{"doi":"10.1111/1475-6773.13886","title":"Development of a homelessness risk screening tool for emergency department patients","abstract":"OBJECTIVE: To develop a screening tool to identify emergency department (ED) patients at risk of entering a homeless shelter, which could inform targeting of interventions to prevent future homelessness episodes. DATA SOURCES: Linked data from (1) ED patient baseline questionnaires and (2) citywide administrative homeless shelter database. STUDY DESIGN: Stakeholder-informed predictive modeling utilizing ED patient questionnaires linked with prospective shelter administrative data. The outcome was shelter entry documented in administrative data within 6 months following the baseline ED visit. Exposures were responses to questions on homelessness risk factors from baseline questionnaires. DATA COLLECTION/EXTRACTION METHODS: Research assistants completed questionnaires with randomly sampled ED patients who were medically stable, not in police/prison custody, and spoke English or Spanish. Questionnaires were linked to administrative data using deterministic and probabilistic matching. PRINCIPAL FINDINGS: Of 1993 ED patients who were not homeless at baseline, 5.6% entered a shelter in the next 6 months. A screening tool consisting of two measures of past shelter use and one of past criminal justice involvement had 83.0% sensitivity and 20.4% positive predictive value for future shelter entry. CONCLUSIONS: Our study demonstrates the potential of using cross-sector data to improve hospital initiatives to address patients' social needs.","journal":"Health Services Research","year":2021,"id":177784,"datarank":1.0111526802348845,"base_score":3.044522437723423,"endowment":3.044522437723423,"self_citation_contribution":0.4566783656585135,"citation_network_contribution":0.5544743145763711,"self_endowment_contribution":0.4566783656585135,"citer_contribution":0.5544743145763711,"corpus_percentile":null,"corpus_rank":null,"citation_count":20,"citer_count":12,"citers_with_citation_signal":8,"citers_with_endowment":8,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.5642,"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":406082,"name":"Eileen Johns","orcid":null,"position":1,"is_corresponding":false},{"id":406084,"name":"Sara Zuiderveen","orcid":null,"position":2,"is_corresponding":false},{"id":405394,"name":"Marybeth Shinn","orcid":"0000-0002-6681-8273","position":3,"is_corresponding":false},{"id":722764,"name":"Kinsey Alden Dinan","orcid":null,"position":4,"is_corresponding":false},{"id":406083,"name":"Maryanne Schretzman","orcid":null,"position":5,"is_corresponding":false},{"id":313552,"name":"Lillian Gelberg","orcid":"0000-0001-9772-0116","position":6,"is_corresponding":false},{"id":405395,"name":"Dennis P. Culhane","orcid":"0000-0002-2332-5567","position":7,"is_corresponding":false},{"id":252454,"name":"Donna Shelley","orcid":"0000-0003-1677-2577","position":8,"is_corresponding":false},{"id":405396,"name":"Tod Mijanovich","orcid":"0000-0001-8454-3018","position":9,"is_corresponding":false},{"id":405393,"name":"Kelly M. Doran","orcid":"0000-0001-8961-3724","position":0,"is_corresponding":true}],"reference_count":27,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-18T23:47:32.096934Z","pmid":"34608999","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":[]}