9 Steps to Using Big Data

Hospitals and health systems are increasingly looking to big data to support accountable care models and aid in restructuring care delivery models in advance of bundled payments.

The Institute for Health Technology Transformation recently released a report highlighting nine steps to develop an analytics framework:

  1. Form a data governance committee
  2. Distinguish between data and "actionable" data
  3. Identify the single source of data
  4. Establish staff and an analytics team
  5. Identify data sources today and determine what data to move to the single source for analysis
  6. Pick a project and focus on data quality and timeliness that work on a particular disease state
  7. Determine benchmarks
  8. Identify a sample population then measure and adjust around individual patient outcomes
  9. Measure patient behavior change and impact on quality and cost

The report recognizes, however, about 80 percent of hospitals' data is considered unstructured and difficult to analyze, as physicians tend to dictate their reports and progress notes. Additionally, just 30 percent of hospitals used a clinical data warehouse or mining solution. Of hospitals with fewer than 200 beds, only 20 percent had such a data solution.

More Articles on Big Data:

Survey: 80% of CIOs Want to Use Big Data, Though 84% Said Big Data Use Presents Challenges
Tech Terms Cheat Sheet: The Health IT Vocabulary Non-CIOs Need to Know
NIH to Grant $24M per Year for Biomedical Data Analysis

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