{"id":"https://openalex.org/W7155074214","doi":"https://doi.org/10.48550/arxiv.2604.16364","title":"Clinical Note Bloat Reduction for Efficient LLM Use","display_name":"Clinical Note Bloat Reduction for Efficient LLM Use","publication_year":2026,"publication_date":"2026-03-21","ids":{"openalex":"https://openalex.org/W7155074214","doi":"https://doi.org/10.48550/arxiv.2604.16364"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.16364","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.16364","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.16364","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5030613059","display_name":"Jordan L. Cahoon","orcid":"https://orcid.org/0000-0003-4393-528X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cahoon, Jordan L.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134212140","display_name":"Chloe Stanwyck","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Stanwyck, Chloe","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046938499","display_name":"Asad Aali","orcid":"https://orcid.org/0009-0008-2120-5722"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Aali, Asad","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060672964","display_name":"Rachel Madding","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Madding, Rachel","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125422723","display_name":"Emma Sun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Emma","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134111408","display_name":"Yixing Jiang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiang, Yixing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134169636","display_name":"Renumathy Dhanasekaran","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dhanasekaran, Renumathy","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5134182910","display_name":"Emily Alsentzer","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Alsentzer, Emily","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.1720000058412552,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.1720000058412552,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10350","display_name":"Electronic Health Records Systems","score":0.16580000519752502,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.13109999895095825,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/metadata","display_name":"Metadata","score":0.7775999903678894},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6291000247001648},{"id":"https://openalex.org/keywords/documentation","display_name":"Documentation","score":0.5256999731063843},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4927999973297119},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.4887999892234802},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.4359999895095825},{"id":"https://openalex.org/keywords/trace","display_name":"TRACE (psycholinguistics)","score":0.4343000054359436},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.42809998989105225},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.37779998779296875},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.3668999969959259}],"concepts":[{"id":"https://openalex.org/C93518851","wikidata":"https://www.wikidata.org/wiki/Q180160","display_name":"Metadata","level":2,"score":0.7775999903678894},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7153000235557556},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6291000247001648},{"id":"https://openalex.org/C56666940","wikidata":"https://www.wikidata.org/wiki/Q788790","display_name":"Documentation","level":2,"score":0.5256999731063843},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4927999973297119},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.4887999892234802},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.4359999895095825},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4343000054359436},{"id":"https://openalex.org/C75291252","wikidata":"https://www.wikidata.org/wiki/Q1315756","display_name":"TRACE (psycholinguistics)","level":2,"score":0.4343000054359436},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.42809998989105225},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.40400001406669617},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.37779998779296875},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.3668999969959259},{"id":"https://openalex.org/C144559511","wikidata":"https://www.wikidata.org/wiki/Q2986279","display_name":"Principal (computer security)","level":2,"score":0.34940001368522644},{"id":"https://openalex.org/C32587265","wikidata":"https://www.wikidata.org/wiki/Q1182260","display_name":"Data deduplication","level":2,"score":0.3366999924182892},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.33250001072883606},{"id":"https://openalex.org/C145642194","wikidata":"https://www.wikidata.org/wiki/Q870895","display_name":"Health informatics","level":3,"score":0.33009999990463257},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.32850000262260437},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.3059000074863434},{"id":"https://openalex.org/C2779010991","wikidata":"https://www.wikidata.org/wiki/Q2720909","display_name":"Artifact (error)","level":2,"score":0.30230000615119934},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.3009999990463257},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2957000136375427},{"id":"https://openalex.org/C2776207758","wikidata":"https://www.wikidata.org/wiki/Q5303302","display_name":"Downstream (manufacturing)","level":2,"score":0.2944999933242798},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.289000004529953},{"id":"https://openalex.org/C2779308522","wikidata":"https://www.wikidata.org/wiki/Q843958","display_name":"Digitization","level":2,"score":0.28690001368522644},{"id":"https://openalex.org/C2779473830","wikidata":"https://www.wikidata.org/wiki/Q1540899","display_name":"MEDLINE","level":2,"score":0.28299999237060547},{"id":"https://openalex.org/C63527458","wikidata":"https://www.wikidata.org/wiki/Q5133829","display_name":"Clinical decision support system","level":3,"score":0.27489998936653137},{"id":"https://openalex.org/C2780512708","wikidata":"https://www.wikidata.org/wiki/Q850661","display_name":"XQuery","level":4,"score":0.27149999141693115},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.2669000029563904},{"id":"https://openalex.org/C206497026","wikidata":"https://www.wikidata.org/wiki/Q1753883","display_name":"SNOMED CT","level":3,"score":0.2662999927997589},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.26339998841285706},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.2578999996185303},{"id":"https://openalex.org/C2777466982","wikidata":"https://www.wikidata.org/wiki/Q5227287","display_name":"Data extraction","level":3,"score":0.2547000050544739},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.2517000138759613},{"id":"https://openalex.org/C160735492","wikidata":"https://www.wikidata.org/wiki/Q31207","display_name":"Health care","level":2,"score":0.25110000371932983},{"id":"https://openalex.org/C8797682","wikidata":"https://www.wikidata.org/wiki/Q2115","display_name":"XML","level":2,"score":0.2508000135421753}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.16364","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.16364","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.16364","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.16364","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Health":[0],"systems":[1],"are":[2,79],"rapidly":[3],"deploying":[4],"large":[5,125],"language":[6],"models":[7],"(LLMs)":[8],"that":[9,37,58],"use":[10],"clinical":[11,14,87,120,164],"notes":[12],"for":[13,116],"decision":[15],"support":[16],"applications.":[17],"However,":[18],"modern":[19],"documentation":[20],"practices":[21],"rely":[22],"heavily":[23],"on":[24],"templates,":[25],"copy--paste":[26],"shortcuts,":[27],"and":[28,42,70,73,93,103,119,159],"auto-populated":[29],"fields,":[30],"producing":[31],"extensive":[32],"duplicated":[33],"text":[34,112],"(``note":[35],"bloat'')":[36],"dilutes":[38],"clinically":[39],"meaningful":[40],"signal":[41],"substantially":[43],"increases":[44],"the":[45],"computational":[46],"cost":[47],"of":[48,110,162],"LLM":[49,140],"use.":[50],"We":[51,81],"introduce":[52],"TRACE,":[53],"a":[54,124],"scalable":[55,158],"preprocessing":[56],"pipeline":[57],"removes":[59],"note":[60],"bloat":[61],"by":[62],"leveraging":[63],"EHR":[64,153],"attribution":[65],"metadata":[66,78,154],"to":[67,132],"identify":[68],"templated":[69],"copied":[71],"content":[72],"applying":[74],"frequency-based":[75],"deduplication":[76],"when":[77],"unavailable.":[80],"evaluated":[82],"TRACE":[83,107],"across":[84],"four":[85],"real--world":[86],"cohorts":[88],"spanning":[89],"liver":[90],"transplantation,":[91],"obstetrics,":[92],"inpatient":[94],"care":[95],"(5.3":[96],"million":[97,136],"notes)":[98],"using":[99],"blinded":[100],"physician":[101],"review":[102],"downstream":[104],"modeling":[105],"tasks.":[106],"removed":[108],"47.3%":[109],"chart":[111],"while":[113],"preserving":[114],"performance":[115],"information":[117],"extraction":[118],"outcome":[121],"prediction.":[122],"At":[123],"academic":[126],"medical":[127],"center,":[128],"this":[129],"reduction":[130],"corresponds":[131],"an":[133],"estimated":[134],"$9.5":[135],"annual":[137],"decrease":[138],"in":[139],"inference":[141],"costs":[142],"assuming":[143],"one":[144],"query":[145],"per":[146],"encounter.":[147],"These":[148],"findings":[149],"show":[150],"how":[151],"underutilized":[152],"can":[155],"enable":[156],"more":[157],"cost-efficient":[160],"deployment":[161],"LLM-based":[163],"systems.":[165]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-04-22T00:00:00"}
