Improving patient outcomes using technology to drive nurse consultation
Early warning scoring (EWS) systems collate clinical assessment parameters to predict clinical deterioration. An EWS embedded into the electronic medical record (EMR) together with two alert communication strategies improved nurse response time to clinical deterioration and reduced ICU admissions.
Relevance/Significance:
Clinical deterioration among medical-surgical patients, as reflected by unplanned transfers to the ICU, can result from missed recognition of physiological parameters. Early warning scoring systems have shown promise in promoting an early response to deterioration. While EWS alerts within the EMR decreases ICU admissions, pager alerts to ICU nurses followed by med-surg to ICU nurse collaboration can offer optimum clinical decision support for both novice and experienced nurses.
Strategy and Implementation:
A 7-item EWS was imbedded into the EMR of a community hospital as part of a clinical decision support system. Implementation across 4 medical-surgical units included an alphanumeric page to the ICU Rapid Response Team (RRT) nurse in the event that a patient's EWS was consistent with a serious state of clinical deterioration. The ICU RRT nurse reviewed the patient's EMR, contacted the patient's nurse and discussed the patient's EWS and clinical condition. The nurse-to-nurse collaboration yielded a plan for re-assessment and potential interventions.
Evaluation:
The EWS alerts together with nurse-to nurse collaboration resulted in decreasing time to re-assessment. Prior to the project, 28% of patients with serious EWS alerts were re-evaluated within 30 minutes. Three month post-implementation data revealed that nearly half (48%) of all serious EWS alerts were re-evaluated within 30 minutes. None of a sample of 84 patients with EWS>4 required ICU transfer.
Implications for Practice:
The socio-technological solution created by the combination of an EWS, the patient's nurse and an ICU nurse can influence both unplanned transfers and patient acuity at time of transfer. The combination of computer intelligence and human wisdom can mitigate clinical deterioration.