Improving the quality of EHR recording in primary care: a data quality feedback tool
Objective: Electronic health record (EHR) data are used to exchange information among health care providers. For this purpose, the quality of the data is essential. We developed a data quality feedback tool that evaluates differences in EHR data quality among practices and software packages as part...
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Veröffentlicht in: | Journal of the American Medical Informatics Association : JAMIA 2017-01, Vol.24 (1), p.81-87 |
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creator | van der Bij, Sjoukje Khan, Nasra ten Veen, Petra de Bakker, Dinny H Verheij, Robert A |
description | Objective: Electronic health record (EHR) data are used to exchange information among health care providers. For this purpose, the quality of the data is essential. We developed a data quality feedback tool that evaluates differences in EHR data quality among practices and software packages as part of a larger intervention.
Methods: The tool was applied in 92 practices in the Netherlands using different software packages. Practices received data quality feedback in 2010 and 2012.
Results: We observed large differences in the quality of recording. For example, the percentage of episodes of care that had a meaningful diagnostic code ranged from 30% to 100%. Differences were highly related to the software package. A year after the first measurement, the quality of recording had improved significantly and differences decreased, with 67% of the physicians indicating that they had actively changed their recording habits based on the results of the first measurement. About 80% found the feedback helpful in pinpointing recording problems. One of the software vendors made changes in functionality as a result of the feedback.
Conclusions: Our EHR data quality feedback tool is capable of highlighting differences among practices and software packages. As such, it also stimulates improvements. As substantial variability in recording is related to the software package, our study strengthens the evidence that data quality can be improved substantially by standardizing the functionalities of EHR software packages. |
doi_str_mv | 10.1093/jamia/ocw054 |
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Methods: The tool was applied in 92 practices in the Netherlands using different software packages. Practices received data quality feedback in 2010 and 2012.
Results: We observed large differences in the quality of recording. For example, the percentage of episodes of care that had a meaningful diagnostic code ranged from 30% to 100%. Differences were highly related to the software package. A year after the first measurement, the quality of recording had improved significantly and differences decreased, with 67% of the physicians indicating that they had actively changed their recording habits based on the results of the first measurement. About 80% found the feedback helpful in pinpointing recording problems. One of the software vendors made changes in functionality as a result of the feedback.
Conclusions: Our EHR data quality feedback tool is capable of highlighting differences among practices and software packages. As such, it also stimulates improvements. As substantial variability in recording is related to the software package, our study strengthens the evidence that data quality can be improved substantially by standardizing the functionalities of EHR software packages.</description><identifier>ISSN: 1067-5027</identifier><identifier>ISSN: 1527-974X</identifier><identifier>EISSN: 1527-974X</identifier><identifier>DOI: 10.1093/jamia/ocw054</identifier><identifier>PMID: 27274019</identifier><language>eng</language><publisher>England: Oxford University Press</publisher><subject>Clinical Coding - standards ; Data Accuracy ; Electronic Health Records - standards ; Feedback ; Humans ; Medical Records Systems, Computerized ; Netherlands ; Practice Patterns, Physicians ; Primary Health Care ; Quality of Health Care ; Research and Applications ; Software</subject><ispartof>Journal of the American Medical Informatics Association : JAMIA, 2017-01, Vol.24 (1), p.81-87</ispartof><rights>The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com 2016</rights><rights>The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c416t-933013aa1272d750d9c5e87863d4b2c1861079ab8ca9f9f27a3d5cbca53318b03</citedby><cites>FETCH-LOGICAL-c416t-933013aa1272d750d9c5e87863d4b2c1861079ab8ca9f9f27a3d5cbca53318b03</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/PMC7654082/pdf/$$EPDF$$P50$$Gpubmedcentral$$H</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7654082/$$EHTML$$P50$$Gpubmedcentral$$H</linktohtml><link.rule.ids>230,314,727,780,784,885,1584,27924,27925,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/27274019$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>van der Bij, Sjoukje</creatorcontrib><creatorcontrib>Khan, Nasra</creatorcontrib><creatorcontrib>ten Veen, Petra</creatorcontrib><creatorcontrib>de Bakker, Dinny H</creatorcontrib><creatorcontrib>Verheij, Robert A</creatorcontrib><title>Improving the quality of EHR recording in primary care: a data quality feedback tool</title><title>Journal of the American Medical Informatics Association : JAMIA</title><addtitle>J Am Med Inform Assoc</addtitle><description>Objective: Electronic health record (EHR) data are used to exchange information among health care providers. For this purpose, the quality of the data is essential. We developed a data quality feedback tool that evaluates differences in EHR data quality among practices and software packages as part of a larger intervention.
Methods: The tool was applied in 92 practices in the Netherlands using different software packages. Practices received data quality feedback in 2010 and 2012.
Results: We observed large differences in the quality of recording. For example, the percentage of episodes of care that had a meaningful diagnostic code ranged from 30% to 100%. Differences were highly related to the software package. A year after the first measurement, the quality of recording had improved significantly and differences decreased, with 67% of the physicians indicating that they had actively changed their recording habits based on the results of the first measurement. About 80% found the feedback helpful in pinpointing recording problems. One of the software vendors made changes in functionality as a result of the feedback.
Conclusions: Our EHR data quality feedback tool is capable of highlighting differences among practices and software packages. As such, it also stimulates improvements. As substantial variability in recording is related to the software package, our study strengthens the evidence that data quality can be improved substantially by standardizing the functionalities of EHR software packages.</description><subject>Clinical Coding - standards</subject><subject>Data Accuracy</subject><subject>Electronic Health Records - standards</subject><subject>Feedback</subject><subject>Humans</subject><subject>Medical Records Systems, Computerized</subject><subject>Netherlands</subject><subject>Practice Patterns, Physicians</subject><subject>Primary Health Care</subject><subject>Quality of Health Care</subject><subject>Research and Applications</subject><subject>Software</subject><issn>1067-5027</issn><issn>1527-974X</issn><issn>1527-974X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kc1LxDAQxYMorq7ePEtuerBuPpqm8SDIsuqCIIiCtzBNU622TU3blf3v7dp10YunGZjfvHnMQ-iIknNKFJ-8QZnDxJlPIsIttEcFk4GS4fN235NIBoIwOUL7TfNGCI0YF7toxCSTIaFqDz3Oy9q7RV694PbV4o8OirxdYpfh2e0D9tY4n66GeYVrn5fgl9iAtxcYcAotbBYya9MEzDtunSsO0E4GRWMP13WMnq5nj9Pb4O7-Zj69ugtMSKM2UJwTygFobyeVgqTKCBvLOOJpmDBD44gSqSCJDahMZUwCT4VJDAjOaZwQPkaXg27dJaVNja1aD4VeG9UOcv13UuWv-sUttIxESGLWC5yuBbz76GzT6jJvjC0KqKzrGk1jFkWKxaHo0bMBNd41jbfZ5gwlehWE_g5CD0H0-PFvaxv45_M9cDIArqv_l_oCv8iT0A</recordid><startdate>20170101</startdate><enddate>20170101</enddate><creator>van der Bij, Sjoukje</creator><creator>Khan, Nasra</creator><creator>ten Veen, Petra</creator><creator>de Bakker, Dinny H</creator><creator>Verheij, Robert A</creator><general>Oxford University Press</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>20170101</creationdate><title>Improving the quality of EHR recording in primary care: a data quality feedback tool</title><author>van der Bij, Sjoukje ; Khan, Nasra ; ten Veen, Petra ; de Bakker, Dinny H ; Verheij, Robert A</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c416t-933013aa1272d750d9c5e87863d4b2c1861079ab8ca9f9f27a3d5cbca53318b03</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Clinical Coding - standards</topic><topic>Data Accuracy</topic><topic>Electronic Health Records - standards</topic><topic>Feedback</topic><topic>Humans</topic><topic>Medical Records Systems, Computerized</topic><topic>Netherlands</topic><topic>Practice Patterns, Physicians</topic><topic>Primary Health Care</topic><topic>Quality of Health Care</topic><topic>Research and Applications</topic><topic>Software</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>van der Bij, Sjoukje</creatorcontrib><creatorcontrib>Khan, Nasra</creatorcontrib><creatorcontrib>ten Veen, Petra</creatorcontrib><creatorcontrib>de Bakker, Dinny H</creatorcontrib><creatorcontrib>Verheij, Robert A</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>van der Bij, Sjoukje</au><au>Khan, Nasra</au><au>ten Veen, Petra</au><au>de Bakker, Dinny H</au><au>Verheij, Robert A</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Improving the quality of EHR recording in primary care: a data quality feedback tool</atitle><jtitle>Journal of the American Medical Informatics Association : JAMIA</jtitle><addtitle>J Am Med Inform Assoc</addtitle><date>2017-01-01</date><risdate>2017</risdate><volume>24</volume><issue>1</issue><spage>81</spage><epage>87</epage><pages>81-87</pages><issn>1067-5027</issn><issn>1527-974X</issn><eissn>1527-974X</eissn><abstract>Objective: Electronic health record (EHR) data are used to exchange information among health care providers. For this purpose, the quality of the data is essential. We developed a data quality feedback tool that evaluates differences in EHR data quality among practices and software packages as part of a larger intervention.
Methods: The tool was applied in 92 practices in the Netherlands using different software packages. Practices received data quality feedback in 2010 and 2012.
Results: We observed large differences in the quality of recording. For example, the percentage of episodes of care that had a meaningful diagnostic code ranged from 30% to 100%. Differences were highly related to the software package. A year after the first measurement, the quality of recording had improved significantly and differences decreased, with 67% of the physicians indicating that they had actively changed their recording habits based on the results of the first measurement. About 80% found the feedback helpful in pinpointing recording problems. One of the software vendors made changes in functionality as a result of the feedback.
Conclusions: Our EHR data quality feedback tool is capable of highlighting differences among practices and software packages. As such, it also stimulates improvements. As substantial variability in recording is related to the software package, our study strengthens the evidence that data quality can be improved substantially by standardizing the functionalities of EHR software packages.</abstract><cop>England</cop><pub>Oxford University Press</pub><pmid>27274019</pmid><doi>10.1093/jamia/ocw054</doi><tpages>7</tpages><oa>free_for_read</oa></addata></record> |
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source | MEDLINE; Oxford University Press Journals All Titles (1996-Current); EZB-FREE-00999 freely available EZB journals; PubMed Central |
subjects | Clinical Coding - standards Data Accuracy Electronic Health Records - standards Feedback Humans Medical Records Systems, Computerized Netherlands Practice Patterns, Physicians Primary Health Care Quality of Health Care Research and Applications Software |
title | Improving the quality of EHR recording in primary care: a data quality feedback tool |
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