US Healthcare Data Analytics Market, Forecast to 2020

How to Design, Implement, and Govern Value-based Healthcare Analytics?


Introduction:
A healthcare data analytics platform can be defined as a single, interoperable system that uses retrospective data to produce business intelligence reports that quantify enterprise-level financial and operational performance, as well as, disparate clinical data to enable predictive, real-time reporting of patient outcomes against every episode of care delivered.

Research Overview:
This study defines and describes the US healthcare data analytics market. It covers factors driving the need to adopt healthcare data analytics technologies that identify care leakages, automate patient-risk assessment, facilitate targeted intervention, support proactive member outreach, and benchmark enterprise-level clinical, financial, and operational utilizations.

Additionally, the report will:
•     Analyze key market drivers and restraints impacting end-user adoption
•     Evaluate existing and emerging healthcare business models centered around data analytics
•     Highlight best-practices in the areas of analytics budgeting, deployment, and governance
•     Shortlist vendors that can provide best-in class solutions
•     Forecast the gross revenue potential of the US healthcare analytics market over the next 5 years

This study is segmented into three major analytics service segments as follows:
•     Clinical Analytics
•     Financial Analytics
•     Operational Analytics

In terms of end-user adoption, this study classifies the buyer market in two broad categories:
•     Provider Organizations     
o     Hospitals
o     Physician Practices
• Payer Organizations
o     Commercial and public payers including payer-viders

Finally, the vendor market is stratified based on two key parameters:
•     Product Relevance
o     Enterprise Platform
o     EMR Integrated Platform
o     Modular Suite of Solutions
o     Web-based Solutions
•     Business Application Relevance
o     Clinical Solutions
o     Financial Solutions
o     Operational Solutions

Healthcare analytics is widely regarded as a key enabler of value-based care. Robust usage of this technology allows health systems to practice data-driven decision making, which improves operational efficiencies, eliminates preventable costs, and streamlines clinical effectiveness. However, analytics adoption among US healthcare payers and providers is not consistent; healthcare organizations embrace a diverse array of deployment strategies that demonstrate different implementation maturity levels. For example, some health systems might utilize advanced enterprise data processing architecture to derive patient-specific insights for every episode of care, whereas others still rely on basic reporting capabilities of legacy Business Intelligence (BI) tools. This year, the cumulative maturity of the US analytics market is likely to be streamlined, mainly due to timely intervention from CMS.

In late 2016, CMS launched the final rules for bundled payment programs, bringing great joy to analytics vendors that now anticipate higher traction from payers and providers. On the contrary, the end-user segment is still apprehensive about the feasibility of this new rule, which mandates that US providers in some regions accept financial accountability for the quality and cost of every episode of cardiac and orthopedic care. The scope of the new rule combines all patients being treated and all patients during the 90-day post-discharge phase; thus, encouraging effective care coordination between acute care hospitals, physician practices, and post acute-care providers. Providers managing to demonstrate episodic cost utilization below the CMS benchmark are likely to be incentivized and others are likely to be penalized.

Regardless of this initiative’s longevity amid political intervention and provider outburst, in 2017, healthcare organizations are likely to accelerate adoption of best-in-class analytics solutions, mainly for quality reporting, which is an integral component of value-based care and population health management. Providers are most receptive to using analytics solutions to identify, assess, and benchmark cost trends by payer, patient, and physician mix, whereas payers are likely to opt for these solutions to identify quality-adjusted target prices for every episode of care.

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Introduction:
A healthcare data analytics platform can be defined as a single, interoperable system that uses retrospective data to produce business intelligence reports that quantify enterprise-level financial and operational performance, as well as, disparate clinical data to enable predictive, real-time reporting of patient outcomes against every episode of care delivered.

Research Overview:
This study defines and describes the US healthcare data analytics market. It covers factors driving the need to adopt healthcare data analytics technologies that identify care leakages, automate patient-risk assessment, facilitate targeted intervention, support proactive member outreach, and benchmark enterprise-level clinical, financial, and operational utilizations.

Additionally, the report will:
• Analyze key market drivers and restraints impacting end-user adoption
• Evaluate existing and emerging healthcare business models centered around data analytics
• Highlight best-practices in the areas of analytics budgeting, deployment, and governance
• Shortlist vendors that can provide best-in class solutions
• Forecast the gross revenue potential of the US healthcare analytics market over the next 5 years

This study is segmented into three major analytics service segments as follows:
• Clinical Analytics
• Financial Analytics
• Operational Analytics

In terms of end-user adoption, this study classifies the buyer market in two broad categories:
• Provider Organizations
o Hospitals
o Physician Practices
• Payer Organizations
o Commercial and public payers including payer-viders

Finally, the vendor market is stratified based on two key parameters:
• Product Relevance
o Enterprise Platform
o EMR Integrated Platform
o Modular Suite of Solutions
o Web-based Solutions
• Business Application Relevance
o Clinical Solutions
o Financial Solutions
o Operational Solutions

Healthcare analytics is widely re
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Table of Contents

1. Executive Summary
Key Findings
Executive Summary
End Users
Hospitals
Physician Practices
Payers
Service Segments
Clinical Analytics
Financial Analytics
Operational Analytics
Scope and Segmentation
Market Engineering Measurements
CEO’s Perspective
Executive Summary—3 Big Predictions
2. Market Overview
Market Background
US Healthcare Data Analytics—Strategic Imperatives
Market Scope and Definition for Healthcare Data Analytics
Customer Segments
Provider Organizations
Payer Organizations
Service Segments
Clinical Solutions
Financial Solutions
Operational Solutions
Deployment Models
Enterprise Platforms
Outsourced Capabilities
Plug-in based Applications
EMR Integrated
Healthcare Data Analytics—Service Segmentation
Healthcare Data Analytics—Key Components
Regulatory Initiatives Driving Analytics Adoption
Healthcare Data Analytics Deployment Outlook—Total US Market
Healthcare Data Analytics Deployment Outlook—Health Plans
Healthcare Data Analytics Deployment Outlook—Hospitals
Healthcare Data Analytics Deployment Outlook—Physician Practices
Healthcare Data Analytics—Evolving Service Propositions
Business Model Stratification and Assessment
Analytics’ Role in PHM
3. Drivers and Restraints—Total Healthcare Data Analytics Market
Market Drivers
Massive cost burden of healthcare delivery drives the need for better prediction and assessment of population health, specially for chronic-care patients who contribute the highest cost levels
The rise of value-, quality-, or risk-driven reimbursement programs fosters the need to pursue evidence-based care delivery through effective capturing, storing, and processing of disparate patient data
Providers acknowledge the benefit of clinical, operational, and financial reporting capabilities amidst growing need to manage, monitor, and benchmark health or business outcomes at a population and patient level
In the PHM era, health systems strive to utilize predictive or precision analytics applications to support best-in class research and visionary innovations
Market Restraints
Poor interoperability between healthcare IT solutions restricts health systems to effectively capture, harmonize, and normalize disparate patient data, which is the primary input of any analytics engine
Lack of investment capability compels health systems to rely on basic BI reporting tools that fail to optimally generate evidence-based clinical workflows and benchmark patient outcomes at a population level
Cultural incompatibility related to usage resistance, lack of knowledge, and fragmented governance leads to slow adoption of analytics solutions
Industry standards, including regulatory provisions, emphasize on basic analytics capabilities
4. Segment Level Analysis—Clinical, Financial, and Operational Analytics Solutions
Clinical Analytics—Business Strategy Assessment
Clinical Analytics—Supply Demand Dynamics of Key Service Components
Financial Analytics—Business Strategy Assessment
Financial Analytics—Supply Demand Dynamics of Key Service Components
Operational Analytics—Business Strategy Assessment
Operational Analytics—Supply Demand Dynamics of Key Service Components
5. Forecasts and Trends—Total Healthcare Data Analytics Market
Market Engineering Measurements
Revenue Forecast
Percent Revenue Forecast by Customer Segment
Revenue Forecast by Customer Segment
Market Engineering Measurements—Hospitals Segment
Revenue Forecast—Hospitals Segment
Market Engineering Measurements—Payers Segment
Revenue Forecast—Payers Segment
Market Engineering Measurements—Physician Practices Segment
Revenue Forecast—Physician Practices Segment
6. Demand Analysis—Hospitals, Physician Practices and Payers
Penetration Analysis—Hospitals
Penetration Analysis—Physician Practices
Penetration Analysis—Payers
7. Competitive Environment
Market Gaps in the United States
Competitive Market Structure
8. Pricing Analysis
Pricing Maturity—US Healthcare Data Analytics
9. Key Companies to Watch—Business Model Relevancy & Core Service Propositions
Assessment of Select Healthcare Data Analytics Vendors
10. Growth Opportunity Assessment and Companies to Action
5 Major Growth Opportunities—Healthcare Data Analytics
Population Health Management
Clinical Surveillance and Decision Support
Revenue Cycle Management
Work Force Management
Supply Chain Management
Ecosystem-level Partnerships Can Leverage Existing and Potential Growth Opportunities
Strategic Imperatives for Success and Growth
Transformation in Healthcare Data Analytics Industry Ecosystem, US, 2017
11. Future Perspectives
3 Big Predictions
The Last Word—Discussion
Legal Disclaimer
12. Appendix
Market Engineering Methodology

Infographic



List of Figures & Charts

1. Healthcare Data Analytics Market: Market Assessment of Key End Users, US, 2016
2. Healthcare Data Analytics Market: Market Assessment of Key Service Components, US, 2016
3. Total Healthcare Data Analytics Market: Key Market Drivers, US, 2016–2020
4. Total Healthcare Data Analytics Market: Key Market Restraints, US, 2016–2020
5. Total Healthcare Data Analytics Market: Market Engineering Measurements, US, 2015
6. Total Healthcare Data Analytics Market: Revenue Forecast by Customer Segment, US, 2015–2020
7. Hospitals Segment: Market Engineering Measurements, US, 2015–2020
8. Payers Segment: Market Engineering Measurements, US, 2015–2020
9. Physician Practices Segment: Market Engineering Measurements, US, 2015
10. Total Healthcare Data Analytics Market: Competitive Market Structure, US, 2016
11. Healthcare Data Analytics Market: Pricing Model Assessment, US, 2016–2020
12. Healthcare Data Analytics Market: Vendor Landscape Assessment, US, 2016

1. Healthcare Data Analytics Market: Deployment Outlook, US, 2016
2. Healthcare Data Analytics Market: Vendor Engagement Landscape, US, 2016
3. Healthcare Data Analytics Market: Partnership Outlook, US, 2016
4. Total Healthcare Data Analytics Market: Market Engineering Measurements, US, 2015
5. Healthcare Data Analytics Market: Customer Segments, US, 2016
6. Healthcare Data Analytics Market: Service Segments, US, 2016
7. Healthcare Data Analytics Market: Deployment Models, US, 2016
8. Healthcare Data Analytics Market: Service Segmentation, US, 2016
9. Healthcare Data Analytics Market: Key Service Components, US, 2016
10. Healthcare Data Analytics Market: Evolving Service Composition, US, 2015–2020
11. Healthcare Data Analytics Market: Traditional and Emerging Product Packages, US, 2015–2020
12. Healthcare Data Analytics Market: Business Model Assessment, US, 2015–2020
13. Healthcare Data Analytics Market: Analyst Perspective—Business Strategy Assessment, US, 2016–2020
14. Healthcare Data Analytics: Supply Demand Dynamics of Key Service Components—Clinical Analytics, US, 2016
15. Healthcare Data Analytics Market: Analyst Perspective—Business Strategy Assessment, US, 2016–2020
16. Healthcare Data Analytics: Supply Demand Dynamics of Key Service Components—Financial Analytics, US, 2016
17. Healthcare Data Analytics Market: Analyst Perspective—Business Strategy Assessment, US, 2016–2020
18. Healthcare Data Analytics: Supply Demand Dynamics of Key Service Components—Operational Analytics, US, 2016
19. Total Healthcare Data Analytics Market: Revenue Forecast, US, 2015–2020
20. Healthcare Data Analytics Market: Market Summary, US, 2015–2020
21. Total Healthcare Data Analytics Market: Percent Revenue Forecast by Customer Segment, US, 2015–2020
22. Hospitals Segment: Revenue Forecast, US, 2015–2020
23. Payer Segment: Revenue Forecast, US, 2015–2020
24. Physician Practices Segment: Revenue Forecast, US, 2015–2020
25. Hospitals Segment: Penetration Analysis, US, 2016
26. Physician Practices Segment: Penetration Analysis, US, 2016
27. Payers Segment: Penetration Analysis, US, 2016
28. Healthcare Data Analytics Market: Key Success Factors, US, 2016–2020



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