Data in Healthcare 2018: Data Underpins the Shift to Value-Based Care Underway Across Health Systems - ResearchAndMarkets.com

The "Data in Healthcare: Underpinning the Shift to Value" report has been added to ResearchAndMarkets.com's offering.

Data underpins the shift to value-based care underway across health systems.

The many kinds of health and health-relevant data vary in complexity, strengths and weaknesses, and are typically owned by different stakeholders. Provider-run electronic health records lie at the heart of the health data universe, yet structured payer claims data is also key to the shift to value-based care. Genomics data and digital-technology-derived data sources are proliferating.

The demand for high-quality data to enable the shift to value-based care has created a vibrant data market, which has attracted a growing range of data crunchers and solution providers, both large established groups and small start-ups. There is now more data, and better data, than ever before. Interoperability is improving slowly, and efforts are underway to combine disparate sources such as clinical and claims data, thereby providing a full picture of the patient care journey. Pharma firms are tapping into multiple data types to improve R&D efficiency and optimize market access.

Challenges facing the data market lie around data collection, quality, sharing, standards, governance, security and access, privacy, validation, application, and around the mindset shift required within provider and pharma organizations in particular, to take full advantage of the growing data-driven insights available.

Population Health Management: Using Data To Control Costs And Manage Disease

Much of the health data being collected is intended to help improve care and outcomes, be it through better, more targeted disease treatment and management, more effective prevention, and/or improved cost controls. Pharma is using better data - mostly genomic sequencing data - to develop more targeted treatments for individuals. Providers and payers are using a far broader range of data and sophisticated analytics tools to more effectively manage the health of their covered populations - known as population health management. Key to that is risk-stratification - figuring out which are the 20% of patients at high risk of adverse events. The more integrated and holistic the data available to tap into, the more accurate the risk-stratification will be - and the more appropriately interventions can be targeted to help manage or reduce that risk.

Hurdles to population health management include variable pharmaceutical pricing; the challenge, for physicians and other providers, of actually using data to inform decision-making; implementing the shift from a treatment toward a prevention mentality; and the controversy around using social and behavioral data in a healthcare setting.

Pharmaceutical firms must develop broader data-focused expertise across all of their functions. Data is increasingly part of an overall, corporate-wide strategy, underpinned by significant investment and new kinds of deals to generate and access richer data - and/or make better use of existing data. A new role - that of the data scientist - has evolved: an expert in extracting insights from data and in building predictive models. Focus remains critical though, as data is only useful if it answers a specific, well-articulated need.

Key Topics Covered:

EXECUTIVE SUMMARY

Mapping the health data landscape

Value-based care is changing the data landscape

Challenges facing the data market

Population health management: using data to control costs and manage disease

Hurdles to population health management

Pharma needs cross-functional data capabilities

MAPPING THE HEALTHCARE DATA LANDSCAPE

Data underpins the shift to value

A healthcare data taxonomy

Bibliography

VALUE-BASED CARE IS CHANGING THE DATA LANDSCAPE

Demand for data creates a vibrant market

Boon for data crunchers and solution providers

Bibliography

CHALLENGES FACING THE DATA MARKET

Data collection

Data quality

Data sharing

Data standards

Data governance

Data security and access

Data privacy

Data validation

Data application and the culture shift

Bibliography

POPULATION HEALTH MANAGEMENT: USING DATA TO CONTROL COSTS AND MANAGE DISEASE

Risk-stratifying patients to better manage costs and outcomes

Hurdles to population health management

Bibliography

PHARMA NEEDS CROSS-FUNCTIONAL DATA CAPABILITIES

Sharing data across the organization

Growing the data scientist

Data dealmaking

Asking the right questions

Data-driven shift in healthcare is underway

Bibliography

APPENDIX

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