Jennifer Bresnick: 10 Challenges Providers Face When Dealing With Big Data Analytics in Healthcare

1. Data Capturing - that is clean, complete, accurate, and formatted correctly for use in multiple systems is an ongoing battle for organizations
2. Data Cleaning – also known as cleansing or scrubbing – ensures that datasets are accurate, correct, consistent, relevant, and not corrupted in any way
3. Data Storage - Front-line clinicians rarely think about where their data is being stored, but it’s a critical cost, security, and performance issue for the IT department
4. Data Security - is the number one priority for healthcare organizations, especially in the wake of a rapid-fire series of high profile breaches, hackings, and ransomware episodes
5. Stewardship - Understanding when the data was created, by whom, and for what purpose – as well as who has previously used the data, why, how, and when
6. Querying - Robust metadata and strong stewardship protocols also make it easier for organizations to query their data and get the answers that they are expecting
7. Reporting - After providers have nailed down the query process, they must generate a report that is clear, concise, and accessible to the target audience
8. Visualization - At the point of care, a clean and engaging data visualization can make it much easier for a clinician to absorb information and use it appropriately
9. Updating - Healthcare data is not static, and most elements will require relatively frequent updates in order to remain current and relevant
10. Sharing - data with external partners is essential, especially as the industry moves towards population health management and value-based care

Source: HealthIT Analytics
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