{"id":"https://openalex.org/W7166016404","doi":"https://doi.org/10.1093/jamia/ocag097","title":"The importance of clinical context in evaluating algorithmic fairness: insights from a medication adherence prediction algorithm","display_name":"The importance of clinical context in evaluating algorithmic fairness: insights from a medication adherence prediction algorithm","publication_year":2026,"publication_date":"2026-05-28","ids":{"openalex":"https://openalex.org/W7166016404","doi":"https://doi.org/10.1093/jamia/ocag097","pmid":"https://pubmed.ncbi.nlm.nih.gov/42350262","pmcid":"https://www.ncbi.nlm.nih.gov/pmc/articles/13630287"},"language":"en","primary_location":{"id":"doi:10.1093/jamia/ocag097","doi":"https://doi.org/10.1093/jamia/ocag097","is_oa":false,"landing_page_url":"https://doi.org/10.1093/jamia/ocag097","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,"listed_in":["anvur-scientific","ccf-b","cwts-core","dongbi-b","doyens","jufo-2","ki-jl-2","medline","norway-1","poland-140","russia-white-list-1","vabb-shw"],"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"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC13630287/","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5054236356","display_name":"Amrita Mukhopadhyay","orcid":"https://orcid.org/0000-0002-7768-459X","observed_orcids":["https://orcid.org/0000-0002-7768-459X"]},"institutions":[{"id":"https://openalex.org/I4210086933","display_name":"NYU Langone Health","ror":"https://ror.org/005dvqh91","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210086933"]},{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Amrita Mukhopadhyay","raw_affiliation_strings":["Department of Population Health, NYU School of Medicine , New York, NY 10016,","Division of Cardiology, Department of Medicine, NYU School of Medicine , New York, NY 10016,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Population Health, NYU School of Medicine , New York, NY 10016,","institution_ids":["https://openalex.org/I4210086933","https://openalex.org/I57206974"]},{"raw_affiliation_string":"Division of Cardiology, Department of Medicine, NYU School of Medicine , New York, NY 10016,","institution_ids":["https://openalex.org/I4210086933","https://openalex.org/I57206974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002913700","display_name":"Yunan Zhao","orcid":"https://orcid.org/0000-0002-0665-5572","observed_orcids":["https://orcid.org/0000-0002-0665-5572"]},"institutions":[{"id":"https://openalex.org/I4210086933","display_name":"NYU Langone Health","ror":"https://ror.org/005dvqh91","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210086933"]},{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yunan Zhao","raw_affiliation_strings":["Department of Population Health, NYU School of Medicine , New York, NY 10016,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Population Health, NYU School of Medicine , New York, NY 10016,","institution_ids":["https://openalex.org/I4210086933","https://openalex.org/I57206974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005061793","display_name":"Rumi Chunara","orcid":"https://orcid.org/0000-0002-5346-7259","observed_orcids":["https://orcid.org/0000-0002-5346-7259"]},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rumi Chunara","raw_affiliation_strings":["Department of Biostatistics and Computer Science & Engineering, NYU Tandon School of Engineering , New York, NY 11201,"],"raw_orcid":"https://orcid.org/0000-0002-5346-7259","affiliations":[{"raw_affiliation_string":"Department of Biostatistics and Computer Science & Engineering, NYU Tandon School of Engineering , New York, NY 11201,","institution_ids":["https://openalex.org/I57206974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058865250","display_name":"Ian Matthew Kronish","orcid":"https://orcid.org/0000-0003-0945-2380","observed_orcids":["https://orcid.org/0000-0003-0945-2380"]},"institutions":[{"id":"https://openalex.org/I2799503643","display_name":"Columbia University Irving Medical Center","ror":"https://ror.org/01esghr10","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I2799503643"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ian M Kronish","raw_affiliation_strings":["Center for Behavioral Cardiovascular Health, Columbia University Irving Medical Center , New York, NY 10032,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Behavioral Cardiovascular Health, Columbia University Irving Medical Center , New York, NY 10032,","institution_ids":["https://openalex.org/I2799503643"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109851540","display_name":"Steven Lawrence","orcid":"https://orcid.org/0000-0002-7595-8323","observed_orcids":["https://orcid.org/0000-0002-7595-8323"]},"institutions":[{"id":"https://openalex.org/I4210086933","display_name":"NYU Langone Health","ror":"https://ror.org/005dvqh91","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210086933"]},{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Steven Lawrence","raw_affiliation_strings":["Department of Population Health, NYU School of Medicine , New York, NY 10016,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Population Health, NYU School of Medicine , New York, NY 10016,","institution_ids":["https://openalex.org/I4210086933","https://openalex.org/I57206974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090785075","display_name":"Saul Blecker","orcid":"https://orcid.org/0000-0003-4460-1046","observed_orcids":["https://orcid.org/0000-0003-4460-1046"]},"institutions":[{"id":"https://openalex.org/I4210086933","display_name":"NYU Langone Health","ror":"https://ror.org/005dvqh91","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210086933"]},{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Saul Blecker","raw_affiliation_strings":["Department of Medicine, NYU School of Medicine , New York, NY 10016,","Department of Population Health, NYU School of Medicine , New York, NY 10016,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Medicine, NYU School of Medicine , New York, NY 10016,","institution_ids":["https://openalex.org/I4210086933","https://openalex.org/I57206974"]},{"raw_affiliation_string":"Department of Population Health, NYU School of Medicine , New York, NY 10016,","institution_ids":["https://openalex.org/I4210086933","https://openalex.org/I57206974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012621096","display_name":"Samrachana Adhikari","orcid":"https://orcid.org/0000-0001-9954-5999","observed_orcids":["https://orcid.org/0000-0001-9954-5999"]},"institutions":[{"id":"https://openalex.org/I4210086933","display_name":"NYU Langone Health","ror":"https://ror.org/005dvqh91","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210086933"]},{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Samrachana Adhikari","raw_affiliation_strings":["Department of Population Health, NYU School of Medicine , New York, NY 10016,"],"raw_orcid":"https://orcid.org/0000-0001-9954-5999","affiliations":[{"raw_affiliation_string":"Department of Population Health, NYU School of Medicine , New York, NY 10016,","institution_ids":["https://openalex.org/I4210086933","https://openalex.org/I57206974"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":4332,"currency":"USD","value_usd":4332},"apc_paid":null,"fwci":2.8407,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.90167131,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":"33","issue":"10","first_page":"1866","last_page":"1874"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10883","display_name":"Ethics and Social Impacts of AI","score":0.5044000148773193,"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/T10883","display_name":"Ethics and Social Impacts of AI","score":0.5044000148773193,"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.3391000032424927,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"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/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.035999998450279236,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/algorithmic-fairness","display_name":"algorithmic fairness","score":0.9980000257492065},{"id":"https://openalex.org/keywords/health-disparities","display_name":"health disparities","score":0.7390000224113464},{"id":"https://openalex.org/keywords/heart-failure","display_name":"heart failure","score":0.9390000104904175},{"id":"https://openalex.org/keywords/racial-disparities","display_name":"racial disparities","score":0.6570000052452087},{"id":"https://openalex.org/keywords/socioeconomic-status","display_name":"socioeconomic status","score":0.9679999947547913},{"id":"https://openalex.org/keywords/false-positive-rate","display_name":"false positive rate","score":0.6050000190734863},{"id":"https://openalex.org/keywords/false-negative-rate","display_name":"false negative rate","score":0.9160000085830688},{"id":"https://openalex.org/keywords/neighborhood-socioeconomic-status","display_name":"neighborhood socioeconomic status","score":0.5659999847412109},{"id":"https://openalex.org/keywords/black-patients","display_name":"Black patients","score":0.8389999866485596},{"id":"https://openalex.org/keywords/prediction-model-evaluation","display_name":"prediction model evaluation","score":0.3720000088214874},{"id":"https://openalex.org/keywords/underserved-populations","display_name":"underserved populations","score":0.640999972820282}],"concepts":[{"id":"https://openalex.org/C64869954","wikidata":"https://www.wikidata.org/wiki/Q1859747","display_name":"False positive paradox","level":2,"score":0.829200029373169},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6728000044822693},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.670199990272522},{"id":"https://openalex.org/C112789634","wikidata":"https://www.wikidata.org/wiki/Q18207010","display_name":"False positives and false negatives","level":3,"score":0.5799999833106995},{"id":"https://openalex.org/C147077947","wikidata":"https://www.wikidata.org/wiki/Q1515895","display_name":"Socioeconomic status","level":3,"score":0.5210000276565552},{"id":"https://openalex.org/C160735492","wikidata":"https://www.wikidata.org/wiki/Q31207","display_name":"Health care","level":2,"score":0.4722999930381775},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4674000144004822},{"id":"https://openalex.org/C3018553135","wikidata":"https://www.wikidata.org/wiki/Q67004728","display_name":"Medication adherence","level":2,"score":0.4320000112056732},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37459999322891235},{"id":"https://openalex.org/C167135981","wikidata":"https://www.wikidata.org/wiki/Q2146302","display_name":"Retrospective cohort study","level":2,"score":0.37040001153945923},{"id":"https://openalex.org/C2779473830","wikidata":"https://www.wikidata.org/wiki/Q1540899","display_name":"MEDLINE","level":2,"score":0.3465999960899353},{"id":"https://openalex.org/C2250968","wikidata":"https://www.wikidata.org/wiki/Q1512929","display_name":"Health equity","level":3,"score":0.3391000032424927},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3107999861240387},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.29910001158714294},{"id":"https://openalex.org/C104863432","wikidata":"https://www.wikidata.org/wiki/Q614304","display_name":"Pharmacy","level":2,"score":0.28690001368522644},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.2840999960899353},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.28349998593330383},{"id":"https://openalex.org/C2909814700","wikidata":"https://www.wikidata.org/wiki/Q18207010","display_name":"False Negative Reactions","level":2,"score":0.257099986076355}],"mesh":[{"descriptor_ui":"D000093862","descriptor_name":"Socioeconomic Disparities in Health","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000095223","descriptor_name":"White","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000098437","descriptor_name":"Prediction Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000368","descriptor_name":"Aged","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D001185","descriptor_name":"Artificial Intelligence","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D001741","descriptor_name":"Black or African American","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005260","descriptor_name":"Female","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006333","descriptor_name":"Heart Failure","qualifier_ui":"Q000188","qualifier_name":"drug therapy","is_major_topic":true},{"descriptor_ui":"D006333","descriptor_name":"Heart Failure","qualifier_ui":"Q000208","qualifier_name":"ethnology","is_major_topic":true},{"descriptor_ui":"D006630","descriptor_name":"Hispanic or Latino","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008297","descriptor_name":"Male","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008875","descriptor_name":"Middle Aged","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012189","descriptor_name":"Retrospective Studies","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016903","descriptor_name":"Drug Monitoring","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D054625","descriptor_name":"Healthcare Disparities","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":3,"locations":[{"id":"doi:10.1093/jamia/ocag097","doi":"https://doi.org/10.1093/jamia/ocag097","is_oa":false,"landing_page_url":"https://doi.org/10.1093/jamia/ocag097","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,"listed_in":["anvur-scientific","ccf-b","cwts-core","dongbi-b","doyens","jufo-2","ki-jl-2","medline","norway-1","poland-140","russia-white-list-1","vabb-shw"],"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:42350262","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/42350262","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,"listed_in":[],"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":"Journal Article"},{"id":"pmh:oai:pubmedcentral.nih.gov:13630287","doi":null,"is_oa":true,"landing_page_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC13630287/","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,"listed_in":[],"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":"J Am Med Inform Assoc","raw_type":"Text"}],"best_oa_location":{"id":"pmh:oai:pubmedcentral.nih.gov:13630287","doi":null,"is_oa":true,"landing_page_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC13630287/","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,"listed_in":[],"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":"J Am Med Inform Assoc","raw_type":"Text"},"sustainable_development_goals":[{"score":0.9907000064849854,"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3"},{"score":0.9629999995231628,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"study_designs":[{"display_name":"Observational Study","id":"https://openalex.org/study-designs/observational-study"}],"awards":[{"id":"https://openalex.org/G3594891887","display_name":"Impact of Guideline \u201cValue Statements\u201d on Drug Coverage Policies and Clinician Perspectives","funder_award_id":"23CDA1042602","funder_id":"https://openalex.org/F4320306230","funder_display_name":"American Heart Association"}],"funders":[{"id":"https://openalex.org/F4320306230","display_name":"American Heart Association","ror":"https://ror.org/013kjyp64"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W2981869278","https://openalex.org/W2986579378","https://openalex.org/W3044259901","https://openalex.org/W3115817852","https://openalex.org/W3137261348","https://openalex.org/W3197483280","https://openalex.org/W4214839143","https://openalex.org/W4225137236","https://openalex.org/W4389794809","https://openalex.org/W4392638077","https://openalex.org/W4396766072","https://openalex.org/W4403107901","https://openalex.org/W4403776672","https://openalex.org/W4404691074","https://openalex.org/W4413107286","https://openalex.org/W4414105960","https://openalex.org/W4414727576"],"related_works":["https://openalex.org/W7171414023","https://openalex.org/W3043023066","https://openalex.org/W3046113390","https://openalex.org/W2981869278","https://openalex.org/W7141166538","https://openalex.org/W4392314714","https://openalex.org/W4399381610","https://openalex.org/W7163741081","https://openalex.org/W3089632904","https://openalex.org/W7127291781"],"abstract_inverted_index":{"OBJECTIVE:":[0],"Using":[1],"AI":[2],"algorithms":[3],"can":[4],"exacerbate":[5],"health":[6,27,51],"disparities":[7,28,181,226],"if":[8,195],"care":[9,87],"or":[10],"resources":[11],"are":[12],"allocated":[13],"away":[14],"from":[15],"underserved":[16],"populations.":[17],"We":[18,65],"evaluated":[19],"an":[20,49,54],"algorithm":[21,55,123,133,158],"for":[22,138,184],"its":[23],"potential":[24],"to":[25,61,106,166,173,246],"worsen":[26,225],"across":[29,127,208],"different":[30],"clinical":[31,109,185,242],"use":[32,110,176,229,243],"cases.":[33,111],"MATERIALS":[34],"AND":[35],"METHODS:":[36],"This":[37],"was":[38,125,182,206],"a":[39],"retrospective":[40],"study":[41],"of":[42,179,197,236,241],"patients":[43,116],"with":[44,82],"heart":[45],"failure":[46],"(HF)":[47],"at":[48],"academic":[50],"system":[52],"using":[53,77],"that":[56,220],"predicts":[57],"pharmacy":[58],"fill":[59],"nonadherence":[60,140,198],"evidence-based":[62],"HF":[63,86],"medications.":[64],"compared":[66],"prediction":[67,223],"performance":[68],"metrics":[69],"(accuracy,":[70],"false":[71,74,136,162,188,213,216],"positive":[72,214],"rate,":[73],"negative":[75,217],"rate),":[76],"rate-ratios":[78],"(RRs),":[79],"between":[80],"subgroups":[81],"and":[83,97,129,150,215],"without":[84],"known":[85],"disparities:":[88],"below":[89],"vs":[90,99,143,152,168],"above":[91],"median":[92],"neighborhood-level":[93],"socioeconomic":[94],"status":[95],"(nSES)":[96],"Black":[98,151,167],"White":[100,153,169],"race.":[101],"Results":[102],"were":[103],"then":[104],"applied":[105,172],"3":[107,174],"hypothetical":[108,175],"RESULTS:":[112],"Among":[113],"34":[114],"697":[115],"(13%":[117],"Black,":[118],"10%":[119],"Hispanic,":[120],"65%":[121],"White),":[122],"accuracy":[124,205],"similar":[126,207],"nSES":[128,145],"racial":[130],"subgroups.":[131,156,170],"The":[132,157],"assigned":[134,160],"more":[135],"positives":[137,189],"medication":[139],"among":[141],"low":[142],"high":[144],"(RR":[146],"[95%CI]":[147],"1.50":[148],"[1.44-1.56])":[149],"(2.05":[154],"[1.92-2.19])":[155],"also":[159],"fewer":[161],"negatives":[163],"(0.63":[164],"[0.59-0.67])":[165],"When":[171],"cases,":[177,230],"worsening":[178,249],"existing":[180],"pertinent":[183],"applications":[186],"where":[187],"could":[190],"be":[191],"particularly":[192],"harmful":[193],"(e.g,":[194],"predictions":[196,237],"prompted":[199],"lower":[200],"treatment":[201],"priority).":[202],"DISCUSSION:":[203],"Although":[204],"demographic":[209],"groups,":[210],"differences":[211],"in":[212,227,238],"rates":[218],"revealed":[219],"the":[221,239],"same":[222],"may":[224],"some":[228],"but":[231],"not":[232],"others.":[233],"CONCLUSION:":[234],"Evaluation":[235],"context":[240],"is":[244],"essential":[245],"avoid":[247],"unintentionally":[248],"inequities.":[250]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-11-06T12:05:46.655746","created_date":"2026-06-27T00:00:00"}
