1. Internship Abstract
Title: Modified Early Warning Score (MEWS) Analysis
Name: Jacob Persily
Preceptors: Dr. Rajiv Arya, Vice President of Quality and Patient Safety
Agency: Robert Wood Johnson University Hospital
Purpose: To analyze Modified Early Warning Score (MEWS) Data for use in discharge program
planning
Significance: The Modified Early Warning Score is a measure developed in the late 1990s, which can,
with a significant degree of accuracy,predict the likelihood of a patient passing away in the next 48
hours. These statistics are calculated based on vital sign data, and MEWS is becoming a built-in function
in Electronic Medical Record systems.Traditionally, the score has been used to aid resuscitation. Under
the Affordable Care Act,hospitals assume economic risk for Medicare readmissions within 30 days of
discharge, and MEWS score data may offer a new way to assist in discharge planning for these patients
and to provide appropriate services for patients who need them.
Method/Approach: Each Week,AllScripts SCM, the EMR product used by Robert Wood Johnson
University Hospital, produces a spreadsheet with various patient information and each MEWS score
calculated for each discharged or expired patient in his or her last three days in the hospital. Each week,
the new data,between 10,000 and 15,000 data points, are added to a master spreadsheet,currently at
about 250,000 data points. Pivot tables are then utilized to determine the maximum MEWS score
recorded in the last three days of hospitalization for each patient.
Outcomes: Out of the 186 days of MEWS data currently available, dating September 28, 2015 to April 1,
2016, 10,007 patients have been discharged from Robert Wood Johnson University Hospital, 9,820 alive,
and 187 expired. These data points are analyzed to find the mortality rate by MEWS Score. Of the patient
population, for patients with a MEWS Score of 6 (n=89), the mortality rate is 33.7%. Of the patient
population, for patients with a MEWS Score of 7 (n=27), the mortality rate is 40.7%. Of the patient
population, for patients with a MEWS Score of 8 (n=12), the mortality rate is 66.7%. The data are then
used, in conjunction with Medicare penalty readmission data over the same time period, to determine
gaps in post-discharge services,like home healthcare, for various penalty diagnoses.
Evaluation: Though this project is still in the data scoping phase, evaluation, at present, is conducted,
through weekly data analysis, to note if there are any drastic changes in the results when an additional
week’s data is added. Once changes are implemented, a data-drive process evaluation tool will be
developed, to determine if the utilization of MEWS score in discharge planning is, in reality, yielding a
decrease in Medicare penalty readmissions.