Abstract P6-05-52: Addressing Healthcare Gaps and Disparities in Electronic Medical Record Messages: A Quality Improvement Project Among Breast Cancer Patients
Authors: Conroy Meghan , Powell Miracle , Nagavally Sneha , Dawson Aprill , Beckius Anna , Min Heun , Sweeney Maressa , Weil Elizabeth , Hallbach Angela , Chaudhary Lubna N. , Cheng Yee Chung , Deiinger Jutta , Burfeind John , Retseck Janet , Wright Tamiah , Charlson John , Kamaraju Sailaja 
Published: March 2023

Abstract
Introduction: Despite evidence that utilization of Electronic Medical Record (EMR) messaging positively impacts patients with cancer, there is little research on who uses EMR messaging and for what purpose.
Methods: Sociodemographic and MyChart usage data was collected from Epic to identify patterns of EMR messaging by patients at an academic breast center. Study eligibility included breast cancer patients who completed a visit and sent at least one message to a provider during the study period (May 2021- May 2022). Chi-square and t-tests were used to describe differences between users and non-users of EMR messaging. ANOVA and chi-square were used to describe differences between race/ethnicity. Analyses were performed in R version 4.2 and p&lt; 0.05 was considered statistically significant.
Results: A total of 4069 patients who had MyChart account activated were included in the analysis sample. Of those, 3575 (87.9%) were messaging users and 494 (12.1%) were non-users. The mean age of users was significantly lower compared to the non-users (57.7 vs 61.2, p&lt; .001). There were statistically significant racial/ethnic differences (p&lt; 0.001) by user status with 83.9% and 9.5% of users being non-Hispanic White (NHW) and non-Hispanic Black (NHB) respectively. Among non-users 69.6% were NHW and 21.1% were NHB. There were also significant differences in preferred language (p&lt; 0.001) and payor (p&lt; 0.001) by user status. 99.2% of users were English speaking and 96.8% of non-users were non-English speaking. 54% and 38%, and 6.5% of users had Managed care, Medicare, and Medicaid respectively as their payor. Whereas 36.9%, 51%, and 10.5% of non-users had Managed care, Medicare, and Medicaid respectively. Lastly, there were statistically significant racial/ethnic differences in the types of messages sent among EMR users.
Conclusions: There are significant differences in race/ethnicity among EMR users and non-users, and racial/ethnic differences in the types of messages sent among EMR messaging users. We believe that these differences may be in part due to disparities in access or comfort in using EMR. Future directions include conducting interviews with minority patients who are users and non-users of EMR messaging to identify barriers and gaps in use.
Table 1. Patient Characteristics. Characteristics of users and non-users of EMR messaging. Chi-square and T-test for significance were performed to assess the difference between groups. P&lt; .05 was considered significant.
Table 2. Message Type by Race/Ethnicity. Types of message sent by race/ethnicity. ANOVA and chi-square were used to describe differences between race/ethnicity and type of message sent. P&lt; .05 was considered significant.
Citation Format: Meghan Conroy, Miracle Powell, Sneha Nagavally, Aprill Dawson, Anna Beckius, Heun Min, Maressa Sweeney, Elizabeth Weil, Angela Hallbach, Lubna N. Chaudhary, Yee Chung Cheng, Jutta Deiinger, John Burfeind, Janet Retseck, Tamiah Wright, John Charlson, Sailaja Kamaraju. Addressing Healthcare Gaps and Disparities in Electronic Medical Record Messages: A Quality Improvement Project Among Breast Cancer Patients [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P6-05-52.