{"id":"https://openalex.org/W3174669709","doi":"https://doi.org/10.1093/jamia/ocab087","title":"A likelihood-based convolution approach to estimate major health events in longitudinal health records data: an external validation study","display_name":"A likelihood-based convolution approach to estimate major health events in longitudinal health records data: an external validation study","publication_year":2021,"publication_date":"2021-04-27","ids":{"openalex":"https://openalex.org/W3174669709","doi":"https://doi.org/10.1093/jamia/ocab087","mag":"3174669709","pmid":"https://pubmed.ncbi.nlm.nih.gov/34151985"},"language":"en","primary_location":{"id":"doi:10.1093/jamia/ocab087","is_oa":false,"landing_page_url":"https://doi.org/10.1093/jamia/ocab087","pdf_url":null,"source":{"id":"https://openalex.org/S129839026","display_name":"Journal of the American Medical Informatics Association","issn_l":"1067-5027","issn":["1067-5027","1527-974X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of the American Medical Informatics Association","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8363786","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5076198521","display_name":"Lisiane Pruinelli","orcid":"https://orcid.org/0000-0002-1046-6037"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]},{"id":"https://openalex.org/I4210124242","display_name":"Optum (United States)","ror":"https://ror.org/0370sjj75","country_code":"US","type":"company","lineage":["https://openalex.org/I4210124242"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Lisiane Pruinelli","raw_affiliation_strings":["OptumLabs Visiting Scholar, Eden Prairie, Minnesota, USA","School of Nursing, University of Minnesota, Minneapolis, USA"],"raw_orcid":"https://orcid.org/0000-0002-1046-6037","affiliations":[{"raw_affiliation_string":"OptumLabs Visiting Scholar, Eden Prairie, Minnesota, USA","institution_ids":["https://openalex.org/I4210124242"]},{"raw_affiliation_string":"School of Nursing, University of Minnesota, Minneapolis, USA","institution_ids":["https://openalex.org/I130238516"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013378515","display_name":"Jiaqi Zhou","orcid":"https://orcid.org/0000-0002-8233-2740"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jiaqi Zhou","raw_affiliation_strings":["School of Statistics, University of Minnesota, Minneapolis, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Statistics, University of Minnesota, Minneapolis, USA","institution_ids":["https://openalex.org/I130238516"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042922956","display_name":"Bethany Stai","orcid":null},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bethany Stai","raw_affiliation_strings":["Computer Science and Engineering, University of Minnesota, Minneapolis, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science and Engineering, University of Minnesota, Minneapolis, USA","institution_ids":["https://openalex.org/I130238516"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021944743","display_name":"Jesse D. Schold","orcid":"https://orcid.org/0000-0002-5341-7286"},"institutions":[{"id":"https://openalex.org/I1316902750","display_name":"Cleveland Clinic","ror":"https://ror.org/03xjacd83","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1316902750"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jesse D Schold","raw_affiliation_strings":["Department of Quantitative Health Sciences, Cleveland Clinic Foundation, Cleveland, Ohio, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Quantitative Health Sciences, Cleveland Clinic Foundation, Cleveland, Ohio, USA","institution_ids":["https://openalex.org/I1316902750"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022183693","display_name":"Timothy L. Pruett","orcid":"https://orcid.org/0000-0002-0715-8535"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Timothy Pruett","raw_affiliation_strings":["Division of Transplantation, Department of Surgery, University of Minnesota, Minneapolis, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Division of Transplantation, Department of Surgery, University of Minnesota, Minneapolis, USA","institution_ids":["https://openalex.org/I130238516"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059973732","display_name":"Sisi Ma","orcid":"https://orcid.org/0000-0003-2956-6844"},"institutions":[{"id":"https://openalex.org/I4210135252","display_name":"University of Minnesota Medical Center","ror":"https://ror.org/03e1ayz78","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1309104334","https://openalex.org/I4210135252"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sisi Ma","raw_affiliation_strings":["Medical School and Institute for Health Informatics, University of Minnesota, Minneapolis, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Medical School and Institute for Health Informatics, University of Minnesota, Minneapolis, USA","institution_ids":["https://openalex.org/I4210135252"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050008389","display_name":"Gy\u00f6rgy Simon","orcid":"https://orcid.org/0000-0003-4715-5934"},"institutions":[{"id":"https://openalex.org/I4210135252","display_name":"University of Minnesota Medical Center","ror":"https://ror.org/03e1ayz78","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1309104334","https://openalex.org/I4210135252"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gyorgy Simon","raw_affiliation_strings":["Medical School and Institute for Health Informatics, University of Minnesota, Minneapolis, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Medical School and Institute for Health Informatics, University of Minnesota, Minneapolis, USA","institution_ids":["https://openalex.org/I4210135252"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5076198521"],"corresponding_institution_ids":["https://openalex.org/I130238516","https://openalex.org/I4210124242"],"apc_list":{"value":3967,"currency":"USD","value_usd":3967},"apc_paid":null,"fwci":0.1399,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.54399004,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"28","issue":"9","first_page":"1885","last_page":"1891"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.4726000130176544,"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":0.4726000130176544,"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":0.11670000106096268,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.045499999076128006,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/computer-science","display_name":"Computer science","score":0.6750855445861816},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.6565707325935364},{"id":"https://openalex.org/keywords/electronic-health-record","display_name":"Electronic health record","score":0.5089921951293945},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.5037040114402771},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5014564990997314},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.47558581829071045},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.4474294185638428},{"id":"https://openalex.org/keywords/data-collection","display_name":"Data collection","score":0.44723254442214966},{"id":"https://openalex.org/keywords/health-care","display_name":"Health care","score":0.3115471601486206},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2557380795478821},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.1981297731399536},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12489581108093262}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6750855445861816},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.6565707325935364},{"id":"https://openalex.org/C3020144179","wikidata":"https://www.wikidata.org/wiki/Q10871684","display_name":"Electronic health record","level":3,"score":0.5089921951293945},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.5037040114402771},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5014564990997314},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.47558581829071045},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.4474294185638428},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.44723254442214966},{"id":"https://openalex.org/C160735492","wikidata":"https://www.wikidata.org/wiki/Q31207","display_name":"Health care","level":2,"score":0.3115471601486206},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2557380795478821},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.1981297731399536},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12489581108093262},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.0}],"mesh":[{"descriptor_ui":"D016013","descriptor_name":"Likelihood Functions","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016013","descriptor_name":"Likelihood Functions","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016013","descriptor_name":"Likelihood Functions","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D057286","descriptor_name":"Electronic Health Records","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D057286","descriptor_name":"Electronic Health Records","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D057286","descriptor_name":"Electronic Health Records","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":3,"locations":[{"id":"doi:10.1093/jamia/ocab087","is_oa":false,"landing_page_url":"https://doi.org/10.1093/jamia/ocab087","pdf_url":null,"source":{"id":"https://openalex.org/S129839026","display_name":"Journal of the American Medical Informatics Association","issn_l":"1067-5027","issn":["1067-5027","1527-974X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of the American Medical Informatics Association","raw_type":"journal-article"},{"id":"pmid:34151985","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/34151985","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of the American Medical Informatics Association : JAMIA","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:8363786","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8363786","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"J Am Med Inform Assoc","raw_type":"Text"}],"best_oa_location":{"id":"pmh:oai:pubmedcentral.nih.gov:8363786","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8363786","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"J Am Med Inform Assoc","raw_type":"Text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1016679971","https://openalex.org/W2140302476","https://openalex.org/W2180935524","https://openalex.org/W2594685110","https://openalex.org/W2610641682","https://openalex.org/W2799061466","https://openalex.org/W2946814533","https://openalex.org/W2990212745","https://openalex.org/W2997681568","https://openalex.org/W3011742849","https://openalex.org/W3097224450","https://openalex.org/W4205687621","https://openalex.org/W6774600821"],"related_works":["https://openalex.org/W3024870410","https://openalex.org/W2410652950","https://openalex.org/W4380150146","https://openalex.org/W4283773154","https://openalex.org/W3139174110","https://openalex.org/W4289597203","https://openalex.org/W2950538088","https://openalex.org/W1977098485","https://openalex.org/W2085630472","https://openalex.org/W4285201053"],"abstract_inverted_index":{"OBJECTIVE:":[0],"In":[1],"electronic":[2,213],"health":[3,12,159,172,244],"record":[4,215],"data,":[5],"the":[6,63,81,89,107,110,125,148,171,227],"exact":[7],"time":[8,36,41,93,141,206,210,221],"stamp":[9],"of":[10,43,109,124,223,249],"major":[11],"events,":[13],"defined":[14],"by":[15,199],"significant":[16],"physiologic":[17],"or":[18,176],"treatment":[19],"changes,":[20],"is":[21,174,197],"often":[22],"missing.":[23],"We":[24,87],"developed":[25,57,230],"and":[26,58,117,122,129],"externally":[27,72],"validated":[28,73],"a":[29,75,232,242],"method":[30,136,150,180],"that":[31,147,196,203],"can":[32,137,163,187,217],"accurately":[33,138],"estimate":[34,92,139],"these":[35],"stamps":[37,42,211,222],"based":[38],"on":[39,74,231],"accurate":[40,205],"related":[44,201,224],"data":[45,61,69,169,216],"elements.":[46],"MATERIALS":[47],"AND":[48],"METHODS:":[49],"A":[50],"novel":[51],"convolution-based":[52],"change":[53],"detection":[54],"methodology":[55,90],"was":[56,114,120,181,229],"tested":[59],"using":[60,220],"from":[62,80],"national":[64],"deidentified":[65],"clinical":[66],"claims":[67],"OptumLabs":[68],"warehouse,":[70],"then":[71],"single":[76],"center":[77],"dataset":[78],"derived":[79],"M":[82],"Health":[83],"Fairview":[84],"system.":[85],"RESULTS:":[86],"applied":[88,165,182,191],"to":[91,94,154,157,183,192,241],"liver":[95,184],"transplantation":[96,185],"for":[97],"waitlisted":[98],"candidates.":[99],"The":[100,134,178],"median":[101,118],"error":[102,119],"between":[103],"estimated":[104,219],"date":[105,113],"within":[106],"period":[108],"actual":[111],"true":[112],"zero":[115],"days,":[116],"92%":[121],"84%":[123],"transplants,":[126],"in":[127,212],"development":[128],"validation":[130,145],"samples,":[131],"respectively.":[132],"DISCUSSION:":[133],"proposed":[135,149,179],"missing":[140,194],"stamps.":[142,207],"Successful":[143],"external":[144],"suggests":[146],"does":[151],"not":[152],"need":[153],"be":[155,164,188,218,238],"refit":[156],"each":[158],"system;":[160],"thus,":[161],"it":[162,236],"even":[166],"when":[167],"training":[168],"at":[170],"system":[173,245],"insufficient":[175],"unavailable.":[177],"but":[186],"more":[189],"generally":[190],"any":[193],"event":[195],"accompanied":[198],"multiple":[200],"events":[202],"have":[204],"CONCLUSION:":[208],"Missing":[209],"healthcare":[214],"events.":[225],"Since":[226],"model":[228],"nationally":[233],"representative":[234],"dataset,":[235],"could":[237],"successfully":[239],"transferred":[240],"local":[243],"without":[246],"substantial":[247],"loss":[248],"accuracy.":[250]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2026-04-29T09:16:38.111599","created_date":"2025-10-10T00:00:00"}