Mind the clinical-analytic gap: Electronic health records and COVID-19 pandemic response
[Display omitted] •Electronic health records (EHRs) are important for real-time tracking of COVID-19.•Generating high-quality real-time EHR data for crisis response is challenging.•Many challenges can be mitigated by forming cross-functional teams.•Such teams join clinical operations, informatics, d...
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Veröffentlicht in: | Journal of biomedical informatics 2021-04, Vol.116, p.103715-103715, Article 103715 |
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container_title | Journal of biomedical informatics |
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creator | Sudat, Sylvia E.K. Robinson, Sarah C. Mudiganti, Satish Mani, Aravind Pressman, Alice R. |
description | [Display omitted]
•Electronic health records (EHRs) are important for real-time tracking of COVID-19.•Generating high-quality real-time EHR data for crisis response is challenging.•Many challenges can be mitigated by forming cross-functional teams.•Such teams join clinical operations, informatics, data analytics, and research.•This team-based approach can better support current and future crisis response.
Data quality is essential to the success of the most simple and the most complex analysis. In the context of the COVID-19 pandemic, large-scale data sharing across the US and around the world has played an important role in public health responses to the pandemic and has been crucial to understanding and predicting its likely course. In California, hospitals have been required to report a large volume of daily data related to COVID-19. In order to meet this need, electronic health records (EHRs) have played an important role, but the challenges of reporting high-quality data in real-time from EHR data sources have not been explored.
We describe some of the challenges of utilizing EHR data for this purpose from the perspective of a large, integrated, mixed-payer health system in northern California, US. We emphasize some of the inadequacies inherent to EHR data using several specific examples, and explore the clinical-analytic gap that forms the basis for some of these inadequacies. We highlight the need for data and analytics to be incorporated into the early stages of clinical crisis planning in order to utilize EHR data to full advantage. We further propose that lessons learned from the COVID-19 pandemic can result in the formation of collaborative teams joining clinical operations, informatics, data analytics, and research, ultimately resulting in improved data quality to support effective crisis response. |
doi_str_mv | 10.1016/j.jbi.2021.103715 |
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•Electronic health records (EHRs) are important for real-time tracking of COVID-19.•Generating high-quality real-time EHR data for crisis response is challenging.•Many challenges can be mitigated by forming cross-functional teams.•Such teams join clinical operations, informatics, data analytics, and research.•This team-based approach can better support current and future crisis response.
Data quality is essential to the success of the most simple and the most complex analysis. In the context of the COVID-19 pandemic, large-scale data sharing across the US and around the world has played an important role in public health responses to the pandemic and has been crucial to understanding and predicting its likely course. In California, hospitals have been required to report a large volume of daily data related to COVID-19. In order to meet this need, electronic health records (EHRs) have played an important role, but the challenges of reporting high-quality data in real-time from EHR data sources have not been explored.
We describe some of the challenges of utilizing EHR data for this purpose from the perspective of a large, integrated, mixed-payer health system in northern California, US. We emphasize some of the inadequacies inherent to EHR data using several specific examples, and explore the clinical-analytic gap that forms the basis for some of these inadequacies. We highlight the need for data and analytics to be incorporated into the early stages of clinical crisis planning in order to utilize EHR data to full advantage. We further propose that lessons learned from the COVID-19 pandemic can result in the formation of collaborative teams joining clinical operations, informatics, data analytics, and research, ultimately resulting in improved data quality to support effective crisis response.</description><identifier>ISSN: 1532-0464</identifier><identifier>EISSN: 1532-0480</identifier><identifier>DOI: 10.1016/j.jbi.2021.103715</identifier><identifier>PMID: 33610878</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>California - epidemiology ; COVID-19 ; COVID-19 - epidemiology ; COVID-19 - mortality ; COVID-19 - therapy ; Data Accuracy ; Data quality ; Delivery of Health Care, Integrated - statistics & numerical data ; Electronic health record ; Electronic Health Records - statistics & numerical data ; Health Information Exchange - statistics & numerical data ; Hospital Bed Capacity - statistics & numerical data ; Humans ; Information Dissemination - methods ; Medical Informatics ; Pandemics - statistics & numerical data ; Real-world data ; SARS-CoV-2</subject><ispartof>Journal of biomedical informatics, 2021-04, Vol.116, p.103715-103715, Article 103715</ispartof><rights>2021 Elsevier Inc.</rights><rights>Copyright © 2021 Elsevier Inc. All rights reserved.</rights><rights>2021 Elsevier Inc. 2021 Elsevier Inc.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c451t-6f9a2e09e81fd8f88415ed50e1f9c3ab91080ad074d557e47a1a46707fc8d7ea3</citedby><cites>FETCH-LOGICAL-c451t-6f9a2e09e81fd8f88415ed50e1f9c3ab91080ad074d557e47a1a46707fc8d7ea3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.jbi.2021.103715$$EHTML$$P50$$Gelsevier$$Hfree_for_read</linktohtml><link.rule.ids>230,314,778,782,883,3539,27907,27908,45978</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33610878$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Sudat, Sylvia E.K.</creatorcontrib><creatorcontrib>Robinson, Sarah C.</creatorcontrib><creatorcontrib>Mudiganti, Satish</creatorcontrib><creatorcontrib>Mani, Aravind</creatorcontrib><creatorcontrib>Pressman, Alice R.</creatorcontrib><title>Mind the clinical-analytic gap: Electronic health records and COVID-19 pandemic response</title><title>Journal of biomedical informatics</title><addtitle>J Biomed Inform</addtitle><description>[Display omitted]
•Electronic health records (EHRs) are important for real-time tracking of COVID-19.•Generating high-quality real-time EHR data for crisis response is challenging.•Many challenges can be mitigated by forming cross-functional teams.•Such teams join clinical operations, informatics, data analytics, and research.•This team-based approach can better support current and future crisis response.
Data quality is essential to the success of the most simple and the most complex analysis. In the context of the COVID-19 pandemic, large-scale data sharing across the US and around the world has played an important role in public health responses to the pandemic and has been crucial to understanding and predicting its likely course. In California, hospitals have been required to report a large volume of daily data related to COVID-19. In order to meet this need, electronic health records (EHRs) have played an important role, but the challenges of reporting high-quality data in real-time from EHR data sources have not been explored.
We describe some of the challenges of utilizing EHR data for this purpose from the perspective of a large, integrated, mixed-payer health system in northern California, US. We emphasize some of the inadequacies inherent to EHR data using several specific examples, and explore the clinical-analytic gap that forms the basis for some of these inadequacies. We highlight the need for data and analytics to be incorporated into the early stages of clinical crisis planning in order to utilize EHR data to full advantage. We further propose that lessons learned from the COVID-19 pandemic can result in the formation of collaborative teams joining clinical operations, informatics, data analytics, and research, ultimately resulting in improved data quality to support effective crisis response.</description><subject>California - epidemiology</subject><subject>COVID-19</subject><subject>COVID-19 - epidemiology</subject><subject>COVID-19 - mortality</subject><subject>COVID-19 - therapy</subject><subject>Data Accuracy</subject><subject>Data quality</subject><subject>Delivery of Health Care, Integrated - statistics & numerical data</subject><subject>Electronic health record</subject><subject>Electronic Health Records - statistics & numerical data</subject><subject>Health Information Exchange - statistics & numerical data</subject><subject>Hospital Bed Capacity - statistics & numerical data</subject><subject>Humans</subject><subject>Information Dissemination - methods</subject><subject>Medical Informatics</subject><subject>Pandemics - statistics & numerical data</subject><subject>Real-world data</subject><subject>SARS-CoV-2</subject><issn>1532-0464</issn><issn>1532-0480</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9UU1rGzEQFaElH05_QC5lj72sK2mllbaBQnDSNpCSS1p6E2NpNpaRV1tpHci_j4ITk156mhnmvTfDe4ScMTpnlLWf1_P10s855azMjWLygBwz2fCaCk3f7ftWHJGTnNeUMiZle0iOmqZlVCt9TP789IOrphVWNvjBWwg1DBAeJ2-rexi_VFcB7ZRiWVUrhDCtqoQ2JpcrKMTF7e_ry5p11Vgm3BRQwjzGIeMped9DyPjhpc7Ir29Xd4sf9c3t9-vFxU1thWRT3fYdcKQdatY73WstmEQnKbK-sw0su_InBUeVcFIqFAoYiFZR1VvtFEIzI193uuN2uUFncZgSBDMmv4H0aCJ48-9m8CtzHx-M0h1vikMz8ulFIMW_W8yT2fhsMQQYMG6z4aLjXAvKdYGyHdSmmHPCfn-GUfOciFmbkoh5TsTsEimcj2__2zNeIyiA8x0Ai0sPHpPJ1uNg0fni9GRc9P-RfwLfxpwm</recordid><startdate>20210401</startdate><enddate>20210401</enddate><creator>Sudat, Sylvia E.K.</creator><creator>Robinson, Sarah C.</creator><creator>Mudiganti, Satish</creator><creator>Mani, Aravind</creator><creator>Pressman, Alice R.</creator><general>Elsevier Inc</general><scope>6I.</scope><scope>AAFTH</scope><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>7X8</scope><scope>5PM</scope></search><sort><creationdate>20210401</creationdate><title>Mind the clinical-analytic gap: Electronic health records and COVID-19 pandemic response</title><author>Sudat, Sylvia E.K. ; Robinson, Sarah C. ; Mudiganti, Satish ; Mani, Aravind ; Pressman, Alice R.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c451t-6f9a2e09e81fd8f88415ed50e1f9c3ab91080ad074d557e47a1a46707fc8d7ea3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>California - epidemiology</topic><topic>COVID-19</topic><topic>COVID-19 - epidemiology</topic><topic>COVID-19 - mortality</topic><topic>COVID-19 - therapy</topic><topic>Data Accuracy</topic><topic>Data quality</topic><topic>Delivery of Health Care, Integrated - statistics & numerical data</topic><topic>Electronic health record</topic><topic>Electronic Health Records - statistics & numerical data</topic><topic>Health Information Exchange - statistics & numerical data</topic><topic>Hospital Bed Capacity - statistics & numerical data</topic><topic>Humans</topic><topic>Information Dissemination - methods</topic><topic>Medical Informatics</topic><topic>Pandemics - statistics & numerical data</topic><topic>Real-world data</topic><topic>SARS-CoV-2</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Sudat, Sylvia E.K.</creatorcontrib><creatorcontrib>Robinson, Sarah C.</creatorcontrib><creatorcontrib>Mudiganti, Satish</creatorcontrib><creatorcontrib>Mani, Aravind</creatorcontrib><creatorcontrib>Pressman, Alice R.</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Journal of biomedical informatics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Sudat, Sylvia E.K.</au><au>Robinson, Sarah C.</au><au>Mudiganti, Satish</au><au>Mani, Aravind</au><au>Pressman, Alice R.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Mind the clinical-analytic gap: Electronic health records and COVID-19 pandemic response</atitle><jtitle>Journal of biomedical informatics</jtitle><addtitle>J Biomed Inform</addtitle><date>2021-04-01</date><risdate>2021</risdate><volume>116</volume><spage>103715</spage><epage>103715</epage><pages>103715-103715</pages><artnum>103715</artnum><issn>1532-0464</issn><eissn>1532-0480</eissn><abstract>[Display omitted]
•Electronic health records (EHRs) are important for real-time tracking of COVID-19.•Generating high-quality real-time EHR data for crisis response is challenging.•Many challenges can be mitigated by forming cross-functional teams.•Such teams join clinical operations, informatics, data analytics, and research.•This team-based approach can better support current and future crisis response.
Data quality is essential to the success of the most simple and the most complex analysis. In the context of the COVID-19 pandemic, large-scale data sharing across the US and around the world has played an important role in public health responses to the pandemic and has been crucial to understanding and predicting its likely course. In California, hospitals have been required to report a large volume of daily data related to COVID-19. In order to meet this need, electronic health records (EHRs) have played an important role, but the challenges of reporting high-quality data in real-time from EHR data sources have not been explored.
We describe some of the challenges of utilizing EHR data for this purpose from the perspective of a large, integrated, mixed-payer health system in northern California, US. We emphasize some of the inadequacies inherent to EHR data using several specific examples, and explore the clinical-analytic gap that forms the basis for some of these inadequacies. We highlight the need for data and analytics to be incorporated into the early stages of clinical crisis planning in order to utilize EHR data to full advantage. We further propose that lessons learned from the COVID-19 pandemic can result in the formation of collaborative teams joining clinical operations, informatics, data analytics, and research, ultimately resulting in improved data quality to support effective crisis response.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>33610878</pmid><doi>10.1016/j.jbi.2021.103715</doi><tpages>1</tpages><oa>free_for_read</oa></addata></record> |
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subjects | California - epidemiology COVID-19 COVID-19 - epidemiology COVID-19 - mortality COVID-19 - therapy Data Accuracy Data quality Delivery of Health Care, Integrated - statistics & numerical data Electronic health record Electronic Health Records - statistics & numerical data Health Information Exchange - statistics & numerical data Hospital Bed Capacity - statistics & numerical data Humans Information Dissemination - methods Medical Informatics Pandemics - statistics & numerical data Real-world data SARS-CoV-2 |
title | Mind the clinical-analytic gap: Electronic health records and COVID-19 pandemic response |
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