Automatic Genetic Risk Assessment Calculation Using Breast Cancer Family History Data from the EHR compared to Self-Report
Genetic testing is a method to assess hereditary cancer risk. However, it is under-utilized and various methods of family history intake have been evaluated in previous studies. The six-point-scale (SPS) is a validated family history screener that is used to determine eligibility for BRCA genetic co...
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| Veröffentlicht in: | AMIA ... Annual Symposium proceedings 2018, Vol.2018, p.970-978 |
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| creator | Sin, Margaret McGuinness, Julia E Trivedi, Meghna S Vanegas, Alejandro Silverman, Thomas B Crew, Katherine D Kukafka, Rita |
| description | Genetic testing is a method to assess hereditary cancer risk. However, it is under-utilized and various methods of family history intake have been evaluated in previous studies. The six-point-scale (SPS) is a validated family history screener that is used to determine eligibility for BRCA genetic counseling. We automated the calculation of the SPS score using structured family history data along with free text from the electronic health record (EHR) to detect detailed family history information of breast cancer. We extracted data for all women aged 35 to 74 who had screening mammography at Columbia University Medical Center (CUMC) from January 2015 to May 2017 (N=37,596). After we calculated SPS scores using structured and free-text EHR data, we compared the results with SPS score calculated from a baseline survey conducted for a prospective study called Know Your Risks: Assessment at Screening (KYRAS). Among 1,202 patients with EHR structured family history data, we found 1.43% had an SPS score of 6 higher which meets criteria for genetic counseling referral, while 12.05% of the survey respondents had SPS score of 6 or higher. Results show there is a need for more efficient methods to identify patients eligible for genetic counseling through EHR analysis. |
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However, it is under-utilized and various methods of family history intake have been evaluated in previous studies. The six-point-scale (SPS) is a validated family history screener that is used to determine eligibility for BRCA genetic counseling. We automated the calculation of the SPS score using structured family history data along with free text from the electronic health record (EHR) to detect detailed family history information of breast cancer. We extracted data for all women aged 35 to 74 who had screening mammography at Columbia University Medical Center (CUMC) from January 2015 to May 2017 (N=37,596). After we calculated SPS scores using structured and free-text EHR data, we compared the results with SPS score calculated from a baseline survey conducted for a prospective study called Know Your Risks: Assessment at Screening (KYRAS). Among 1,202 patients with EHR structured family history data, we found 1.43% had an SPS score of 6 higher which meets criteria for genetic counseling referral, while 12.05% of the survey respondents had SPS score of 6 or higher. Results show there is a need for more efficient methods to identify patients eligible for genetic counseling through EHR analysis.</description><identifier>ISSN: 1942-597X</identifier><identifier>EISSN: 1559-4076</identifier><identifier>PMID: 30815140</identifier><language>eng</language><publisher>United States: American Medical Informatics Association</publisher><subject>Adult ; Aged ; Breast Neoplasms - genetics ; Breast Neoplasms, Male - genetics ; Early Detection of Cancer ; Electronic Health Records ; Eligibility Determination ; Female ; Genetic Counseling ; Genetic Testing ; Humans ; Male ; Mammography ; Medical History Taking ; Middle Aged ; Prospective Studies ; Referral and Consultation ; Risk Assessment - methods ; Risk Factors ; Self Report ; Surveys and Questionnaires</subject><ispartof>AMIA ... Annual Symposium proceedings, 2018, Vol.2018, p.970-978</ispartof><rights>2018 AMIA - All rights reserved. 2018</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371348/pdf/$$EPDF$$P50$$Gpubmedcentral$$H</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371348/$$EHTML$$P50$$Gpubmedcentral$$H</linktohtml><link.rule.ids>230,314,727,780,784,885,4024,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/30815140$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Sin, Margaret</creatorcontrib><creatorcontrib>McGuinness, Julia E</creatorcontrib><creatorcontrib>Trivedi, Meghna S</creatorcontrib><creatorcontrib>Vanegas, Alejandro</creatorcontrib><creatorcontrib>Silverman, Thomas B</creatorcontrib><creatorcontrib>Crew, Katherine D</creatorcontrib><creatorcontrib>Kukafka, Rita</creatorcontrib><title>Automatic Genetic Risk Assessment Calculation Using Breast Cancer Family History Data from the EHR compared to Self-Report</title><title>AMIA ... Annual Symposium proceedings</title><addtitle>AMIA Annu Symp Proc</addtitle><description>Genetic testing is a method to assess hereditary cancer risk. However, it is under-utilized and various methods of family history intake have been evaluated in previous studies. The six-point-scale (SPS) is a validated family history screener that is used to determine eligibility for BRCA genetic counseling. We automated the calculation of the SPS score using structured family history data along with free text from the electronic health record (EHR) to detect detailed family history information of breast cancer. We extracted data for all women aged 35 to 74 who had screening mammography at Columbia University Medical Center (CUMC) from January 2015 to May 2017 (N=37,596). After we calculated SPS scores using structured and free-text EHR data, we compared the results with SPS score calculated from a baseline survey conducted for a prospective study called Know Your Risks: Assessment at Screening (KYRAS). Among 1,202 patients with EHR structured family history data, we found 1.43% had an SPS score of 6 higher which meets criteria for genetic counseling referral, while 12.05% of the survey respondents had SPS score of 6 or higher. Results show there is a need for more efficient methods to identify patients eligible for genetic counseling through EHR analysis.</description><subject>Adult</subject><subject>Aged</subject><subject>Breast Neoplasms - genetics</subject><subject>Breast Neoplasms, Male - genetics</subject><subject>Early Detection of Cancer</subject><subject>Electronic Health Records</subject><subject>Eligibility Determination</subject><subject>Female</subject><subject>Genetic Counseling</subject><subject>Genetic Testing</subject><subject>Humans</subject><subject>Male</subject><subject>Mammography</subject><subject>Medical History Taking</subject><subject>Middle Aged</subject><subject>Prospective Studies</subject><subject>Referral and Consultation</subject><subject>Risk Assessment - methods</subject><subject>Risk Factors</subject><subject>Self Report</subject><subject>Surveys and Questionnaires</subject><issn>1942-597X</issn><issn>1559-4076</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNpVkN9LwzAcxIsobk7_BcmjL4WkSZr2RZhzPwRBmA58K2n67Yy2SU1SYf71djhFn-7gjs_BHUVjwnkeMyzS48HnLIl5Lp5H0Zn3rxgzwbP0NBpRnBFOGB5Hn9M-2FYGrdASDOx1rf0bmnoP3rdgAprJRvXNULEGbbw2W3TjQPp9YBQ4tJCtbnZopX2wboduZZCodrZF4QXQfLVGyraddFChYNEjNHW8hs66cB6d1LLxcHHQSbRZzJ9mq_j-YXk3m97HHclIiEsqBGaVgjKreMUZEbnM8pTjElNGuUh4yhVNyiznda0qoWpVQklTyFmFExB0El1_c7u-bGEAmeBkU3ROt9LtCit18T8x-qXY2o8ipYJQlg2AqwPA2fcefCha7RU0jTRge18kJBM4SRmlQ_Xy79bvyM_h9AsXF3_D</recordid><startdate>2018</startdate><enddate>2018</enddate><creator>Sin, Margaret</creator><creator>McGuinness, Julia E</creator><creator>Trivedi, Meghna S</creator><creator>Vanegas, Alejandro</creator><creator>Silverman, Thomas B</creator><creator>Crew, Katherine D</creator><creator>Kukafka, Rita</creator><general>American Medical Informatics Association</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>2018</creationdate><title>Automatic Genetic Risk Assessment Calculation Using Breast Cancer Family History Data from the EHR compared to Self-Report</title><author>Sin, Margaret ; McGuinness, Julia E ; Trivedi, Meghna S ; Vanegas, Alejandro ; Silverman, Thomas B ; Crew, Katherine D ; Kukafka, Rita</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-p181t-b37704dceb8d5d54179a89650b0343572565c32b895ffcd7cfcbeb36e94d02e73</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Adult</topic><topic>Aged</topic><topic>Breast Neoplasms - genetics</topic><topic>Breast Neoplasms, Male - genetics</topic><topic>Early Detection of Cancer</topic><topic>Electronic Health Records</topic><topic>Eligibility Determination</topic><topic>Female</topic><topic>Genetic Counseling</topic><topic>Genetic Testing</topic><topic>Humans</topic><topic>Male</topic><topic>Mammography</topic><topic>Medical History Taking</topic><topic>Middle Aged</topic><topic>Prospective Studies</topic><topic>Referral and Consultation</topic><topic>Risk Assessment - methods</topic><topic>Risk Factors</topic><topic>Self Report</topic><topic>Surveys and Questionnaires</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Sin, Margaret</creatorcontrib><creatorcontrib>McGuinness, Julia E</creatorcontrib><creatorcontrib>Trivedi, Meghna S</creatorcontrib><creatorcontrib>Vanegas, Alejandro</creatorcontrib><creatorcontrib>Silverman, Thomas B</creatorcontrib><creatorcontrib>Crew, Katherine D</creatorcontrib><creatorcontrib>Kukafka, Rita</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>AMIA ... Annual Symposium proceedings</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Sin, Margaret</au><au>McGuinness, Julia E</au><au>Trivedi, Meghna S</au><au>Vanegas, Alejandro</au><au>Silverman, Thomas B</au><au>Crew, Katherine D</au><au>Kukafka, Rita</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Automatic Genetic Risk Assessment Calculation Using Breast Cancer Family History Data from the EHR compared to Self-Report</atitle><jtitle>AMIA ... Annual Symposium proceedings</jtitle><addtitle>AMIA Annu Symp Proc</addtitle><date>2018</date><risdate>2018</risdate><volume>2018</volume><spage>970</spage><epage>978</epage><pages>970-978</pages><issn>1942-597X</issn><eissn>1559-4076</eissn><abstract>Genetic testing is a method to assess hereditary cancer risk. However, it is under-utilized and various methods of family history intake have been evaluated in previous studies. The six-point-scale (SPS) is a validated family history screener that is used to determine eligibility for BRCA genetic counseling. We automated the calculation of the SPS score using structured family history data along with free text from the electronic health record (EHR) to detect detailed family history information of breast cancer. We extracted data for all women aged 35 to 74 who had screening mammography at Columbia University Medical Center (CUMC) from January 2015 to May 2017 (N=37,596). After we calculated SPS scores using structured and free-text EHR data, we compared the results with SPS score calculated from a baseline survey conducted for a prospective study called Know Your Risks: Assessment at Screening (KYRAS). Among 1,202 patients with EHR structured family history data, we found 1.43% had an SPS score of 6 higher which meets criteria for genetic counseling referral, while 12.05% of the survey respondents had SPS score of 6 or higher. Results show there is a need for more efficient methods to identify patients eligible for genetic counseling through EHR analysis.</abstract><cop>United States</cop><pub>American Medical Informatics Association</pub><pmid>30815140</pmid><tpages>9</tpages></addata></record> |
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| source | MEDLINE; EZB-FREE-00999 freely available EZB journals; PubMed Central |
| subjects | Adult Aged Breast Neoplasms - genetics Breast Neoplasms, Male - genetics Early Detection of Cancer Electronic Health Records Eligibility Determination Female Genetic Counseling Genetic Testing Humans Male Mammography Medical History Taking Middle Aged Prospective Studies Referral and Consultation Risk Assessment - methods Risk Factors Self Report Surveys and Questionnaires |
| title | Automatic Genetic Risk Assessment Calculation Using Breast Cancer Family History Data from the EHR compared to Self-Report |
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