Article Text
Abstract
Objectives Medical complications that result in patient readmissions to the intensive care unit (ICU) are known to be associated with increased mortality and length of stay. Scoring systems have been used in healthcare systems for decades to objectively assess a patient’s current status and implement the appropriate interventions based on the score generated from physiologic variables that comprise each scoring system. The Modified Early Warning Score (MEWS) employs five physiologic parameters (systolic blood pressure, heart rate, respiratory rate, temperature, and level of consciousness) for scoring and has been an essential tool for the identification of deteriorating patients. The early identification of a deteriorating patient is essential to decrease ICU readmission, length of stay, and mortality. The purpose of this study was to determine if there is any association between the MEWS and medical intensive care unit (MICU) readmission within 72 hours of initial discharge.
Method This was a retrospective study that used patient data spanning a 40-day period from September to November 2016. After ethics board approval, we reviewed the electronic health records (EHR) of 50 adult patients admitted to and subsequently discharged from the medical intensive care unit (MICU) of an urban academic medical center located in the Midwestern United States. We manually extracted patient demographic data including patient age, gender, weight, height, and the admitting diagnosis. Clinical variables collected include the value of each parameter of the MEWS as well as the MEWS score calculated from physiologic data entered into the EHR twelve hours, six hours, and one hour prior to MICU readmission. Additionally, Acute Physiologic Assessment and Chronic Health Evaluation II (APACHE II) score was calculated for each patient. The extracted data was recorded in REDCap, a web-based HIPAA compliant research database.
Results The median MEWS score calculated from physiologic data entered into the electronic health record (EHR) twelve and six hours prior to MICU readmission was 3.0 for patients readmitted to the ICU compared with a median MEWS score of 2.0 for their cohorts who were not readmitted. The median MEWS score one hour before MICU readmission for subjects readmitted to the MICU was 4.0 compared to a median MEWS score of 2.0 for their cohorts who were not readmitted to the MICU during that one-hour period. Mann-Whitney U test revealed that there was a significant association (P = 0.013) between MICU readmission and the MEWS score calculated one hour before ICU readmission. Additionally, logistic regression analysis showed that this MEWS score predicts MICU readmission (OR 1.8, 95% CI 1.14 to 2.72).
Conclusions The MEWS independently predicts the likelihood of MICU readmission. Since the MEWS score can be automatically generated by the EHR it is prudent for clinicians to use it for frequent monitoring of patients during the first 72 hours of their discharge from the intensive care unit.