Neighborhood Effects on Missed Appointments in a Large Urban Academic Multispecialty Practice
Background Missed appointments diminish the continuity and quality of care. Objective To determine whether missing scheduled appointments is associated with characteristics of the populations in places where patients reside. Design Retrospective cross-sectional study using data extracted from electr...
Gespeichert in:
| Veröffentlicht in: | Journal of general internal medicine : JGIM 2022-03, Vol.37 (4), p.785-792 |
|---|---|
| Hauptverfasser: | , , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 792 |
|---|---|
| container_issue | 4 |
| container_start_page | 785 |
| container_title | Journal of general internal medicine : JGIM |
| container_volume | 37 |
| creator | Chou, Edgar Y. Moore, Kari Zhao, Yuzhe Melly, Steven Payvandi, Lily Buehler, James W. |
| description | Background
Missed appointments diminish the continuity and quality of care.
Objective
To determine whether missing scheduled appointments is associated with characteristics of the populations in places where patients reside.
Design
Retrospective cross-sectional study using data extracted from electronic health records linked to population descriptors for each patient’s census tract of residence.
Patients
A total of 58,981 patients ≥18 years of age with 275,682 scheduled appointments during 2014–2015 at a multispecialty outpatient practice.
Main Measures
We used multinomial generalized linear mixed models to examine associations between the outcomes of scheduled appointments (arrived, canceled, or missed) and selected characteristics of the populations in patients’ census tracts of residence (racial/ethnic segregation based on population composition, levels of poverty, violent crime, and perceived safety and social capital), controlling for patients’ age, gender, type of insurance, and type of clinic service.
Key Results
Overall, 17.5% of appointments were missed. For appointments among patients residing in census tracts in the highest versus lowest quartile for each population metric, adjusted odds ratios (aORs) for missed appointments were 1.27 (CI 1.19, 1.35) for the rate of violent crime, 1.27 (CI 1.20, 1.34) for the proportion Hispanic, 1.19 (CI 1.12, 1.27) for the proportion living in poverty, 1.13 (CI 1.05, 1.20) for the proportion of the census tract population that was Black, and 1.06 (CI 1.01, 1.11 for perceived neighborhood safety.
Conclusions
Characteristics of the places where patients reside are associated with missing scheduled appointments, including high levels of racial/ethnic segregation, poverty, and violent crime and low levels of perceived neighborhood safety. As such, targeting efforts to improve access for patients living in such neighborhoods will be particularly important to address underlying social determinants of access to health care. |
| doi_str_mv | 10.1007/s11606-021-06935-x |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_8904676</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2544462501</sourcerecordid><originalsourceid>FETCH-LOGICAL-c474t-629b3e4d3363359b3cb3697b28af8998ca3e022992998bde8730d60f402875e93</originalsourceid><addsrcrecordid>eNp9kUtv1DAUhS0EotOBP8ACWWLDJuD3Y4M0qkpBmgILukSW49zMuEriwU5Q--8xTCmPBZIlW77fPb7HB6FnlLyihOjXhVJFVEMYbYiyXDY3D9CKSiYbKqx-iFbEGNEYzcUJOi3lmhDKGTOP0QkXVFopzAp9-QBxt29T3qfU4fO-hzAXnCZ8GUuBDm8OhxSneYSpXscJe7z1eQf4Krd-wpvgOxhjwJfLMMdygBD9MN_iT9mHOQZ4gh71fijw9G5fo6u355_P3jXbjxfvzzbbJggt5kYx23IQHeeKc1nPoeXK6pYZ3xtrTfAcCGPW1mXaDqol0inSC8KMlmD5Gr056h6WdoQu1GmzH9whx9HnW5d8dH9Xprh3u_TNGUuE0qoKvLwTyOnrAmV2YywBhsFPkJbimBRCKCbrD67Ri3_Q67TkqdpzTHEttVVUV4odqZBTKRn6-2EocT_Sc8f0XE3P_UzP3dSm53_auG_5FVcF-BEotTTtIP9--z-y3wH4QaXi</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2637579617</pqid></control><display><type>article</type><title>Neighborhood Effects on Missed Appointments in a Large Urban Academic Multispecialty Practice</title><source>MEDLINE</source><source>Springer Nature - Complete Springer Journals</source><source>EZB-FREE-00999 freely available EZB journals</source><source>PubMed Central</source><source>Alma/SFX Local Collection</source><creator>Chou, Edgar Y. ; Moore, Kari ; Zhao, Yuzhe ; Melly, Steven ; Payvandi, Lily ; Buehler, James W.</creator><creatorcontrib>Chou, Edgar Y. ; Moore, Kari ; Zhao, Yuzhe ; Melly, Steven ; Payvandi, Lily ; Buehler, James W.</creatorcontrib><description>Background
Missed appointments diminish the continuity and quality of care.
Objective
To determine whether missing scheduled appointments is associated with characteristics of the populations in places where patients reside.
Design
Retrospective cross-sectional study using data extracted from electronic health records linked to population descriptors for each patient’s census tract of residence.
Patients
A total of 58,981 patients ≥18 years of age with 275,682 scheduled appointments during 2014–2015 at a multispecialty outpatient practice.
Main Measures
We used multinomial generalized linear mixed models to examine associations between the outcomes of scheduled appointments (arrived, canceled, or missed) and selected characteristics of the populations in patients’ census tracts of residence (racial/ethnic segregation based on population composition, levels of poverty, violent crime, and perceived safety and social capital), controlling for patients’ age, gender, type of insurance, and type of clinic service.
Key Results
Overall, 17.5% of appointments were missed. For appointments among patients residing in census tracts in the highest versus lowest quartile for each population metric, adjusted odds ratios (aORs) for missed appointments were 1.27 (CI 1.19, 1.35) for the rate of violent crime, 1.27 (CI 1.20, 1.34) for the proportion Hispanic, 1.19 (CI 1.12, 1.27) for the proportion living in poverty, 1.13 (CI 1.05, 1.20) for the proportion of the census tract population that was Black, and 1.06 (CI 1.01, 1.11 for perceived neighborhood safety.
Conclusions
Characteristics of the places where patients reside are associated with missing scheduled appointments, including high levels of racial/ethnic segregation, poverty, and violent crime and low levels of perceived neighborhood safety. As such, targeting efforts to improve access for patients living in such neighborhoods will be particularly important to address underlying social determinants of access to health care.</description><identifier>ISSN: 0884-8734</identifier><identifier>EISSN: 1525-1497</identifier><identifier>DOI: 10.1007/s11606-021-06935-x</identifier><identifier>PMID: 34159548</identifier><language>eng</language><publisher>Cham: Springer International Publishing</publisher><subject>Appointments and Schedules ; Census ; Censuses ; Crime ; Cross-Sectional Studies ; Electronic health records ; Electronic medical records ; Ethnicity ; Health care ; Humans ; Internal Medicine ; Medicine ; Medicine & Public Health ; Neighborhoods ; Original Research ; Patients ; Population ; Populations ; Poverty ; Residence Characteristics ; Retrospective Studies ; Safety ; Segregation ; Social Segregation ; Statistical models ; Violence ; Violent crime</subject><ispartof>Journal of general internal medicine : JGIM, 2022-03, Vol.37 (4), p.785-792</ispartof><rights>Society of General Internal Medicine 2021</rights><rights>2021. Society of General Internal Medicine.</rights><rights>Society of General Internal Medicine 2021.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c474t-629b3e4d3363359b3cb3697b28af8998ca3e022992998bde8730d60f402875e93</citedby><cites>FETCH-LOGICAL-c474t-629b3e4d3363359b3cb3697b28af8998ca3e022992998bde8730d60f402875e93</cites><orcidid>0000-0001-9784-2711</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8904676/pdf/$$EPDF$$P50$$Gpubmedcentral$$H</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8904676/$$EHTML$$P50$$Gpubmedcentral$$H</linktohtml><link.rule.ids>230,314,724,777,781,882,27905,27906,41469,42538,51300,53772,53774</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34159548$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Chou, Edgar Y.</creatorcontrib><creatorcontrib>Moore, Kari</creatorcontrib><creatorcontrib>Zhao, Yuzhe</creatorcontrib><creatorcontrib>Melly, Steven</creatorcontrib><creatorcontrib>Payvandi, Lily</creatorcontrib><creatorcontrib>Buehler, James W.</creatorcontrib><title>Neighborhood Effects on Missed Appointments in a Large Urban Academic Multispecialty Practice</title><title>Journal of general internal medicine : JGIM</title><addtitle>J GEN INTERN MED</addtitle><addtitle>J Gen Intern Med</addtitle><description>Background
Missed appointments diminish the continuity and quality of care.
Objective
To determine whether missing scheduled appointments is associated with characteristics of the populations in places where patients reside.
Design
Retrospective cross-sectional study using data extracted from electronic health records linked to population descriptors for each patient’s census tract of residence.
Patients
A total of 58,981 patients ≥18 years of age with 275,682 scheduled appointments during 2014–2015 at a multispecialty outpatient practice.
Main Measures
We used multinomial generalized linear mixed models to examine associations between the outcomes of scheduled appointments (arrived, canceled, or missed) and selected characteristics of the populations in patients’ census tracts of residence (racial/ethnic segregation based on population composition, levels of poverty, violent crime, and perceived safety and social capital), controlling for patients’ age, gender, type of insurance, and type of clinic service.
Key Results
Overall, 17.5% of appointments were missed. For appointments among patients residing in census tracts in the highest versus lowest quartile for each population metric, adjusted odds ratios (aORs) for missed appointments were 1.27 (CI 1.19, 1.35) for the rate of violent crime, 1.27 (CI 1.20, 1.34) for the proportion Hispanic, 1.19 (CI 1.12, 1.27) for the proportion living in poverty, 1.13 (CI 1.05, 1.20) for the proportion of the census tract population that was Black, and 1.06 (CI 1.01, 1.11 for perceived neighborhood safety.
Conclusions
Characteristics of the places where patients reside are associated with missing scheduled appointments, including high levels of racial/ethnic segregation, poverty, and violent crime and low levels of perceived neighborhood safety. As such, targeting efforts to improve access for patients living in such neighborhoods will be particularly important to address underlying social determinants of access to health care.</description><subject>Appointments and Schedules</subject><subject>Census</subject><subject>Censuses</subject><subject>Crime</subject><subject>Cross-Sectional Studies</subject><subject>Electronic health records</subject><subject>Electronic medical records</subject><subject>Ethnicity</subject><subject>Health care</subject><subject>Humans</subject><subject>Internal Medicine</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Neighborhoods</subject><subject>Original Research</subject><subject>Patients</subject><subject>Population</subject><subject>Populations</subject><subject>Poverty</subject><subject>Residence Characteristics</subject><subject>Retrospective Studies</subject><subject>Safety</subject><subject>Segregation</subject><subject>Social Segregation</subject><subject>Statistical models</subject><subject>Violence</subject><subject>Violent crime</subject><issn>0884-8734</issn><issn>1525-1497</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNp9kUtv1DAUhS0EotOBP8ACWWLDJuD3Y4M0qkpBmgILukSW49zMuEriwU5Q--8xTCmPBZIlW77fPb7HB6FnlLyihOjXhVJFVEMYbYiyXDY3D9CKSiYbKqx-iFbEGNEYzcUJOi3lmhDKGTOP0QkXVFopzAp9-QBxt29T3qfU4fO-hzAXnCZ8GUuBDm8OhxSneYSpXscJe7z1eQf4Krd-wpvgOxhjwJfLMMdygBD9MN_iT9mHOQZ4gh71fijw9G5fo6u355_P3jXbjxfvzzbbJggt5kYx23IQHeeKc1nPoeXK6pYZ3xtrTfAcCGPW1mXaDqol0inSC8KMlmD5Gr056h6WdoQu1GmzH9whx9HnW5d8dH9Xprh3u_TNGUuE0qoKvLwTyOnrAmV2YywBhsFPkJbimBRCKCbrD67Ri3_Q67TkqdpzTHEttVVUV4odqZBTKRn6-2EocT_Sc8f0XE3P_UzP3dSm53_auG_5FVcF-BEotTTtIP9--z-y3wH4QaXi</recordid><startdate>20220301</startdate><enddate>20220301</enddate><creator>Chou, Edgar Y.</creator><creator>Moore, Kari</creator><creator>Zhao, Yuzhe</creator><creator>Melly, Steven</creator><creator>Payvandi, Lily</creator><creator>Buehler, James W.</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>3V.</scope><scope>7QL</scope><scope>7RV</scope><scope>7U9</scope><scope>7X7</scope><scope>7XB</scope><scope>88C</scope><scope>8AO</scope><scope>8FD</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>H94</scope><scope>K9.</scope><scope>M0S</scope><scope>M0T</scope><scope>M1P</scope><scope>M2O</scope><scope>M7N</scope><scope>MBDVC</scope><scope>NAPCQ</scope><scope>P64</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0001-9784-2711</orcidid></search><sort><creationdate>20220301</creationdate><title>Neighborhood Effects on Missed Appointments in a Large Urban Academic Multispecialty Practice</title><author>Chou, Edgar Y. ; Moore, Kari ; Zhao, Yuzhe ; Melly, Steven ; Payvandi, Lily ; Buehler, James W.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c474t-629b3e4d3363359b3cb3697b28af8998ca3e022992998bde8730d60f402875e93</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Appointments and Schedules</topic><topic>Census</topic><topic>Censuses</topic><topic>Crime</topic><topic>Cross-Sectional Studies</topic><topic>Electronic health records</topic><topic>Electronic medical records</topic><topic>Ethnicity</topic><topic>Health care</topic><topic>Humans</topic><topic>Internal Medicine</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Neighborhoods</topic><topic>Original Research</topic><topic>Patients</topic><topic>Population</topic><topic>Populations</topic><topic>Poverty</topic><topic>Residence Characteristics</topic><topic>Retrospective Studies</topic><topic>Safety</topic><topic>Segregation</topic><topic>Social Segregation</topic><topic>Statistical models</topic><topic>Violence</topic><topic>Violent crime</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Chou, Edgar Y.</creatorcontrib><creatorcontrib>Moore, Kari</creatorcontrib><creatorcontrib>Zhao, Yuzhe</creatorcontrib><creatorcontrib>Melly, Steven</creatorcontrib><creatorcontrib>Payvandi, Lily</creatorcontrib><creatorcontrib>Buehler, James W.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Nursing & Allied Health Database</collection><collection>Virology and AIDS Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Healthcare Administration Database (Alumni)</collection><collection>ProQuest Pharma Collection</collection><collection>Technology Research Database</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Healthcare Administration Database</collection><collection>Medical Database</collection><collection>Research Library</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Research Library (Corporate)</collection><collection>Nursing & Allied Health Premium</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Journal of general internal medicine : JGIM</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Chou, Edgar Y.</au><au>Moore, Kari</au><au>Zhao, Yuzhe</au><au>Melly, Steven</au><au>Payvandi, Lily</au><au>Buehler, James W.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Neighborhood Effects on Missed Appointments in a Large Urban Academic Multispecialty Practice</atitle><jtitle>Journal of general internal medicine : JGIM</jtitle><stitle>J GEN INTERN MED</stitle><addtitle>J Gen Intern Med</addtitle><date>2022-03-01</date><risdate>2022</risdate><volume>37</volume><issue>4</issue><spage>785</spage><epage>792</epage><pages>785-792</pages><issn>0884-8734</issn><eissn>1525-1497</eissn><abstract>Background
Missed appointments diminish the continuity and quality of care.
Objective
To determine whether missing scheduled appointments is associated with characteristics of the populations in places where patients reside.
Design
Retrospective cross-sectional study using data extracted from electronic health records linked to population descriptors for each patient’s census tract of residence.
Patients
A total of 58,981 patients ≥18 years of age with 275,682 scheduled appointments during 2014–2015 at a multispecialty outpatient practice.
Main Measures
We used multinomial generalized linear mixed models to examine associations between the outcomes of scheduled appointments (arrived, canceled, or missed) and selected characteristics of the populations in patients’ census tracts of residence (racial/ethnic segregation based on population composition, levels of poverty, violent crime, and perceived safety and social capital), controlling for patients’ age, gender, type of insurance, and type of clinic service.
Key Results
Overall, 17.5% of appointments were missed. For appointments among patients residing in census tracts in the highest versus lowest quartile for each population metric, adjusted odds ratios (aORs) for missed appointments were 1.27 (CI 1.19, 1.35) for the rate of violent crime, 1.27 (CI 1.20, 1.34) for the proportion Hispanic, 1.19 (CI 1.12, 1.27) for the proportion living in poverty, 1.13 (CI 1.05, 1.20) for the proportion of the census tract population that was Black, and 1.06 (CI 1.01, 1.11 for perceived neighborhood safety.
Conclusions
Characteristics of the places where patients reside are associated with missing scheduled appointments, including high levels of racial/ethnic segregation, poverty, and violent crime and low levels of perceived neighborhood safety. As such, targeting efforts to improve access for patients living in such neighborhoods will be particularly important to address underlying social determinants of access to health care.</abstract><cop>Cham</cop><pub>Springer International Publishing</pub><pmid>34159548</pmid><doi>10.1007/s11606-021-06935-x</doi><tpages>8</tpages><orcidid>https://orcid.org/0000-0001-9784-2711</orcidid><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0884-8734 |
| ispartof | Journal of general internal medicine : JGIM, 2022-03, Vol.37 (4), p.785-792 |
| issn | 0884-8734 1525-1497 |
| language | eng |
| recordid | cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_8904676 |
| source | MEDLINE; Springer Nature - Complete Springer Journals; EZB-FREE-00999 freely available EZB journals; PubMed Central; Alma/SFX Local Collection |
| subjects | Appointments and Schedules Census Censuses Crime Cross-Sectional Studies Electronic health records Electronic medical records Ethnicity Health care Humans Internal Medicine Medicine Medicine & Public Health Neighborhoods Original Research Patients Population Populations Poverty Residence Characteristics Retrospective Studies Safety Segregation Social Segregation Statistical models Violence Violent crime |
| title | Neighborhood Effects on Missed Appointments in a Large Urban Academic Multispecialty Practice |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-20T10%3A54%3A23IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_pubme&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Neighborhood%20Effects%20on%20Missed%20Appointments%20in%20a%20Large%20Urban%20Academic%20Multispecialty%20Practice&rft.jtitle=Journal%20of%20general%20internal%20medicine%20:%20JGIM&rft.au=Chou,%20Edgar%20Y.&rft.date=2022-03-01&rft.volume=37&rft.issue=4&rft.spage=785&rft.epage=792&rft.pages=785-792&rft.issn=0884-8734&rft.eissn=1525-1497&rft_id=info:doi/10.1007/s11606-021-06935-x&rft_dat=%3Cproquest_pubme%3E2544462501%3C/proquest_pubme%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2637579617&rft_id=info:pmid/34159548&rfr_iscdi=true |