{"id":"https://openalex.org/W7161783769","doi":"https://doi.org/10.48550/arxiv.2605.18839","title":"An Integrated Forecasting Prototype for Emergency Department Boarding Time to Support Proactive Operational Decision Making","display_name":"An Integrated Forecasting Prototype for Emergency Department Boarding Time to Support Proactive Operational Decision Making","publication_year":2026,"publication_date":"2026-05-13","ids":{"openalex":"https://openalex.org/W7161783769","doi":"https://doi.org/10.48550/arxiv.2605.18839"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.18839","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.18839","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.18839","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5114553843","display_name":"Orhun Vural","orcid":"https://orcid.org/0009-0004-7918-5307"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Vural, Orhun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104623159","display_name":"Abdulaziz Ahmed","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ahmed, Abdulaziz","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136603206","display_name":"Ferhat Zengul","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zengul, Ferhat","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136560011","display_name":"James Booth","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Booth, James","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5065889292","display_name":"Bunyamin Ozaydin","orcid":"https://orcid.org/0000-0002-6775-0450"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ozaydin, Bunyamin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"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/T11095","display_name":"Emergency and Acute Care Studies","score":0.8483999967575073,"subfield":{"id":"https://openalex.org/subfields/2711","display_name":"Emergency Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11095","display_name":"Emergency and Acute Care Studies","score":0.8483999967575073,"subfield":{"id":"https://openalex.org/subfields/2711","display_name":"Emergency Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11773","display_name":"Healthcare Operations and Scheduling Optimization","score":0.04610000178217888,"subfield":{"id":"https://openalex.org/subfields/3604","display_name":"Emergency Medical Services"},"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/T11918","display_name":"Forecasting Techniques and Applications","score":0.022700000554323196,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/overcrowding","display_name":"Overcrowding","score":0.880299985408783},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5098000168800354},{"id":"https://openalex.org/keywords/decision-support-system","display_name":"Decision support system","score":0.446399986743927},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.44519999623298645},{"id":"https://openalex.org/keywords/duration","display_name":"Duration (music)","score":0.4099999964237213},{"id":"https://openalex.org/keywords/operational-planning","display_name":"Operational planning","score":0.36570000648498535}],"concepts":[{"id":"https://openalex.org/C2778872837","wikidata":"https://www.wikidata.org/wiki/Q7113614","display_name":"Overcrowding","level":2,"score":0.880299985408783},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5098000168800354},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4925999939441681},{"id":"https://openalex.org/C107327155","wikidata":"https://www.wikidata.org/wiki/Q330268","display_name":"Decision support system","level":2,"score":0.446399986743927},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.44519999623298645},{"id":"https://openalex.org/C42475967","wikidata":"https://www.wikidata.org/wiki/Q194292","display_name":"Operations research","level":1,"score":0.44359999895095825},{"id":"https://openalex.org/C112758219","wikidata":"https://www.wikidata.org/wiki/Q16038819","display_name":"Duration (music)","level":2,"score":0.4099999964237213},{"id":"https://openalex.org/C2776613951","wikidata":"https://www.wikidata.org/wiki/Q7097788","display_name":"Operational planning","level":2,"score":0.36570000648498535},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.3257000148296356},{"id":"https://openalex.org/C193809577","wikidata":"https://www.wikidata.org/wiki/Q3409300","display_name":"Demand forecasting","level":2,"score":0.30160000920295715},{"id":"https://openalex.org/C135510737","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Performance indicator","level":2,"score":0.2953999936580658},{"id":"https://openalex.org/C110593043","wikidata":"https://www.wikidata.org/wiki/Q7300787","display_name":"Real-time data","level":2,"score":0.2824000120162964},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.2759000062942505},{"id":"https://openalex.org/C2780724011","wikidata":"https://www.wikidata.org/wiki/Q1295316","display_name":"Emergency department","level":2,"score":0.2745000123977661}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.18839","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.18839","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.18839","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.18839","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[{"score":0.42895078659057617,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Overcrowding":[0],"in":[1,13,29,48,88],"emergency":[2],"departments":[3],"(ED)":[4],"remains":[5],"a":[6,38,62,84,142],"persistent":[7],"operational":[8,52],"challenge":[9],"worldwide,":[10],"causing":[11],"delays":[12],"care":[14],"delivery":[15],"and":[16,60,78,94,104,111,168],"downstream":[17],"congestion.":[18,43],"ED":[19,31,45,70],"boarding":[20,46,71,138],"time,":[21],"defined":[22],"as":[23],"the":[24,30,89,156],"duration":[25],"admitted":[26],"patients":[27],"remain":[28],"while":[32],"awaiting":[33],"inpatient":[34],"bed":[35],"placement,":[36],"is":[37],"key":[39],"indicator":[40],"of":[41,155],"this":[42],"Predicting":[44],"time":[47,64,72,115],"advance":[49],"enables":[50],"proactive":[51],"decision":[53],"making":[54],"before":[55],"congestion":[56,133],"escalates.":[57],"We":[58],"developed":[59,151],"evaluated":[61,130],"multi-horizon":[63],"series":[65,116],"forecasting":[66,117,157],"framework":[67,158],"to":[68,152],"predict":[69],"at":[73],"6,":[74],"8,":[75],"10,":[76],"12,":[77],"24-hour":[79],"horizons.":[80,126],"Real-world":[81],"data":[82,99,163],"from":[83],"university-affiliated":[85],"urban":[86],"hospital":[87],"United":[90],"States":[91],"were":[92,128],"utilized":[93],"integrated":[95,162],"with":[96],"external":[97],"contextual":[98],"sources,":[100],"including":[101],"weather,":[102],"holidays,":[103],"major":[105],"local":[106],"events.":[107],"Decomposition-based":[108],"Linear":[109,113],"(DLinear)":[110],"Normalization-based":[112],"(NLinear)":[114],"deep":[118],"learning":[119],"models":[120],"showed":[121],"superior":[122],"performance":[123],"across":[124],"multiple":[125],"Models":[127],"also":[129],"under":[131],"extreme":[132],"scenarios":[134],"characterized":[135],"by":[136],"elevated":[137],"times.":[139],"In":[140],"addition,":[141],"Machine":[143],"Learning":[144],"Operations":[145],"(MLOps)":[146],"web":[147],"application":[148],"prototype":[149],"was":[150],"support":[153],"translation":[154],"into":[159],"practice":[160],"through":[161],"ingestion,":[164],"forecast":[165],"visualization,":[166],"experimentation,":[167],"retraining.":[169]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-21T00:00:00"}