Inc. Vitreos Health, Ikon Tech IQVIA, and GENERAL ELECTRIC and others

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Healthcare analytics is also known as clinical data analytics which is the branch of analysis that offers insights into patient records, hospital management, diagnosis and more providing insights on macro and micro levels. Healthcare analytics helps in providing real-time data that can help in deciding the course of future treatment of the patient.

Analytics can be used in multiple ways in today's healthcare setting, like:

Operations management
Clinical variability (cost/quality/outcomes) assessment
Patient segmentation
Risk management
Population health
Patient monitoring
Drivers:�Global Healthcare Analytics Market

GROWING NEED TO CURB HEALTHCARE SPENDING WITH BETTER CLINICAL OUTCOMES

The U.S. spends the most amount of money on healthcare than any other nation worldwide. Per person spending in the U.S is USD 10.34, this amount to about 18% of their Gross Domestic Product. The growing cost of healthcare will burden all payers in the nation that avail its healthcare facilities. Primary care delivery through various coordinated-care models like patient-centred medical homes (PCMHs) will help in improving the quality of care and decreasing the cost. When compared with other nations, the United States higher levels of health care spending is majorly because of the increased prices for products and services instead of higher service volumes.

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ENTRY OF BIG DATA INTO HEALTHCARE

Big data in healthcare is the massive amount of data amassed from various sources like EHR, medical devices and wearables, medical imaging etc. It has 3 basic characteristics that differentiate it from health data used for decision making in healthcare: The extraordinary volume and a high velocity and its structural variability.

There are few main factors that makes Big Data in enticing the authorities and encouraging its usage at a larger level are:

The U.S. National Institutes of Health (NIH) has partnered with many hospitals and universities to form the Undiagnosed Disease Network, which collects data on super-rare conditions (, for which every patient record is important to researchers.
Optum Labs, U.S. research collaborative, collected EHRs of over 30 million patients to create a database for predictive analytics tools to improve how healthcare is delivered.
According to the Network for Excellence in Health Innovation, prescription errors amount USD 21 billion per year, leading to 7,000 deaths. Medware, an Israeli startup has partnered with healthcare organizations to use their decision support tool that uses big data to detect prescription errors before they happen.

Restraint:

LESS NUMBER OF SKILLED PERSONNEL

Due to the fast growth of the technology and it's entry in healthcare along with its growing adoption by healthcare workers, it is on an uphill rise. Bringing analytics and big data into healthcare is time saving, cost efficient and easy but there is a dire need to get skilled personnel to handle it because managing huge amount of confidential data comes with a need of certain skill and efficiency.

Since health data of a patient is confidential and should not have errors, it is important to train people according to the constantly moving standard of care. If the data of a patient is entered wrongly, it can impact the whole diagnosis and the future treatment plans which can further have dire consequences which can result to be fatal as well.

OPPORTUNITIES:

INCREASE IN CLOUD BASED ANALYTICS

Though the use of cloud based analytics is slow at present, it is about to rise in the coming years. There are various powerful reasons for the shift to cloud based analytics that makes it ideal for usage in healthcare like scalable data storage, scalable computing power and machine-learning abilities. Also, cloud based analytics provides cyber security that is otherwise a little difficult to devote to.

The reason for the increase in cloud analytics is:

Healthcare has the ability of generating data from patient data to image and video, implying that cloud providers have the ability to scale data storage. To reduce extra investment in hardware and software, cloud analytics companies use pay-as-you-go model
Cloud computing has become an important part of medical field, so much so that, it might help transform healthcare to share information of the patient among doctors for urgent cases.

CHALLENGES:�

ISSUES IN DATA ACCURACY AND CONSISTENCY

As the use of integrated analytics platforms grows in healthcare, the data collection and export process have major loopholes and inconsistencies. The general understanding of what is important, what to measure, how and when to measure it and the goals to target keeps changing.

Some of the errors and inconsistencies in data are:

Generic diagnosis codes entered quickly or out-of-habit instead of more specific and actionable diagnosis codes appropriate to the patient
Inaccurate patient identifiers, such as a missing social security number, misspelled name, incorrect sex, or swapped date of birth.
Inconsistent entry of standard codes, such as National Drug Catalog (NDC) for drugs, disrupting bulk analysis.

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Market Trends

On the basis of type, the market is segmented into Prescriptive Analytics, Predictive Analytics and Descriptive Analytics

On the basis of Component, the market is segmented into Services, Software, and Hardware. In 2018, Software segment is growing at a Highest CAGR.

Segmentation:�Global Healthcare Analytics Market

The Global Healthcare Analytics Market is segmented into five notable segments such as Type, Component, Delivery Model, Application and End User

On the basis of type, the market is segmented into predictive analytics, descriptive analytics and prescriptive analytics.Prescriptive analytics segment is growing at the highest CAGR and expected in the forecast period of 2019 to 2026.
In 2018 , McKesson launched Health Mart Atlas, which is the largest network of high-performing community pharmacies dedicated to delivering high quality care with a personal touch

On the basis of component, the market is segmented into software, hardware and services. The services segment is sub-segmented into support services and business analytics services.Software segment is estimated to grow at the highest CAGR in the forecast period of 2019 to 2026.

In 2018, McKesson acquired RxCrossroads . With this acquisition McKesson has become a partner with pharmaceutical manufacturers, providers, pharmacies, governments and other organizations in healthcare to help provide medicines, medical products and healthcare services to the patients.
On the basis of delivery model, the market is segmented into on-demand and on-premise.On-demand segment is growing at the highest CAGR of in the forecast period of 2019 to 2026.

In 2018, EPSi, Allscripts flagship budgeting, long-range planning, cost accounting and financial decision support platform, announced a partnership with MPA Healthcare Solutions.

On the basis of application, the market is segmented into clinical analytics, financial analytics, operational and administrative analytics and population health analytics. The clinical analytics segment is sub-segmented into quality improvement and clinical benchmarking, clinical decision support, regulatory reporting and compliance, comparative analytics/ effectiveness and precision health. The financial analytics segment is sub-segmented into claims processing, revenue cycle management (RCM), payment integrity and fraud, waste, and abuse (FWA) and risk adjustment and risk assessment. The operational and administrative analytics segment is sub-segmented into supply chain analytics, workforce analytics, enterprise performance, supply chain analytics, market intelligence, research analytics and strategic analytics. The population health analytics segment is sub-segmented into population risk management, population care management, patient engagement, clinical outcome management and activity-based costing.Population health analytics segment is growing at the highest CAGR in the forecast period of 2019 to 2026.

In 2018, OptumServe, the federal government health services business of Optum, was recently selected to continue to provide health services to participants in two federal health programs, building on years of successful service to first responders and the U.S. Armed Forces.

On the basis of end user, the market is segmented into healthcare payers, healthcare providers and ACOS, HIES, MCOS, and TPAS. The healthcare payers segment is sub-segmented into government agencies, private insurance companies and employers and private exchanges. The healthcare providers segment is sub-segmented into post-acute care organizations, hospitals, physician practices, and IDNS and ambulatory settings.Healthcare Payers segment is growing at the highest CAGR in the forecast period of 2019 to 2026.
In 2018, Cerner began an EHR implementation at the five hospitals and 50 primary and specialty care clinics part of University of Missouri (MU) Health Care in Columbia.

Product Launch:

In 2018, Medtronic plc and its strategic technology partner, IBM Watson Health, announced commercial availability of the Sugar.IQ smart diabetes assistant, a first-of-its-kind intelligent app designed to simplify and improve daily diabetes management

In 2018, SAS for Containers was launched. This will help IBM Watson Health to expand their product portfolio and become a strong market player.
In 2018, ExpressCoverage has been launched by McKesson Specialty Health and CoverMyMeds (divisions of McKesson Corporation). This is an integrated eServices platform designed to improve the patient care journey. ExpressCoverage is a new and powerful patient provision platform that will help consumers to connect patients, providers, payers and the life science industry to facilitate patient access and adherence for improved outcomes.

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