Big Data Research

The Big Data arm of the Data Science section of the Center for Resuscitation Science provides data management of large datasets and performs statistical analysis including descriptive statistics, hypothesis testing, data interpretation and graphical presentation. Having both access to and the ability to analyze large datasets is essential in clinical research. A large sample size increases power to detect differences, increases the precision of results, and often increases generalizability. It also allows for research to be performed more quickly and easier detection and analysis of rare events, among other benefits. However, big data often comes with big challenges. Our team has gained experience handling these issues through multiple projects that utilize large registry data with over 100,000 patients as well as larger administrative-type data.

Examples of data sources used by the CRS:

  • Get with the Guidelines-Resuscitation Acute Respiratory Compromise, Adult, and Pediatric modules
  • The Cardiac Arrest Registry to Enhance Survival (CARES)
  • Internal administrative claims data and data from internal Hospital Data Servers
  • Cerner HealthFacts

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Improving patient lives by advancing the field of resuscitation medicine