Implicit Bias among Anesthesia Providers based on Age.

Doctoral Candidate Name: 
Mel Okuta, RN, BSN, SRNA
Program: 
Doctor of Nursing Practice
Abstract: 

Social disparities and implicit bias are detrimental to patient care and exist among providers. Research has shown that implicit bias hinders rapport between patient and provider, leading to patients becoming resistant to medical advice and treatment protocols and lead to providers to misinterpret or misunderstand patients. Therefore, it is crucial to identify levels of implicit bias among healthcare providers and the ramifications that implicit bias could induce. This quality project aims to assess and establish baseline levels of existing implicit bias among anesthesia providers in a healthcare system located in a large southeastern city.
Anesthesia providers from four hospitals were asked to complete the Harvard Implicit Bias Association test. Three hundred and seventy-four providers and thirty-two student registered nurse anesthetists received the email with instructions to complete the test. In addition, participants provided demographic information about their practice location, age, race, and anesthesia title. The results were scored using the Harvard IAT D-score ‘slight’ (.15), ‘moderate’ (.35), and ‘strong’ (.65). A total of forty-six individuals completed the survey: 26 certified registered nurse anesthetists, 18 students registered anesthetists and two anesthesiologists. There was no statistical significance at 95% confidence that showed the difference in provider bias based on race, location, or title.

Defense Date and Time: 
Friday, November 25, 2022 - 4:45pm
Defense Location: 
UNCC College of Health & Human Services – Room 406
Committee Chair's Name: 
Dr. David Langford
Committee Members: 
Dr. Dianne Earnhardt, Paula Ospina-Gómez, Dr. Susan Lynch, Dr. Zhou Job Chen. Dr. Suzanne Boyd