{"id":2067,"date":"2023-02-07T18:54:56","date_gmt":"2023-02-07T18:54:56","guid":{"rendered":"https:\/\/meetings.informs.org\/wordpress\/analytics2023\/speakers\/david-hampton-copy\/"},"modified":"2023-02-07T19:08:47","modified_gmt":"2023-02-07T19:08:47","slug":"molli-sanocki","status":"publish","type":"page","link":"https:\/\/meetings.informs.org\/wordpress\/analytics2023\/speakers\/molli-sanocki\/","title":{"rendered":"Molli Sanocki"},"content":{"rendered":"\n
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Molli Sanocki<\/h1>\n

Head of Healthcare Analytics at LexisNexis Risk Solutions<\/span><\/h1>\n
Dr. Molli Sanocki currently leads a team of data scientists at LexisNexis Risk Solutions that is focused on development of models, improvement of data quality, and research and development.  The Healthcare division supports a broad portfolio of products built on socio-economic, provider, and deidentified claims data.  Molli has ten years of experience in developing models using deidentified patient data, primarily focused on life-science use cases.  Her educational background is a combination of Mathematics, Computer Science, and Statistics, and, prior to her work in the Healthcare industry, she was a university professor.  Throughout her career, Molli has devoted her time to mentorship, leadership development, and fostering an inclusive workplace.  <\/div><\/div> <\/div>\n<\/div>\n <\/div>\n <\/div>\n <\/div>\n
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Executive<\/p> <\/div>\n<\/div>\n\n

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Track: Life Science & Healthcare<\/h6> <\/div>\n<\/div>\n\n
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Meeting the Challenges of Secondary Use of Patient Data<\/h2>\n

Obtaining a full picture of a patient often involves several health-related datasets in addition to insights into the aspects of a patient\u2019s life outside of their health records.  Over time, patients move, change jobs, change insurance coverage, and even change names.  Unfortunately, the more information that is added to a deidentified patient record, the greater the risk of reidentification.  Based on all of these challenges, what techniques can be used to create an effective dataset that protects a patient\u2019s privacy and provides the essential information to answer the specific research questions?  In this talk, we will explore our approach to the creation of a referential patient token that allows more accurate tracking across life events, our methods for using this token to combine various real-world data assets, and our approach to expert determination to ensure that the dataset produced protects a patient\u2019s privacy while still meeting the needs of the researcher. <\/p> <\/div>\n<\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n","protected":false},"excerpt":{"rendered":"

Molli Sanocki Molli Sanocki Head of Healthcare Analytics at LexisNexis Risk Solutions Dr. Molli Sanocki currently leads a team of data scientists at LexisNexis Risk Solutions that is focused on development of models, improvement of data quality, and research and development.  The Healthcare division supports a broad portfolio of products built on socio-economic, provider, and […]<\/p>\n","protected":false},"author":1001094,"featured_media":2048,"parent":712,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"content-type":"","footnotes":""},"class_list":["post-2067","page","type-page","status-publish","has-post-thumbnail","hentry","has-post-title","has-post-date","has-post-category","has-post-tag","has-post-comment","has-post-author",""],"acf":[],"yoast_head":"\nMolli Sanocki - 2023 INFORMS Business Analytics Conference<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, 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src=\"\/wordpress\/analytics2023\/files\/2023\/02\/Molli_Sanocki.jpg\" title=\"Molli Sanocki\" alt=\"Molli Sanocki headshot\"> <h3> Molli Sanocki <\/h3>\n<h1>Molli Sanocki<\/h1> <h1>Head of Healthcare Analytics at LexisNexis Risk Solutions<\/h1> Dr. Molli Sanocki currently leads a team of data scientists at LexisNexis Risk Solutions that is focused on development of models, improvement of data quality, and research and development.  The Healthcare division supports a broad portfolio of products built on socio-economic, provider, and deidentified claims data.  Molli has ten years of experience in developing models using deidentified patient data, primarily focused on life-science use cases.  Her educational background is a combination of Mathematics, Computer Science, and Statistics, and, prior to her work in the Healthcare industry, she was a university professor.  Throughout her career, Molli has devoted her time to mentorship, leadership development, and fostering an inclusive workplace.  \n<p>Executive<\/p>\n<h6>Track: Life Science & Healthcare<\/h6>\n<h2>Meeting the Challenges of Secondary Use of Patient Data<\/h2> <p>Obtaining a full picture of a patient often involves several health-related datasets in addition to insights into the aspects of a patient\u2019s life outside of their health records.  Over time, patients move, change jobs, change insurance coverage, and even change names.  Unfortunately, the more information that is added to a deidentified patient record, the greater the risk of reidentification.  Based on all of these challenges, what techniques can be used to create an effective dataset that protects a patient\u2019s privacy and provides the essential information to answer the specific research questions?  In this talk, we will explore our approach to the creation of a referential patient token that allows more accurate tracking across life events, our methods for using this token to combine various real-world data assets, and our approach to expert determination to ensure that the dataset produced protects a patient\u2019s privacy while still meeting the needs of the researcher. <\/p>","_links":{"self":[{"href":"https:\/\/meetings.informs.org\/wordpress\/analytics2023\/wp-json\/wp\/v2\/pages\/2067","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/meetings.informs.org\/wordpress\/analytics2023\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/meetings.informs.org\/wordpress\/analytics2023\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/meetings.informs.org\/wordpress\/analytics2023\/wp-json\/wp\/v2\/users\/1001094"}],"replies":[{"embeddable":true,"href":"https:\/\/meetings.informs.org\/wordpress\/analytics2023\/wp-json\/wp\/v2\/comments?post=2067"}],"version-history":[{"count":8,"href":"https:\/\/meetings.informs.org\/wordpress\/analytics2023\/wp-json\/wp\/v2\/pages\/2067\/revisions"}],"predecessor-version":[{"id":2078,"href":"https:\/\/meetings.informs.org\/wordpress\/analytics2023\/wp-json\/wp\/v2\/pages\/2067\/revisions\/2078"}],"up":[{"embeddable":true,"href":"https:\/\/meetings.informs.org\/wordpress\/analytics2023\/wp-json\/wp\/v2\/pages\/712"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/meetings.informs.org\/wordpress\/analytics2023\/wp-json\/wp\/v2\/media\/2048"}],"wp:attachment":[{"href":"https:\/\/meetings.informs.org\/wordpress\/analytics2023\/wp-json\/wp\/v2\/media?parent=2067"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}