{"id":"https://openalex.org/W7131106814","doi":"https://doi.org/10.3390/systems14020226","title":"A Copula-Based Joint Modeling Framework for Hospitalization Costs and Length of Stay in Massive Healthcare Data","display_name":"A Copula-Based Joint Modeling Framework for Hospitalization Costs and Length of Stay in Massive Healthcare Data","publication_year":2026,"publication_date":"2026-02-23","ids":{"openalex":"https://openalex.org/W7131106814","doi":"https://doi.org/10.3390/systems14020226"},"language":"en","primary_location":{"id":"doi:10.3390/systems14020226","is_oa":true,"landing_page_url":"https://doi.org/10.3390/systems14020226","pdf_url":"https://www.mdpi.com/2079-8954/14/2/226/pdf?version=1771836659","source":{"id":"https://openalex.org/S4210219410","display_name":"Systems","issn_l":"2079-8954","issn":["2079-8954"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2079-8954/14/2/226/pdf?version=1771836659","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Xuan Xu","orcid":"https://orcid.org/0009-0006-4687-0409"},"institutions":[{"id":"https://openalex.org/I90727586","display_name":"Zhejiang University of Finance and Economics","ror":"https://ror.org/055vj5234","country_code":"CN","type":"education","lineage":["https://openalex.org/I90727586"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuan Xu","raw_affiliation_strings":["Asset and Laboratory Management Office, Zhejiang University of Finance and Economics, Hangzhou 310018, China"],"raw_orcid":"https://orcid.org/0009-0006-4687-0409","affiliations":[{"raw_affiliation_string":"Asset and Laboratory Management Office, Zhejiang University of Finance and Economics, Hangzhou 310018, China","institution_ids":["https://openalex.org/I90727586"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5121247467","display_name":"Yijun Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I75059550","display_name":"Zhejiang Gongshang University","ror":"https://ror.org/0569mkk41","country_code":"CN","type":"education","lineage":["https://openalex.org/I75059550"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yijun Wang","raw_affiliation_strings":["School of Statistics and Data Science, Zhejiang Gongshang University, Hangzhou 310018, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Statistics and Data Science, Zhejiang Gongshang University, Hangzhou 310018, China","institution_ids":["https://openalex.org/I75059550"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5121247467"],"corresponding_institution_ids":["https://openalex.org/I75059550"],"apc_list":{"value":1600,"currency":"CHF","value_usd":1732},"apc_paid":{"value":1600,"currency":"CHF","value_usd":1732},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.27812724,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"14","issue":"2","first_page":"226","last_page":"226"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.4198000133037567,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.4198000133037567,"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/T12246","display_name":"Chronic Disease Management Strategies","score":0.13490000367164612,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"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/T10391","display_name":"Healthcare Policy and Management","score":0.09279999881982803,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/health-care","display_name":"Health care","score":0.4952999949455261},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.4650999903678894},{"id":"https://openalex.org/keywords/copula","display_name":"Copula (linguistics)","score":0.4343999922275543},{"id":"https://openalex.org/keywords/medical-costs","display_name":"Medical costs","score":0.39910000562667847},{"id":"https://openalex.org/keywords/resource-allocation","display_name":"Resource allocation","score":0.37869998812675476},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.3691999912261963},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.3637000024318695},{"id":"https://openalex.org/keywords/resource","display_name":"Resource (disambiguation)","score":0.3357999920845032}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5360000133514404},{"id":"https://openalex.org/C160735492","wikidata":"https://www.wikidata.org/wiki/Q31207","display_name":"Health care","level":2,"score":0.4952999949455261},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.4650999903678894},{"id":"https://openalex.org/C17618745","wikidata":"https://www.wikidata.org/wiki/Q207509","display_name":"Copula (linguistics)","level":2,"score":0.4343999922275543},{"id":"https://openalex.org/C3019354653","wikidata":"https://www.wikidata.org/wiki/Q5690885","display_name":"Medical costs","level":3,"score":0.39910000562667847},{"id":"https://openalex.org/C29202148","wikidata":"https://www.wikidata.org/wiki/Q287260","display_name":"Resource allocation","level":2,"score":0.37869998812675476},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.3691999912261963},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.3637000024318695},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.36329999566078186},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.3357999920845032},{"id":"https://openalex.org/C2988170871","wikidata":"https://www.wikidata.org/wiki/Q11000047","display_name":"Healthcare system","level":3,"score":0.3345000147819519},{"id":"https://openalex.org/C66887028","wikidata":"https://www.wikidata.org/wiki/Q382444","display_name":"Marginal cost","level":2,"score":0.3190000057220459},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.3122999966144562},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.30869999527931213},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.3041999936103821},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.28929999470710754},{"id":"https://openalex.org/C18653775","wikidata":"https://www.wikidata.org/wiki/Q1333358","display_name":"Joint probability distribution","level":2,"score":0.2793000042438507},{"id":"https://openalex.org/C42475967","wikidata":"https://www.wikidata.org/wiki/Q194292","display_name":"Operations research","level":1,"score":0.27489998936653137},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.27059999108314514},{"id":"https://openalex.org/C3018838755","wikidata":"https://www.wikidata.org/wiki/Q31207","display_name":"Medical care","level":2,"score":0.257999986410141},{"id":"https://openalex.org/C2778136018","wikidata":"https://www.wikidata.org/wiki/Q10350689","display_name":"Predictive power","level":2,"score":0.25529998540878296},{"id":"https://openalex.org/C93983250","wikidata":"https://www.wikidata.org/wiki/Q795053","display_name":"Cost estimate","level":2,"score":0.2549999952316284}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/systems14020226","is_oa":true,"landing_page_url":"https://doi.org/10.3390/systems14020226","pdf_url":"https://www.mdpi.com/2079-8954/14/2/226/pdf?version=1771836659","source":{"id":"https://openalex.org/S4210219410","display_name":"Systems","issn_l":"2079-8954","issn":["2079-8954"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Systems","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:0e0097f7fe61468888fa268321c8dc30","is_oa":false,"landing_page_url":"https://doaj.org/article/0e0097f7fe61468888fa268321c8dc30","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Systems, Vol 14, Iss 2, p 226 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/systems14020226","is_oa":true,"landing_page_url":"https://doi.org/10.3390/systems14020226","pdf_url":"https://www.mdpi.com/2079-8954/14/2/226/pdf?version=1771836659","source":{"id":"https://openalex.org/S4210219410","display_name":"Systems","issn_l":"2079-8954","issn":["2079-8954"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Systems","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1174876977","display_name":null,"funder_award_id":"LMS25G010001","funder_id":"https://openalex.org/F4320338464","funder_display_name":"Natural Science Foundation of Zhejiang Province"},{"id":"https://openalex.org/G2005710343","display_name":null,"funder_award_id":"2025ZDPY06","funder_id":"https://openalex.org/F4554350417","funder_display_name":"Fundamental Research Funds for the Provincial Universities of Zhejiang"},{"id":"https://openalex.org/G8131344699","display_name":null,"funder_award_id":"2025LZ023","funder_id":"https://openalex.org/F4320311212","funder_display_name":"National Bureau of Statistics of China"}],"funders":[{"id":"https://openalex.org/F4320311212","display_name":"National Bureau of Statistics of China","ror":"https://ror.org/008zm7t63"},{"id":"https://openalex.org/F4320338464","display_name":"Natural Science Foundation of Zhejiang Province","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4554350417","display_name":"Fundamental Research Funds for the Provincial Universities of Zhejiang","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7131106814.pdf","grobid_xml":"https://content.openalex.org/works/W7131106814.grobid-xml"},"referenced_works_count":38,"referenced_works":["https://openalex.org/W1423766661","https://openalex.org/W1846128085","https://openalex.org/W1968106809","https://openalex.org/W1968692896","https://openalex.org/W1994479173","https://openalex.org/W2001696823","https://openalex.org/W2025329530","https://openalex.org/W2046113245","https://openalex.org/W2049405182","https://openalex.org/W2056436688","https://openalex.org/W2064551188","https://openalex.org/W2086101125","https://openalex.org/W2087942999","https://openalex.org/W2101095383","https://openalex.org/W2105691242","https://openalex.org/W2121281704","https://openalex.org/W2134902673","https://openalex.org/W2142635246","https://openalex.org/W2145769852","https://openalex.org/W2158825179","https://openalex.org/W2282644239","https://openalex.org/W2325031208","https://openalex.org/W2403080995","https://openalex.org/W2497830913","https://openalex.org/W2519243772","https://openalex.org/W2549476603","https://openalex.org/W3093838468","https://openalex.org/W3138338712","https://openalex.org/W3147894994","https://openalex.org/W4301380908","https://openalex.org/W4313609053","https://openalex.org/W4381715104","https://openalex.org/W4392911737","https://openalex.org/W4410339798","https://openalex.org/W4416026644","https://openalex.org/W7118089209","https://openalex.org/W7123352851","https://openalex.org/W7128551273"],"related_works":[],"abstract_inverted_index":{"In":[0,131],"large-scale":[1],"medical":[2,12,63,124,135,172],"data,":[3],"the":[4,36,43,118],"connection":[5],"between":[6,42],"hospital":[7,121],"length":[8,119],"of":[9,21,120],"stay":[10],"and":[11,17,39,99,112,123,164,175],"expenses":[13,136],"shows":[14],"a":[15,22,29,47,59,72,166],"complex":[16],"nonlinear":[18,159],"relationship":[19],"instead":[20],"straightforward":[23],"positive":[24],"link.":[25],"This":[26],"study":[27,94],"proposes":[28],"Cox\u2013Log-Logistic\u2013Copula":[30],"joint":[31],"modeling":[32],"framework":[33,150],"to":[34,75,108,152],"describe":[35],"marginal":[37],"distributions":[38],"latent":[40],"dependence":[41],"two":[44,66],"variables.":[45],"Specifically,":[46],"semi-parametric":[48],"Cox":[49],"proportional":[50],"hazards":[51],"model":[52,61],"is":[53],"used":[54],"for":[55,170],"hospitalization":[56,84],"duration,":[57],"while":[58],"Log-Logistic":[60],"handles":[62],"costs.":[64,177],"The":[65,148],"margins":[67],"are":[68,126],"flexibly":[69],"coupled":[70],"through":[71],"Copula":[73],"function":[74],"capture":[76],"dynamic":[77],"variations":[78],"in":[79,90,157,161],"cost":[80],"levels":[81],"during":[82,138],"different":[83],"stages.":[85],"To":[86],"address":[87],"computational":[88],"challenges":[89],"large":[91],"datasets,":[92],"this":[93],"also":[95],"includes":[96],"subsample":[97],"correction":[98],"one-step":[100],"adjustment":[101],"algorithms,":[102],"combined":[103],"with":[104],"parallel":[105],"computing":[106],"strategies,":[107],"enhance":[109],"estimation":[110],"efficiency":[111],"accuracy.":[113],"Empirical":[114],"results":[115],"show":[116],"that":[117],"stays":[122],"costs":[125],"not":[127],"always":[128],"positively":[129],"related.":[130],"some":[132],"cases,":[133],"higher":[134],"occur":[137],"shorter":[139],"stays,":[140],"suggesting":[141],"possible":[142],"over-treatment":[143],"or":[144],"uneven":[145],"resource":[146,173],"distribution.":[147],"proposed":[149],"proves":[151],"have":[153],"strong":[154],"explanatory":[155],"power":[156],"identifying":[158],"patterns":[160],"healthcare":[162],"behavior":[163],"offers":[165],"new":[167],"quantitative":[168],"tool":[169],"optimizing":[171],"allocation":[174],"controlling":[176]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2026-02-24T00:00:00"}