Above PAR Care: Implementation of a Failure to Rescue Strategy

Purpose:
Integrating data into a cohesive picture of the patient is an elusive skill. Recognition and responding to a patient deterioration that may lead to adverse event can be intimidating, for the novice or experienced nurse. Can a structured approach preemptively prevent adverse events?

Background/Significance:
Failure to rescue is considered a nurse-sensitive indicator related to the quality of nursing care. Recognition and prevention of an adverse event influences mortality rates. Mortality rates directly reflect the quality of care and patient outcomes. There is a need for ongoing investigation into the causes of failure to rescue events to develop empirically sound interventions. (Schmidt, 2007). Any process that affects this continuum improves hospital quality and patient outcomes.

Methods:
Utilizing data already being collected, a clinical prediction rule (PAR score) rates the level of patient stability. A specific score mandates an evaluation and escalation of care pathways. The PAR pilot study utilized a quasi-experimental design. The dependent variable is the number of adverse events per 1000 in-patient days. The independent variable is the PAR assessment score/tool. All patients admitted to the PCU were included in the study. The PAR scoring tool was not implemented on any other unit within the facility. The only identified factor influencing the recognized number of adverse events was the PAR scoring tool. IRB approval was obtained prior to initiation of the pilot study.

Results:
The dependent variable, adverse event (RRT, Code Blues,and deaths) was calculated per 1000 patient days. A series of binomial exact tests were computed on the difference between the mean number of events that occurred before and after the PAR scoring system began. The mean number of RRTs per 1000 patient days significantly dropped in the eight months that the PAR scoring system has been in use. The mean number of Code Blues reduced significantly and the number of deaths which occurred in people who had an RRT and/or Code Blue and who met the inclusion criteria dropped significantly.

Conclusions and Implications for Practice:
Utilization of a clinical prediction rule that mandates a specific course of action and approach to patient deterioration was successful. Computerized documentation automatically generated the score, thus not increasing the work load of the nurse, but allowing the nurse to work smarter, not harder.