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Improving IV Insulin Administration in a Community Hospital
Published on: June 11, 2012
Using online and offline change models to improve ICU access and revenues
P J Pronovost1, L Morlock, R O Davis
1Department of Anesthesiology/Critical Care Medicine, Johns Hopkins Hospital, Baltimore, MD 21287-7294, USA. ppronovo@jhmi.edu
Background:
Hospital operational problems that span departments often present formidable challenges because they involve both processes and organizational relationships. Many improvement efforts fail because of relationship issues rather than a lack of understanding of system processes. Reflection on a recent change initiative led to the development of an integrated change model that includes both online and offline components. The online component draws on performance improvement models that provide concepts and tools for use in team meetings to improve processes. The offline component borrows from an earlier tradition of change management that offers guidelines for individuals or teams desiring to be change agents.
Methods:
The integrated change model was applied in 1997 at The Johns Hopkins Hospital, Baltimore, to reduce ambulance bypass hours, a chronic problem resulting in $6.7 million in lost revenue annually. The goal was to reduce red alert hours per month by 50%. Three Plan-Do-Study-Act (PDSA) cycles were implemented to test change concepts.
Results:
There was a significant reduction in red alert hours after the change initiative, with an estimated $6 million in additional hospital revenue.
Discussion:
The integrated change model may serve as a prototype for improving complex problems in which improving organizational relationships may be as difficult as improving processes and is likely to require a significant amount of work offline. For example, this approach may be particularly helpful for improving processes that span departments or functional units such as reducing cycle times for admissions, first-dose medications, as well as in building and improving integrated delivery systems. The model awaits further testing and evolution.
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