Publication Date

Summer 8-2-2022

Project Category

Patient Safety and Quality Improvement (PSQI)

Faculty Mentor

Scott Sadler, MD

Document Type



An EMR, electronic medical record, system refers to the software widely adopted by medical practitioners to reduce the use of hard-copy files, and improve the documentation, storage, and retrieval of patient information. Some EMR systems can generate automatic alerts reminding providers when patients are due for certain preventive services or meet the criteria for various screening measures. Epic, one of the leading EMR systems in use today, contains this additional feature. The screening recommendations built into Epic are derived from a committee of USPSTF, U.S. Preventive Services Task Force, medical experts whose focus is to improve patient health across the nation. In September of 2021, the University of Tennessee-Family Medicine Jackson clinic switched from using the Centricity EMR to Epic EMR. The primary goal of this study was to measure whether there is any quantifiable improvement in USPSTF screening rates after implementing the Epic EMR, which contains the notifications to prevent lapses in patient care.

For each EMR, 100 patients were selected at random including those greater than 44 years of age and less than 65 years of age. This study involved checking whether patients were up-to-date on thirteen potential USPSTF screening measures and recording the data in the SPSS statistical software program. Chi-square analysis comparing the data across both Centricity and Epic, revealed no statistical significance between screening rates. However, when accounting for sex (male vs. female) across both EMRs, women in the study had 16% more drug screening, 3% more tobacco screening, and 18% more statin use in comparison to men. Furthermore, statistical significance was found when comparing race (black vs. white). For example, black patients had 10% more syphilis screening and 33% more STD screening, whereas white patients had 28% more lung cancer screening across both EMR systems.

Although reassuring to find no statistical significance when comparing screening rates across both EMRs, conclusions to explain the results for specific screening measures pertaining to race and sex cannot be drawn based on the data at this time. Future research analyzing external variables such as patient compliance, provider biases, and population risk, may be useful in providing further insight to explain the statistical significance of this data.