How is the electronic health record being used? Use of EHR data to assess physician-level variability in technology use
Studies of the effects of electronic health records (EHRs) have had mixed findings, which may be attributable to unmeasured confounders such as individual variability in use of EHR features. To capture physician-level variations in use of EHR features, associations with other predictors, and usage i...
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Veröffentlicht in: | Journal of the American Medical Informatics Association : JAMIA 2014-11, Vol.21 (6), p.1001-1008 |
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creator | Ancker, Jessica S Kern, Lisa M Edwards, Alison Nosal, Sarah Stein, Daniel M Hauser, Diane Kaushal, Rainu |
description | Studies of the effects of electronic health records (EHRs) have had mixed findings, which may be attributable to unmeasured confounders such as individual variability in use of EHR features.
To capture physician-level variations in use of EHR features, associations with other predictors, and usage intensity over time.
Retrospective cohort study of primary care providers eligible for meaningful use at a network of federally qualified health centers, using commercial EHR data from January 2010 through June 2013, a period during which the organization was preparing for and in the early stages of meaningful use.
Data were analyzed for 112 physicians and nurse practitioners, consisting of 430,803 encounters with 99,649 patients. EHR usage metrics were developed to capture how providers accessed and added to patient data (eg, problem list updates), used clinical decision support (eg, responses to alerts), communicated (eg, printing after-visit summaries), and used panel management options (eg, viewed panel reports). Provider-level variability was high: for example, the annual average proportion of encounters with problem lists updated ranged from 5% to 60% per provider. Some metrics were associated with provider, patient, or encounter characteristics. For example, problem list updates were more likely for new patients than established ones, and alert acceptance was negatively correlated with alert frequency.
Providers using the same EHR developed personalized patterns of use of EHR features. We conclude that physician-level usage of EHR features may be a valuable additional predictor in research on the effects of EHRs on healthcare quality and costs. |
doi_str_mv | 10.1136/amiajnl-2013-002627 |
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To capture physician-level variations in use of EHR features, associations with other predictors, and usage intensity over time.
Retrospective cohort study of primary care providers eligible for meaningful use at a network of federally qualified health centers, using commercial EHR data from January 2010 through June 2013, a period during which the organization was preparing for and in the early stages of meaningful use.
Data were analyzed for 112 physicians and nurse practitioners, consisting of 430,803 encounters with 99,649 patients. EHR usage metrics were developed to capture how providers accessed and added to patient data (eg, problem list updates), used clinical decision support (eg, responses to alerts), communicated (eg, printing after-visit summaries), and used panel management options (eg, viewed panel reports). Provider-level variability was high: for example, the annual average proportion of encounters with problem lists updated ranged from 5% to 60% per provider. Some metrics were associated with provider, patient, or encounter characteristics. For example, problem list updates were more likely for new patients than established ones, and alert acceptance was negatively correlated with alert frequency.
Providers using the same EHR developed personalized patterns of use of EHR features. We conclude that physician-level usage of EHR features may be a valuable additional predictor in research on the effects of EHRs on healthcare quality and costs.</description><identifier>ISSN: 1067-5027</identifier><identifier>EISSN: 1527-974X</identifier><identifier>DOI: 10.1136/amiajnl-2013-002627</identifier><identifier>PMID: 24914013</identifier><language>eng</language><publisher>England: BMJ Publishing Group</publisher><subject>Adult ; Decision Making, Computer-Assisted ; Electronic Health Records - statistics & numerical data ; Electronic Health Records - utilization ; Female ; Humans ; Male ; Nurse Practitioners - statistics & numerical data ; Physicians, Primary Care - statistics & numerical data ; Research and Applications ; Retrospective Studies ; United States</subject><ispartof>Journal of the American Medical Informatics Association : JAMIA, 2014-11, Vol.21 (6), p.1001-1008</ispartof><rights>Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.</rights><rights>Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions 2014</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c541t-91c88f33bd2e5acbe95e67adc6f4c756969e4039aac2bc2497601b460f00336a3</citedby><cites>FETCH-LOGICAL-c541t-91c88f33bd2e5acbe95e67adc6f4c756969e4039aac2bc2497601b460f00336a3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4215048/pdf/$$EPDF$$P50$$Gpubmedcentral$$H</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4215048/$$EHTML$$P50$$Gpubmedcentral$$H</linktohtml><link.rule.ids>230,314,727,780,784,885,27924,27925,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/24914013$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Ancker, Jessica S</creatorcontrib><creatorcontrib>Kern, Lisa M</creatorcontrib><creatorcontrib>Edwards, Alison</creatorcontrib><creatorcontrib>Nosal, Sarah</creatorcontrib><creatorcontrib>Stein, Daniel M</creatorcontrib><creatorcontrib>Hauser, Diane</creatorcontrib><creatorcontrib>Kaushal, Rainu</creatorcontrib><creatorcontrib>HITEC Investigators</creatorcontrib><creatorcontrib>with the HITEC Investigators</creatorcontrib><title>How is the electronic health record being used? Use of EHR data to assess physician-level variability in technology use</title><title>Journal of the American Medical Informatics Association : JAMIA</title><addtitle>J Am Med Inform Assoc</addtitle><description>Studies of the effects of electronic health records (EHRs) have had mixed findings, which may be attributable to unmeasured confounders such as individual variability in use of EHR features.
To capture physician-level variations in use of EHR features, associations with other predictors, and usage intensity over time.
Retrospective cohort study of primary care providers eligible for meaningful use at a network of federally qualified health centers, using commercial EHR data from January 2010 through June 2013, a period during which the organization was preparing for and in the early stages of meaningful use.
Data were analyzed for 112 physicians and nurse practitioners, consisting of 430,803 encounters with 99,649 patients. EHR usage metrics were developed to capture how providers accessed and added to patient data (eg, problem list updates), used clinical decision support (eg, responses to alerts), communicated (eg, printing after-visit summaries), and used panel management options (eg, viewed panel reports). Provider-level variability was high: for example, the annual average proportion of encounters with problem lists updated ranged from 5% to 60% per provider. Some metrics were associated with provider, patient, or encounter characteristics. For example, problem list updates were more likely for new patients than established ones, and alert acceptance was negatively correlated with alert frequency.
Providers using the same EHR developed personalized patterns of use of EHR features. We conclude that physician-level usage of EHR features may be a valuable additional predictor in research on the effects of EHRs on healthcare quality and costs.</description><subject>Adult</subject><subject>Decision Making, Computer-Assisted</subject><subject>Electronic Health Records - statistics & numerical data</subject><subject>Electronic Health Records - utilization</subject><subject>Female</subject><subject>Humans</subject><subject>Male</subject><subject>Nurse Practitioners - statistics & numerical data</subject><subject>Physicians, Primary Care - statistics & numerical data</subject><subject>Research and Applications</subject><subject>Retrospective Studies</subject><subject>United States</subject><issn>1067-5027</issn><issn>1527-974X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNpVkU9rGzEQxZfSkqRpPkGh6NjLtvov76WlhKQuBAKlgd7ErHbWqyBLriQ7-Nt3jd3QnGZg3nszw69p3jP6iTGhP8Paw2MMLadMtJRyzc2r5oIpbtrOyN-v555q0yrKzXnztpRHSpnmQp0151x2TM62i-ZpmZ6IL6ROSDCgqzlF78iEEOpEMrqUB9KjjyuyLTh8JQ8FSRrJzfInGaACqYlAKVgK2Uz74p2H2AbcYSA7yB56H3zdEx9JRTfFFNJqf0h617wZIRS8OtXL5uH25tf1sr27__7j-ttd65Rkte2YWyxGIfqBowLXY6dQGxicHqUzSne6Q0lFB-B47-a3jKasl5qOlAqhQVw2X465m22_xsFhrBmC3WS_hry3Cbx9OYl-squ0s5IzReViDvh4CsjpzxZLtWtfHIYAEdO2WKYZNVoIJWepOEpdTqVkHJ_XMGoPyOwJmT0gs0dks-vD_xc-e_4xEn8BGkKWVQ</recordid><startdate>20141101</startdate><enddate>20141101</enddate><creator>Ancker, Jessica S</creator><creator>Kern, Lisa M</creator><creator>Edwards, Alison</creator><creator>Nosal, Sarah</creator><creator>Stein, Daniel M</creator><creator>Hauser, Diane</creator><creator>Kaushal, Rainu</creator><general>BMJ Publishing Group</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>7X8</scope><scope>5PM</scope></search><sort><creationdate>20141101</creationdate><title>How is the electronic health record being used? Use of EHR data to assess physician-level variability in technology use</title><author>Ancker, Jessica S ; Kern, Lisa M ; Edwards, Alison ; Nosal, Sarah ; Stein, Daniel M ; Hauser, Diane ; Kaushal, Rainu</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c541t-91c88f33bd2e5acbe95e67adc6f4c756969e4039aac2bc2497601b460f00336a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Adult</topic><topic>Decision Making, Computer-Assisted</topic><topic>Electronic Health Records - statistics & numerical data</topic><topic>Electronic Health Records - utilization</topic><topic>Female</topic><topic>Humans</topic><topic>Male</topic><topic>Nurse Practitioners - statistics & numerical data</topic><topic>Physicians, Primary Care - statistics & numerical data</topic><topic>Research and Applications</topic><topic>Retrospective Studies</topic><topic>United States</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ancker, Jessica S</creatorcontrib><creatorcontrib>Kern, Lisa M</creatorcontrib><creatorcontrib>Edwards, Alison</creatorcontrib><creatorcontrib>Nosal, Sarah</creatorcontrib><creatorcontrib>Stein, Daniel M</creatorcontrib><creatorcontrib>Hauser, Diane</creatorcontrib><creatorcontrib>Kaushal, Rainu</creatorcontrib><creatorcontrib>HITEC Investigators</creatorcontrib><creatorcontrib>with the HITEC Investigators</creatorcontrib><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 the American Medical Informatics Association : JAMIA</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ancker, Jessica S</au><au>Kern, Lisa M</au><au>Edwards, Alison</au><au>Nosal, Sarah</au><au>Stein, Daniel M</au><au>Hauser, Diane</au><au>Kaushal, Rainu</au><aucorp>HITEC Investigators</aucorp><aucorp>with the HITEC Investigators</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>How is the electronic health record being used? Use of EHR data to assess physician-level variability in technology use</atitle><jtitle>Journal of the American Medical Informatics Association : JAMIA</jtitle><addtitle>J Am Med Inform Assoc</addtitle><date>2014-11-01</date><risdate>2014</risdate><volume>21</volume><issue>6</issue><spage>1001</spage><epage>1008</epage><pages>1001-1008</pages><issn>1067-5027</issn><eissn>1527-974X</eissn><abstract>Studies of the effects of electronic health records (EHRs) have had mixed findings, which may be attributable to unmeasured confounders such as individual variability in use of EHR features.
To capture physician-level variations in use of EHR features, associations with other predictors, and usage intensity over time.
Retrospective cohort study of primary care providers eligible for meaningful use at a network of federally qualified health centers, using commercial EHR data from January 2010 through June 2013, a period during which the organization was preparing for and in the early stages of meaningful use.
Data were analyzed for 112 physicians and nurse practitioners, consisting of 430,803 encounters with 99,649 patients. EHR usage metrics were developed to capture how providers accessed and added to patient data (eg, problem list updates), used clinical decision support (eg, responses to alerts), communicated (eg, printing after-visit summaries), and used panel management options (eg, viewed panel reports). Provider-level variability was high: for example, the annual average proportion of encounters with problem lists updated ranged from 5% to 60% per provider. Some metrics were associated with provider, patient, or encounter characteristics. For example, problem list updates were more likely for new patients than established ones, and alert acceptance was negatively correlated with alert frequency.
Providers using the same EHR developed personalized patterns of use of EHR features. We conclude that physician-level usage of EHR features may be a valuable additional predictor in research on the effects of EHRs on healthcare quality and costs.</abstract><cop>England</cop><pub>BMJ Publishing Group</pub><pmid>24914013</pmid><doi>10.1136/amiajnl-2013-002627</doi><tpages>8</tpages><oa>free_for_read</oa></addata></record> |
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source | Oxford University Press Journals All Titles (1996-Current); MEDLINE; EZB-FREE-00999 freely available EZB journals; PubMed Central |
subjects | Adult Decision Making, Computer-Assisted Electronic Health Records - statistics & numerical data Electronic Health Records - utilization Female Humans Male Nurse Practitioners - statistics & numerical data Physicians, Primary Care - statistics & numerical data Research and Applications Retrospective Studies United States |
title | How is the electronic health record being used? Use of EHR data to assess physician-level variability in technology use |
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