[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-292201-105":59,"doc-detail-292201-en":131},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":60,"data":61},"ok",{"site_id":62,"language":63,"slug":64,"title":65,"keywords":66,"description":67,"schema_data":68,"social_meta":124,"head_meta":126,"extra_data":128,"updated_unix":130},105,"en","prevalence-and-evaluation-of-potential-abbreviations-in-intensive-care-documentation-dissertation","Prevalence and Evaluation of Potential Abbreviations in Intensive Care Documentation - Dissertation","","Abbreviations are widely used in clinical documentation to reduce time and conserve space in electronic health records, but their ambiguous meanings create patient-safety risks for clinicians and health-literacy barriers for patients interpreting provider notes. A semi-supervised approach was used to identify potential abbreviations in the MIMIC-III dataset by comparing over 400 million-word tokens to a Beth Israel Deaconess Hospital approved list. Results show 463,175,566 raw tokens matched against 1,742 abbreviations, with notable variation across RN and MD documentation. Medrec2vec embeddings were also used to extract semantic relationships for many approved terms.",{"@graph":69,"@context":123},[70,84,106],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/prevalence-and-evaluation-of-potential-abbreviations-in-intensive-care-documentation-dissertation/292201/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/prevalence-and-evaluation-of-potential-abbreviations-in-intensive-care-documentation-dissertation/292201.png","ImageObject",300,407,{"name":92,"@type":93},"Arica Lee","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-18","2026-09-17",true,{"@type":102,"interactionType":103,"userInteractionCount":105},"InteractionCounter",{"@type":104},"ViewAction",11,{"@type":107,"mainEntity":108},"FAQPage",[109,115,119],{"name":110,"@type":111,"acceptedAnswer":112},"Why are abbreviations considered a patient-safety and health-literacy concern in clinical documentation?","Question",{"text":113,"@type":114},"Abbreviations can have multiple meanings, so clinicians may misunderstand intended usage, creating patient-safety risks. Patients also face difficulties interpreting provider notes when abbreviations are ambiguous.","Answer",{"name":116,"@type":111,"acceptedAnswer":117},"How were potential abbreviations identified in the MIMIC-III database?",{"text":118,"@type":114},"A semi-supervised method compared more than 400 million-word tokens in MIMIC-III to a list of abbreviations approved by Beth Israel Deaconess Hospital.",{"name":120,"@type":111,"acceptedAnswer":121},"What differences in abbreviation usage were observed between RN-created and MD-created notes?",{"text":122,"@type":114},"The average count of potential abbreviations differed by clinician type, with RN notes averaging 21.87 and MD notes averaging 11.39, indicating a substantial difference in usage patterns.","https://schema.org",{"og:url":83,"og:type":125,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":127,"canonical":83},"index,follow",{"doc_id":129,"site_id":62},292201,1789648968,{"code":4,"msg":5,"data":132},{"doc_id":129,"user_id":133,"nickname":92,"user_avatar":134,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":135,"file_id":136,"file_url":137,"file_type":138,"file_size":139,"view_count":105,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":140,"language":141,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":142,"faqs":143,"seo_title":144,"seo_description":67,"update_tm":130,"read_time":145,"preview_page_count":4},8796096645457,"https://ap-avatar.wpscdn.com/avatar/800003749518d68ffe3?x-image-process=image/resize,m_fixed,w_180,h_180&k=1779345340919836971","Prevalence and Evaluation of Potential Abbreviationsin Intensive Care Documentation  \nA Clinical Language Exploration, Annotation Research: Utilizing Open Source and Commercial  \nApplications  \nBy  \nDavid M. Brundage  \nA Dissertation Submitted  \nin Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy in  \nBiomedical Informatics  \nDepartment of Health Informatics School of Health Professions Rutgers, the State University of New Jersey  \nNovember 2019  \nFinal Dissertation Defense Approval Form  \nPrevalence and Evaluation of Potential Abbreviations in Intensive Care  \nDocumentation  \nBY  \nDavid Brundage  \nDissertation Committee:  \nShankar Srinivasan PhD  \nFrederick Coffman PhD  \nSuril Gohel PhD  \nApproved by the Dissertation Committee:  \nDate:  \nDate:  \nDate:  \nDate:  \nDate:  \n|  |\n| --- |\n|  |\n\nTABLE OF CONTENTS  \nAbstract……………………………………………………………..............5  \nAcknowledgement………………………………………………………..... 7  \nList of Tables………………………………………………………………. 8  \nList of Figures………………………………………………………………9  \n1.0 Introduction……………………………………………………………….10  \n1.1 Background of the Problem………………………………………............... 10  \n1.2 Statement of the Problem…………………….…………………..................12  \n1.3 Research Objective………………………………………………………….14  \n1.4 Need & Rationale …………………………………………………..............15  \n1.5 Research Hypothesis……………………………………………...................15  \n2.0 Literature Review…………………………………..……………...………17  \n2.1 Literature Search and Search String……………………………………….. 17  \n2.2 Current State of Research………………………………………………….. 18  \n2.3 MIMIC-III Database……………………………………………………….. 19  \n2.4 Predicting Clinical Outcomes with MIMIC………………………………...25  \n2.5 MIMIC and Natural Language Processing…………………………............27  \n2.6 Abbreviations in Healthcare……………………………………………….. 32  \n2.7 Health Literacy…………………………………………………………….. 34  \n2.8 Abbreviation Disambiguation………………………………………………35  \n2.9 Text Analysis in Python…………………………………………………….36  \n3.0 Research Methodology…………..………………………………….......... 39  \n3.1 Introduction…………………………………………………………………39  \n3.2 Data Aggregation and Tools………………………………………………..40  \n3.3 Clinical Language Entity Extraction Pipeline………………………............47  \n3.4 Procedures for Access………………………………………………………49  \n4.0 Results…………….……...………………………………………………...51  \n4.1 Introduction…………………………………………………………………51  \n4.2 Evaluating Potential Abbreviations in MIMIC……………………………..51  \n4.3 Evaluating Potential Abbreviations Between Clinicians…………………... 54  \n4.4 MedRec2Vec – Domain Specific Word Embedding……………………….58  \n4.5 Most Similar Abbreviations – Beth Israel Abbreviations…………………..60  \n4.6 Most Similar Abbreviations – Do Not Use…………………………………60  \n4.7 Extractions and Replacements………………………………………...........60  \n4.8 Web Application……………………………………………………………65  \n5.0 Summary and Conclusion…………………………………………...........69  \n5.1 Introduction…………………………………………………………………69  \n5.2 Limitations………………………………………………………………….69  \n5.3 Application of Research…………………………………………………….70  \n5.4 Implications for Future Study………………………………………………71  \n6.0 References………………………………………………………………….72  \n7.0 Appendix……………………………………………………………...........74  \nA MIMIC Word2Vec Code……………………………………………...........74  \nB MIMIC SQL Loading Code…………………………………………...........75  \nC Stop words…………………………………………………………………. 97  \nD Software Versions…………………………………………………………..99  \nE Virtual Environment Setup…………………………………………………99  \nF BIDMC Approved Abbreviations…………………………………………..101  \nABSTRACT  \nIntroduction: Abbreviations are often used in clinical documentation to reduce time spent documenting in electronic health records and to save space during documentation. Abbreviations represent a specific challenge in healthcare as they can often contain multiple means. This ambiguous use of abbreviations is a patient safety issue for clinicians who do not properly understand the intended use of the abbreviation and presents a health literacy issue to patients as they try and understand what a provider’s note says about the care provided. Plenty of ","cbCais0QazPfT1AZ","https://ap.wps.com/l/cbCais0QazPfT1AZ","pdf",1551263,138,"English","# Abstract\n# Introduction\n## Background of the Problem\n## Statement of the Problem\n## Research Objective\n## Need & Rationale\n## Research Hypothesis\n# Literature Review\n## Literature Search and Search String\n## Current State of Research\n## MIMIC-III Database\n## Predicting Clinical Outcomes with MIMIC\n## MIMIC and Natural Language Processing\n## Abbreviations in Healthcare\n## Health Literacy\n## Abbreviation Disambiguation\n## Text Analysis in Python\n# Research Methodology\n## Data Aggregation and Tools\n## Clinical Language Entity Extraction Pipeline\n## Procedures for Access\n# Results\n## Evaluating Potential Abbreviations in MIMIC\n## Evaluating Potential Abbreviations Between Clinicians\n## MedRec2Vec – Domain Specific Word Embedding\n## Most Similar Abbreviations – Beth Israel Abbreviations\n## Most Similar Abbreviations – Do Not Use\n## Extractions and Replacements\n## Web Application\n# Summary and Conclusion\n## Limitations\n## Application of Research\n## Implications for Future Study\n# References\n# Appendix","[{\"question\":\"Why are abbreviations considered a patient-safety and health-literacy concern in clinical documentation?\",\"answer\":\"Abbreviations can have multiple meanings, so clinicians may misunderstand intended usage, creating patient-safety risks. Patients also face difficulties interpreting provider notes when abbreviations are ambiguous.\"},{\"question\":\"How were potential abbreviations identified in the MIMIC-III database?\",\"answer\":\"A semi-supervised method compared more than 400 million-word tokens in MIMIC-III to a list of abbreviations approved by Beth Israel Deaconess Hospital.\"},{\"question\":\"What differences in abbreviation usage were observed between RN-created and MD-created notes?\",\"answer\":\"The average count of potential abbreviations differed by clinician type, with RN notes averaging 21.87 and MD notes averaging 11.39, indicating a substantial difference in usage patterns.\"}]","Prevalence and Evaluation of Potential Abbreviations in Intensive Care Documentation - Dissertation | PDF",348]