{"doi":"10.1093/ofid/ofab130","title":"Development and Validation of a Multivariable Prediction Model for Missed HIV Health Care Provider Visits in a Large US Clinical Cohort","abstract":"BACKGROUND: Identifying individuals at high risk of missing HIV care provider visits could support proactive intervention. Previous prediction models for missed visits have not incorporated data beyond the individual level. METHODS: We developed prediction models for missed visits among people with HIV (PWH) with ≥1 follow-up visit in the Center for AIDS Research Network of Integrated Clinical Systems from 2010 to 2016. Individual-level (medical record data and patient-reported outcomes), community-level (American Community Survey), HIV care site-level (standardized clinic leadership survey), and structural-level (HIV criminalization laws, Medicaid expansion, and state AIDS Drug Assistance Program budget) predictors were included. Models were developed using random forests with 10-fold cross-validation; candidate models with the highest area under the curve (AUC) were identified. RESULTS: Data from 382 432 visits among 20 807 PWH followed for a median of 3.8 years were included; the median age was 44 years, 81% were male, 37% were Black, 15% reported injection drug use, and 57% reported male-to-male sexual contact. The highest AUC was 0.76, and the strongest predictors were at the individual level (prior visit adherence, age, CD4+ count) and community level (proportion living in poverty, unemployed, and of Black race). A simplified model, including readily accessible variables available in a web-based calculator, had a slightly lower AUC of .700. CONCLUSIONS: Prediction models validated using multilevel data had a similar AUC to previous models developed using only individual-level data. The strongest predictors were individual-level variables, particularly prior visit adherence, though community-level variables were also predictive. Absent additional data, PWH with previous missed visits should be prioritized by interventions to improve visit adherence.","journal":"Open Forum Infectious Diseases","year":2021,"id":178334,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":19,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.8998,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2021-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":283320,"name":"Aihua Bian","orcid":null,"position":1,"is_corresponding":false},{"id":723563,"name":"Cassandra O Schember","orcid":"0000-0001-8231-3956","position":2,"is_corresponding":false},{"id":240239,"name":"Peter F. Rebeiro","orcid":"0000-0003-1951-9104","position":3,"is_corresponding":false},{"id":286356,"name":"Jeanne Keruly","orcid":"0000-0002-8489-435X","position":4,"is_corresponding":false},{"id":305156,"name":"Kenneth H. Mayer","orcid":"0000-0001-7460-733X","position":5,"is_corresponding":false},{"id":393879,"name":"W. Christopher Mathews","orcid":null,"position":6,"is_corresponding":false},{"id":240242,"name":"Richard D. Moore","orcid":"0000-0001-8250-5069","position":7,"is_corresponding":false},{"id":240253,"name":"Heidi M. Crane","orcid":"0000-0002-3308-7005","position":8,"is_corresponding":false},{"id":371005,"name":"Elvin Geng","orcid":"0000-0002-0825-1424","position":9,"is_corresponding":false},{"id":340146,"name":"Sonia Napravnik","orcid":"0000-0002-9032-3713","position":10,"is_corresponding":false},{"id":240240,"name":"Bryan E. Shepherd","orcid":"0000-0002-3758-5992","position":11,"is_corresponding":false},{"id":313570,"name":"Michael J. Mugavero","orcid":"0000-0001-6916-6701","position":12,"is_corresponding":false},{"id":346880,"name":"April C. Pettit","orcid":"0000-0001-8832-0866","position":0,"is_corresponding":true}],"reference_count":31,"raw_metadata":null,"created_at":"2026-07-18T23:47:36.112170Z","pmid":"34327249","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}