Recipe for Early Recognition in Changing Patient Condition

Purpose:
Imagine an EMR tool with 22 real time clinical triggers guiding patient's level of care. Our recipe for early recognition has developed nurse's critical thinking to recognize patients with declining conditions. Providers can see patients of the highest priority in one color coded glance.

Relevance/Significance:
The recipe for early warning system has shown to develop nurse's critical thinking skills and to recognize patients with deteriorating conditions earlier. This tool brings real time auto-configured values into the ever changing patient condition from EMR documentation, re- calculating each time a new data input is entered. No longer are we taken unaware but now have a sense of which of our patients are high risk to deteriorate in condition and which are improving.

Strategy and Implementation:
Imagine an EMR tool that can guide patient priority of illness or level of care? How many times have we heard , “ I did not realize he was getting that bad?” or a failure to rescue. Bellin has been taking the MEWS to a whole new level and the ability of the healthcare team to identify early warning signs of patients deteriorating conditions through automated electronic medical record data entry. The IS department collaborating with the ICU CNS and house SWAT team have built a system that incorporates EMR data from vital signs flow-sheet, nursing assessment rows, and laboratory values. The next step was to use the early warning system to show how interventions were improving or not improving our patients. We added a color coded row for MEWS change score and report with real time calculations to show increased, declining, or no change in patient condition making it visible to the multidisciplinary players.

Evaluation:
Our recipe started March 1, 2014 with our house supervisors. Prior to that time we had 4 code blues in January and 5 in February. From March 1 through July 31 we had 1 code blue in house on the acute care floors and ICU combined. Sepsis mortality went from 38% to 14.2 %. We have decreased our readmission rates, length of stay in ICU, and improved our discharge process.

Implications for Practice:
Identify how data entered in the EMR record can develop a recipe for an early warning tool identifying patient condition changes. Analyze the MEWS tool to decreasing code blue events throughout the inpatient hospital stay. Develop your own recipe for early recognition with our data point resources.