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3 Ways Health Data Engineering is Important in the Age of Healthcare Consolidation

Large physician medical practices, hospital and large health systems are continuing to consolidate and merge in the US. The advantage is a greater ability for collective bargaining advantage with equipment and technology purchases and an opportunity to share clinical services at a broader scale. As the consolidation continues, the demand for better connected care through intelligent interoperable solutions has increased exponentially. This is where enterprise health data engineering has moved to the top of the priority list.

Learn more ways to expand the reach of Health Systems here.

Here are the 3 ways an enterprise data optimization solution can help empower these healthcare organizations.

1.  Design an intelligent enterprise database management

As data sources and types proliferate it becomes increasingly difficult to secure and manage the flow of information. While leveraging a variety of open source and commercial tools these consolidated healthcare organizations need deep expertise and proven strategies to enable comprehensive, scalable solutions, while maintaining the health of their patient population. Data security, scalability, normalization, and integration are essential requirements along with a comprehensive, intuitive enterprise master patient index.

2. Use artificial Intelligence empowered solutions to maximize meaningful data sharing

Keen insights and visualization with a strong business strategy are key to a sustainable healthcare data enterprise. Artificial intelligence can assist in the collection, integration, analysis, and sharing of actionable healthcare information for better decision making across the care continuum. AI can identity key data and extract insights from multiple data sources quickly and easily. The right AI empowered data management infrastructure can turn data into actionable intelligence that ultimately results in digital healthcare transformation.

3. Connect disparate and data formats and technology formats

A well-engineered healthcare data enterprise enables secure access, exchange, integration, and collaborative use of health data in an orchestrated manner, within and across organizational and care community boundaries. This dynamic infrastructure must provide timely and consistent transfer of information to improve the health of individuals and patient populations.

Flexible architectures, application interfaces and standards must continuously enable data access and sharing. This requires normalizing data from disparate formats and technology sources and then story the data into a master patient index that connects to each stakeholder involved in the care continuum. It also requires a disruptive data engineering approach to lead the charge towards healthcare transformation.

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