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Gender Disparities in Electronic Health Record Usage and Inbasket Burden for Internal Medicine Residents
Background Studies have demonstrated patients hold different expectations for female physicians compared to male physicians, including higher expectations for patient-centered communication and addressing socioeconomic or emotional needs. Recent evidence indicates this gender disparity extends to th...
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| Published in: | Journal of general internal medicine : JGIM 2024-11, Vol.39 (15), p.2904-2909 |
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| container_end_page | 2909 |
| container_issue | 15 |
| container_start_page | 2904 |
| container_title | Journal of general internal medicine : JGIM |
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| creator | Liddell, Savannah S. Tomasi, Alessandra G. Halvorsen, Andrew J. Stelling, Brianna E. Vaa Leasure, Emily L. |
| description | Background
Studies have demonstrated patients hold different expectations for female physicians compared to male physicians, including higher expectations for patient-centered communication and addressing socioeconomic or emotional needs. Recent evidence indicates this gender disparity extends to the electronic health record (EHR). Similar studies have not been conducted with resident physicians.
Objective
This study seeks to characterize differences in EHR workload for female resident physicians compared to male resident physicians.
Design
This study evaluated 12 months of 156 Mayo Clinic internal medicine residents’ inbasket data from July 2020 to June 2021 using Epic’s Signal and Physician Efficiency Profile (PEP) data. Excel, BlueSky Statistics, and SAS analytical software were used for analysis. Paired
t
-tests and analysis of variance were used to compare PEP data by gender and postgraduate year (PGY). “Male” and “female” were used in substitute for “gender” as is precedent in the literature.
Subjects
Mayo Clinic internal medicine residents.
Main Measures
Total time spent in EHR per day; time in inbasket and notes per day; time in notes per appointment; number of patient advice requests made through the portal; message turnaround time.
Key Results
Female residents received more patient advice requests per year (
p
= 0.004) with an average of 86.7 compared to 68, resulting in 34% more patient advice requests per day worked (
p
|
| doi_str_mv | 10.1007/s11606-024-08861-0 |
| format | article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_3072803429</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>3072803429</sourcerecordid><originalsourceid>FETCH-LOGICAL-c256t-52e3934e3299b0a937c9238c92de8e4fe71c97bf709c09edd2710723c013c6d3</originalsourceid><addsrcrecordid>eNp9kU9P3DAQxS0Egi3lC_SALHHpJWX8J7F9LAsFJBBSBWfLa0_AkHUWOzn029d0aSv10Istzfzes2ceIZ8YfGEA6rQw1kHXAJcNaN2xBnbIgrW8bZg0apcsalU2Wgl5QD6U8gzABOd6nxwIbXgnuFyQp0tMATM9j2XjcpwiFhoTvRjQT3lM0dMrdMP0RL-jH3OgD8U9InUp0Ou0cuUFJ3o254CJ9mOutQlzcgO9xRB9TFhlJdbuVD6Svd4NBY_e70Ny_-3ifnnV3NxdXi-_3jSet93UtByFERIFN2YFzgjlDRe6HgE1yh4V80ategXGg8EQuGKguPB1Nt8FcUg-b203eXydsUx2HYvHYXAJx7lYUWENQnJT0ZN_0Odxfvt9pZiAtuu0bCvFt5TPYykZe7vJce3yD8vAvsVgtzHYGoP9FYOFKjp-t55Xawx_JL_3XgGxBUptpUfMf9_-j-1P3eWRsA</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>3130566845</pqid></control><display><type>article</type><title>Gender Disparities in Electronic Health Record Usage and Inbasket Burden for Internal Medicine Residents</title><source>Springer Nature</source><creator>Liddell, Savannah S. ; Tomasi, Alessandra G. ; Halvorsen, Andrew J. ; Stelling, Brianna E. Vaa ; Leasure, Emily L.</creator><creatorcontrib>Liddell, Savannah S. ; Tomasi, Alessandra G. ; Halvorsen, Andrew J. ; Stelling, Brianna E. Vaa ; Leasure, Emily L.</creatorcontrib><description>Background
Studies have demonstrated patients hold different expectations for female physicians compared to male physicians, including higher expectations for patient-centered communication and addressing socioeconomic or emotional needs. Recent evidence indicates this gender disparity extends to the electronic health record (EHR). Similar studies have not been conducted with resident physicians.
Objective
This study seeks to characterize differences in EHR workload for female resident physicians compared to male resident physicians.
Design
This study evaluated 12 months of 156 Mayo Clinic internal medicine residents’ inbasket data from July 2020 to June 2021 using Epic’s Signal and Physician Efficiency Profile (PEP) data. Excel, BlueSky Statistics, and SAS analytical software were used for analysis. Paired
t
-tests and analysis of variance were used to compare PEP data by gender and postgraduate year (PGY). “Male” and “female” were used in substitute for “gender” as is precedent in the literature.
Subjects
Mayo Clinic internal medicine residents.
Main Measures
Total time spent in EHR per day; time in inbasket and notes per day; time in notes per appointment; number of patient advice requests made through the portal; message turnaround time.
Key Results
Female residents received more patient advice requests per year (
p
= 0.004) with an average of 86.7 compared to 68, resulting in 34% more patient advice requests per day worked (
p
< 0.001). Female residents spent more time in inbasket per day (
p
= 0.002), in notes per day (
p
< 0.001), and in notes per appointment (
p
= 0.001). Resident panel comparisons revealed equivocal sizes with significantly more female patients on female (
n
= 55) vs male (
n
= 34) resident panels (
p
< 0.001). There was no difference in message turnaround time, total messages, or number of results received.
Conclusions
Female resident physicians experience significantly more patient-initiated messages and EHR workload despite equivalent number of results and panel size. Gender differences in inbasket burden may disproportionally impact the resident educational experience.</description><identifier>ISSN: 0884-8734</identifier><identifier>ISSN: 1525-1497</identifier><identifier>EISSN: 1525-1497</identifier><identifier>DOI: 10.1007/s11606-024-08861-0</identifier><identifier>PMID: 38926324</identifier><language>eng</language><publisher>Cham: Springer International Publishing</publisher><subject>Adult ; Data analysis ; Electronic health records ; Electronic Health Records - statistics & numerical data ; Electronic medical records ; Female ; Females ; Gender ; Gender aspects ; Gender differences ; Gender equity ; Humans ; Internal Medicine ; Internal Medicine - education ; Internship and Residency - statistics & numerical data ; Male ; Medical education ; Medical personnel ; Medicine ; Medicine & Public Health ; Messages ; Original Research ; Patients ; Physicians ; Physicians, Women - statistics & numerical data ; Sex differences ; Sex Factors ; Sexism ; Statistical analysis ; Telemedicine ; Time measurement ; Variance analysis ; Workload ; Workloads</subject><ispartof>Journal of general internal medicine : JGIM, 2024-11, Vol.39 (15), p.2904-2909</ispartof><rights>The Author(s), under exclusive licence to Society of General Internal Medicine 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</rights><rights>2024. The Author(s), under exclusive licence to Society of General Internal Medicine.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c256t-52e3934e3299b0a937c9238c92de8e4fe71c97bf709c09edd2710723c013c6d3</cites><orcidid>0000-0002-6891-6264</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27903,27904</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/38926324$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Liddell, Savannah S.</creatorcontrib><creatorcontrib>Tomasi, Alessandra G.</creatorcontrib><creatorcontrib>Halvorsen, Andrew J.</creatorcontrib><creatorcontrib>Stelling, Brianna E. Vaa</creatorcontrib><creatorcontrib>Leasure, Emily L.</creatorcontrib><title>Gender Disparities in Electronic Health Record Usage and Inbasket Burden for Internal Medicine Residents</title><title>Journal of general internal medicine : JGIM</title><addtitle>J GEN INTERN MED</addtitle><addtitle>J Gen Intern Med</addtitle><description>Background
Studies have demonstrated patients hold different expectations for female physicians compared to male physicians, including higher expectations for patient-centered communication and addressing socioeconomic or emotional needs. Recent evidence indicates this gender disparity extends to the electronic health record (EHR). Similar studies have not been conducted with resident physicians.
Objective
This study seeks to characterize differences in EHR workload for female resident physicians compared to male resident physicians.
Design
This study evaluated 12 months of 156 Mayo Clinic internal medicine residents’ inbasket data from July 2020 to June 2021 using Epic’s Signal and Physician Efficiency Profile (PEP) data. Excel, BlueSky Statistics, and SAS analytical software were used for analysis. Paired
t
-tests and analysis of variance were used to compare PEP data by gender and postgraduate year (PGY). “Male” and “female” were used in substitute for “gender” as is precedent in the literature.
Subjects
Mayo Clinic internal medicine residents.
Main Measures
Total time spent in EHR per day; time in inbasket and notes per day; time in notes per appointment; number of patient advice requests made through the portal; message turnaround time.
Key Results
Female residents received more patient advice requests per year (
p
= 0.004) with an average of 86.7 compared to 68, resulting in 34% more patient advice requests per day worked (
p
< 0.001). Female residents spent more time in inbasket per day (
p
= 0.002), in notes per day (
p
< 0.001), and in notes per appointment (
p
= 0.001). Resident panel comparisons revealed equivocal sizes with significantly more female patients on female (
n
= 55) vs male (
n
= 34) resident panels (
p
< 0.001). There was no difference in message turnaround time, total messages, or number of results received.
Conclusions
Female resident physicians experience significantly more patient-initiated messages and EHR workload despite equivalent number of results and panel size. Gender differences in inbasket burden may disproportionally impact the resident educational experience.</description><subject>Adult</subject><subject>Data analysis</subject><subject>Electronic health records</subject><subject>Electronic Health Records - statistics & numerical data</subject><subject>Electronic medical records</subject><subject>Female</subject><subject>Females</subject><subject>Gender</subject><subject>Gender aspects</subject><subject>Gender differences</subject><subject>Gender equity</subject><subject>Humans</subject><subject>Internal Medicine</subject><subject>Internal Medicine - education</subject><subject>Internship and Residency - statistics & numerical data</subject><subject>Male</subject><subject>Medical education</subject><subject>Medical personnel</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Messages</subject><subject>Original Research</subject><subject>Patients</subject><subject>Physicians</subject><subject>Physicians, Women - statistics & numerical data</subject><subject>Sex differences</subject><subject>Sex Factors</subject><subject>Sexism</subject><subject>Statistical analysis</subject><subject>Telemedicine</subject><subject>Time measurement</subject><subject>Variance analysis</subject><subject>Workload</subject><subject>Workloads</subject><issn>0884-8734</issn><issn>1525-1497</issn><issn>1525-1497</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><recordid>eNp9kU9P3DAQxS0Egi3lC_SALHHpJWX8J7F9LAsFJBBSBWfLa0_AkHUWOzn029d0aSv10Istzfzes2ceIZ8YfGEA6rQw1kHXAJcNaN2xBnbIgrW8bZg0apcsalU2Wgl5QD6U8gzABOd6nxwIbXgnuFyQp0tMATM9j2XjcpwiFhoTvRjQT3lM0dMrdMP0RL-jH3OgD8U9InUp0Ou0cuUFJ3o254CJ9mOutQlzcgO9xRB9TFhlJdbuVD6Svd4NBY_e70Ny_-3ifnnV3NxdXi-_3jSet93UtByFERIFN2YFzgjlDRe6HgE1yh4V80ategXGg8EQuGKguPB1Nt8FcUg-b203eXydsUx2HYvHYXAJx7lYUWENQnJT0ZN_0Odxfvt9pZiAtuu0bCvFt5TPYykZe7vJce3yD8vAvsVgtzHYGoP9FYOFKjp-t55Xawx_JL_3XgGxBUptpUfMf9_-j-1P3eWRsA</recordid><startdate>20241101</startdate><enddate>20241101</enddate><creator>Liddell, Savannah S.</creator><creator>Tomasi, Alessandra G.</creator><creator>Halvorsen, Andrew J.</creator><creator>Stelling, Brianna E. Vaa</creator><creator>Leasure, Emily L.</creator><general>Springer International Publishing</general><general>Springer Nature B.V</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QL</scope><scope>7U9</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>H94</scope><scope>K9.</scope><scope>M7N</scope><scope>NAPCQ</scope><scope>P64</scope><scope>RC3</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-6891-6264</orcidid></search><sort><creationdate>20241101</creationdate><title>Gender Disparities in Electronic Health Record Usage and Inbasket Burden for Internal Medicine Residents</title><author>Liddell, Savannah S. ; Tomasi, Alessandra G. ; Halvorsen, Andrew J. ; Stelling, Brianna E. Vaa ; Leasure, Emily L.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c256t-52e3934e3299b0a937c9238c92de8e4fe71c97bf709c09edd2710723c013c6d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Adult</topic><topic>Data analysis</topic><topic>Electronic health records</topic><topic>Electronic Health Records - statistics & numerical data</topic><topic>Electronic medical records</topic><topic>Female</topic><topic>Females</topic><topic>Gender</topic><topic>Gender aspects</topic><topic>Gender differences</topic><topic>Gender equity</topic><topic>Humans</topic><topic>Internal Medicine</topic><topic>Internal Medicine - education</topic><topic>Internship and Residency - statistics & numerical data</topic><topic>Male</topic><topic>Medical education</topic><topic>Medical personnel</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Messages</topic><topic>Original Research</topic><topic>Patients</topic><topic>Physicians</topic><topic>Physicians, Women - statistics & numerical data</topic><topic>Sex differences</topic><topic>Sex Factors</topic><topic>Sexism</topic><topic>Statistical analysis</topic><topic>Telemedicine</topic><topic>Time measurement</topic><topic>Variance analysis</topic><topic>Workload</topic><topic>Workloads</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Liddell, Savannah S.</creatorcontrib><creatorcontrib>Tomasi, Alessandra G.</creatorcontrib><creatorcontrib>Halvorsen, Andrew J.</creatorcontrib><creatorcontrib>Stelling, Brianna E. Vaa</creatorcontrib><creatorcontrib>Leasure, Emily L.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Virology and AIDS Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Nursing & Allied Health Premium</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of general internal medicine : JGIM</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Liddell, Savannah S.</au><au>Tomasi, Alessandra G.</au><au>Halvorsen, Andrew J.</au><au>Stelling, Brianna E. Vaa</au><au>Leasure, Emily L.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Gender Disparities in Electronic Health Record Usage and Inbasket Burden for Internal Medicine Residents</atitle><jtitle>Journal of general internal medicine : JGIM</jtitle><stitle>J GEN INTERN MED</stitle><addtitle>J Gen Intern Med</addtitle><date>2024-11-01</date><risdate>2024</risdate><volume>39</volume><issue>15</issue><spage>2904</spage><epage>2909</epage><pages>2904-2909</pages><issn>0884-8734</issn><issn>1525-1497</issn><eissn>1525-1497</eissn><abstract>Background
Studies have demonstrated patients hold different expectations for female physicians compared to male physicians, including higher expectations for patient-centered communication and addressing socioeconomic or emotional needs. Recent evidence indicates this gender disparity extends to the electronic health record (EHR). Similar studies have not been conducted with resident physicians.
Objective
This study seeks to characterize differences in EHR workload for female resident physicians compared to male resident physicians.
Design
This study evaluated 12 months of 156 Mayo Clinic internal medicine residents’ inbasket data from July 2020 to June 2021 using Epic’s Signal and Physician Efficiency Profile (PEP) data. Excel, BlueSky Statistics, and SAS analytical software were used for analysis. Paired
t
-tests and analysis of variance were used to compare PEP data by gender and postgraduate year (PGY). “Male” and “female” were used in substitute for “gender” as is precedent in the literature.
Subjects
Mayo Clinic internal medicine residents.
Main Measures
Total time spent in EHR per day; time in inbasket and notes per day; time in notes per appointment; number of patient advice requests made through the portal; message turnaround time.
Key Results
Female residents received more patient advice requests per year (
p
= 0.004) with an average of 86.7 compared to 68, resulting in 34% more patient advice requests per day worked (
p
< 0.001). Female residents spent more time in inbasket per day (
p
= 0.002), in notes per day (
p
< 0.001), and in notes per appointment (
p
= 0.001). Resident panel comparisons revealed equivocal sizes with significantly more female patients on female (
n
= 55) vs male (
n
= 34) resident panels (
p
< 0.001). There was no difference in message turnaround time, total messages, or number of results received.
Conclusions
Female resident physicians experience significantly more patient-initiated messages and EHR workload despite equivalent number of results and panel size. Gender differences in inbasket burden may disproportionally impact the resident educational experience.</abstract><cop>Cham</cop><pub>Springer International Publishing</pub><pmid>38926324</pmid><doi>10.1007/s11606-024-08861-0</doi><tpages>6</tpages><orcidid>https://orcid.org/0000-0002-6891-6264</orcidid></addata></record> |
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| identifier | ISSN: 0884-8734 |
| ispartof | Journal of general internal medicine : JGIM, 2024-11, Vol.39 (15), p.2904-2909 |
| issn | 0884-8734 1525-1497 1525-1497 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_3072803429 |
| source | Springer Nature |
| subjects | Adult Data analysis Electronic health records Electronic Health Records - statistics & numerical data Electronic medical records Female Females Gender Gender aspects Gender differences Gender equity Humans Internal Medicine Internal Medicine - education Internship and Residency - statistics & numerical data Male Medical education Medical personnel Medicine Medicine & Public Health Messages Original Research Patients Physicians Physicians, Women - statistics & numerical data Sex differences Sex Factors Sexism Statistical analysis Telemedicine Time measurement Variance analysis Workload Workloads |
| title | Gender Disparities in Electronic Health Record Usage and Inbasket Burden for Internal Medicine Residents |
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