What are some of the key concerns about the use of big data in health care and how can they be mitig

We need to solve core data fragmentation and dispersion problems for health care, as well as provide patients improved access, control and transparency for use of their personal health data.

We have seen many recent failures in attempts to integrate new technology within high-profile health care systems, and despite enormous expenditures. These failures show that successful development of new patient data systems will require the design of core new implementation and development strategies within health care systems.

Digital health innovation hubs that leverage multidisciplinary teams are a promising new strategy for successful integration of new big data systems. Innovation hubs are a way to gather the right technology experts working together to decrease barriers within the health care system.

Key Concerns:

• How data is captured (accuracy, complete and how formatted) for multiple systems

How to mitigate: Data governance and integrity expertise in health information specialists

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• Dirty data: There is concern that data will be corrupted, inconsistent.

How to mitigate: Automatic scrubbing tools with machine learning techniques

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• Data Storage: Security, cost and performance issues for IT departments. With volume, many providers are not able to manage the costs and impacts on data centers.

How to mitigate: Cloud storage, which is both nimble for disaster recovery, but also less expensive

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• Data Security: This is the #1 priority for health care organizations. Breaches, hackings and ransomware episodes, among many other threats, make data vulnerable.

How to mitigate: Simplified security procedures such as up-to-date anti-virus software, firewalls, encrypting sensitive data and other multi-factor authentication

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• Data Reporting: Data must be extracted and examined. Most of reporting in health care is external due to regulatory and quality assessment programs.

How to mitigate: Providers can use qualified registries and reporting tools built into their electronic health records.

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• Data Sharing: Fundamental differences in the way EHRs are designed and implemented can make it difficult to move data between organizations, which can leave information out that is necessary for key decisions, strategies, and patient follow-up. This ultimately affects overall outcomes.

How to mitigate: There are new tools and strategies such as public APIs and partnerships to make it easier for developers to share data accurately and securely.