Clinical Quality Excellence in Anesthesia Management




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The transition to outcomes-based payment models has made data capture an important function. This is particularly true of anesthesia, as its quality affects every area of the surgical suite. One of the risks involved in data collection is that the massive quantity of data can overshadow its intended value – immediate improvement of perioperative performance.

What began as simple recordkeeping has developed into decision-making and analytics, with tools and technology for predictive modeling. The key is extracting the right data.

This report will answer your most pressing questions:

  • How do I overcome the biggest challenges in data collection?
  • How can I identify the most important, actionable data?
  • How can I analyze and use that data to improve performance?
  • How can I create a “culture of quality” among my OR team?

Download this valuable guide today and learn to identify actionable data for continuous performance improvement.

“While standardized data collection and new analytical methods are critical to the big data movement, practical application will be key to its success.”

“Why Health Care May Finally Be Ready for Big Data”
Harvard Business Review:
Information & Technology
December 3, 2014

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