EHRIntelligence - Tackling Complex Data Challenges in Healthcare Analytics

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Tackling Complex Data Challenges in Healthcare Analytics

Modern data analytics tools and technologies can help organizations analyze complex data and use it to benefit the institutions as well as their patients. However, selecting and implementing these solutions requires one to understand the underlying data and processes in place. This whitepaper will present the challenge of complex data in medical organizations, and present the ways in which modern technology can solve these problems.

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Chicago, IL | June 22-23, 2017

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As a valued member of HealthITAnalytics.com register today for $249! (Save $150)
Use discount code: ANALYTICS

Featured Workshop: How Big Data Analytics Can Support Quality and Cost Improvements
Learn more about the complex process of leveraging big data analytics to produce measurable quality care improvements and cost savings. Our workshop leaders will offer tips and best practices stemming from their own experience tackling high-value use cases in the clinical environment.

Featured Speakers:
Randall S. Moore, MD, MBA, President, Mercy Virtual
Kathy Farrell MD, FAAP, Associate Medical Director of Telemedicine, Children's Mercy Hospital
Nikhyl Jhangiani MBA, MPH, Program Manager, Distance Health, Office of Clinical Transformation, Cleveland Clinic

Infographic: Quick Guide to Alternative Payment Models (APMs)

Alternative Payment Models (APMs) are the most advanced options under the Medicare Access and CHIP Reauthorization Act’s (MACRA) Quality Payment Program. APMs offer the highest incentives and could be the preferred model of the future. But APM requirements are complex — and some don’t even qualify for MACRA. Where do you stand? Here’s an overview of some of the current guidelines.

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Business Analytics and the Data Complexity Matrix

What exactly makes data complex? In the context of business analytics, there are two key drivers of data complexity:

  • The size of the data (is it millions of rows, 100’s of millions, or billion+)?
  • The number of disparate data sources (or data tables)

These elements drive complexity because the bigger the data, the more effort (cost) needed to query and store it. The more data sources (data tables) the more effort (cost) that is needed to prepare the data for analysis. The data complexity matrix describes data from both of these standpoints. Your data may be Simple, Diversified, Big, or Complex. When considering a Business Analytics program, different approaches are better suited for each data state.

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About EHRIntelligence

Electronic health record (EHR) news and product Information. Stay up to date with EHR News, ICD-10, HIE, EHR Incentive guidelines, EHR requirements, Whitepapers