{"doi":"10.1002/jhm.70066","title":"Intervention for hospitalized people with chronic pain and elevated risk for opioid‐related harm: A pilot randomized controlled trial","abstract":"BACKGROUND: The management of analgesia in people hospitalized with chronic pain and elevated risk for opioid-related harm is challenging. While opioid stewardship programs could provide guidance, their feasibility in this population has not been examined. OBJECTIVES: To develop a case identification tool and evaluate the feasibility of an electronic medical record (EMR)-delivered opioid stewardship and pain intervention among hospitalized people with chronic pain and elevated risk for opioid-related harm. METHODS: After developing and evaluating the operating characteristics of a case identification tool to identify people with chronic pain and elevated risk for opioid-related harm, hospitalized adults with chronic pain and elevated risk for opioid-related harm were randomized to an EMR-delivered opioid stewardship and pain intervention versus usual care. Primary outcomes were feasibility-based. Exploratory outcomes were pain-related clinical outcomes. RESULTS: The case identification tool had a sensitivity of 88.9% and a specificity of 95.7%. The trial recruited 52/97 (54%) of potential participants who completed 52/52 (100%) potential assessments and of whom 45/52 (87%) were retained in the study at 4 weeks, demonstrating feasibility. On average, both treatment arms received 56% of the recommended guideline-concordant care and there was no significant difference in opioid and pain-related care in the two groups. CONCLUSION: It is both feasible to develop an EMR-based tool to prospectively identify hospitalized people with chronic pain and elevated risk for opioid-related harm as well as recruit these individuals to an EMR-delivered opioid stewardship and pain intervention. Additional strategies to support the provision of guideline-concordant care may be warranted.","journal":"Journal of Hospital Medicine","year":2025,"id":564806,"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":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9495,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":449726,"name":"Michele Buonora","orcid":"0000-0003-1425-1938","position":1,"is_corresponding":false},{"id":376142,"name":"Alexandra M. Hajduk","orcid":"0000-0002-5800-347X","position":2,"is_corresponding":false},{"id":1468445,"name":"Adam L. Ackerman","orcid":null,"position":3,"is_corresponding":false},{"id":729063,"name":"Krishna R. Daggula","orcid":null,"position":4,"is_corresponding":false},{"id":270187,"name":"William C. Becker","orcid":"0000-0002-0788-1467","position":5,"is_corresponding":false},{"id":376143,"name":"Sarwat I. Chaudhry","orcid":"0000-0002-5614-8157","position":6,"is_corresponding":false},{"id":249729,"name":"David A. Fiellin","orcid":"0000-0002-4006-010X","position":7,"is_corresponding":false},{"id":799280,"name":"Melissa B. Weimer","orcid":"0000-0002-5624-2434","position":0,"is_corresponding":true}],"reference_count":20,"raw_metadata":null,"created_at":"2026-07-19T02:56:24.872312Z","pmid":"40271961","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":[]}