3:00-4:00 pm
Room: 225 AB North

'Are We in the Green?' and Other Adventures in Missing the Point
Presenter: Stephen Durkota, MSHI RN CPHQ

The session is intended to provide a case study of a number of recent efforts that Piedmont Healthcare has found to be ineffective in actually accomplishing the intended goals despite several process indicators being 'in the green'. The session provide an explanation of the life cycle of a performance measure and the key lessons learned from our "failures". Many organizations fail to recognize the enormous cost of building and maintaining process measures. This presentation will demonstrate what happens when nothing is in place to measure our measures and provide practical steps for recognizing which measures are wasting time and resources. It will also demonstrate how we quantified the true effectiveness of initiatives such as our CAUTI and CLABSI bundles and provide a model for ensuring every performance measures' "juice" is worth the "squeeze".

Learning Objectives:

  • Learn the importance of treating data as an asset
  • Learn about the life cycle of a performance measure. They will be given a methodology for identifying which measures aren't truly effective. Statistical methods for assessing independence will be discussed
  • Leave with a practical model for creating new process measures, quantifying their effectiveness and knowing when it's time to "pull the plug"

In his role as a Quality Safety Specialist, Stephen Durkota strives to bridge the technical and clinical divide by developing tools and strategies that provide clinicians with the information they need to drive improvements in patient care. As a registered nurse, he works closely with clinicians to understand their needs and workflow. As an informaticist, Durkota helps develop sustainable tools and processes to answer questions from data. He is uniquely qualified to present this information to a NAHQ audience because he can speak both to the clinicians and the data-oriented process engineers in the room.

Audience Level: CPHQ/Mid
Topic: Health Data Analytics
Date: September 16