Introducing Medical Students into the Emergency Department: The Impact upon Patient Satisfaction.

INTRODUCTION: Performance on patient satisfaction surveys is becoming increasingly important for practicing emergency physicians and the introduction of learners into a new clinical environment may impact such scores. This study aimed to quantify the impact of introducing fourth-year medical students on patient satisfaction in two university-affiliated community emergency departments (EDs). METHODS: Two community-based EDs in the Indiana University Health (IUH) system began hosting medical students in March 2011 and October 2013, respectively. We analyzed responses from patient satisfaction surveys at each site for seven months before and after the introduction of students. Two components of the survey, "Would you recommend this ED to your friends and family?" and "How would you rate this facility overall?" were selected for analysis, as they represent the primary questions reviewed by the Center for Medicare Services (CMS) as part of value-based purchasing. We evaluated the percentage of positive responses for adult, pediatric, and all patients combined. RESULTS: Analysis did not reveal a statistically significant difference in the percentage of positive response for the "would you recommend" question at both clinical sites with regards to the adult and pediatric subgroups, as well as the all-patient group. At one of the sites, there was significant improvement in the percentage of positive response to the "overall rating" question following the introduction of medical students when all patients were analyzed (60.3% to 68.2%, p=0.038). However, there was no statistically significant difference in the "overall rating" when the pediatric or adult subgroups were analyzed at this site and no significant difference was observed in any group at the second site. CONCLUSION: The introduction of medical students in two community-based EDs is not associated with a statistically significant difference in overall patient satisfaction, but was associated with a significant positive effect on the overall rating of the ED at one of the two clinical sites studied. Further study is needed to evaluate the effect of medical student learners upon patient satisfaction in settings outside of a single health system

Optical flow based analyses to detect emotion from human facial image data

Artificial recognition of facial expression has attracted a lot of attention in the last few years and different facial expression detection methods have been developed. The current study uses a feature point tracking technique separately applied to the five facial image regions (eyebrows, eyes and mouth) to capture basic emotions. The used dataset contains a total 60 facial images from subject's different genders and nationality not wearing glasses and/or facial hair. Results show that the used point tracking algorithm separately applied to the five facial image regions can detect emotions in image sequences. © 2010 Elsevier Ltd. All rights reserved