{"doi":"10.1101/2024.02.23.24303292","title":"Identifying High and Low Performing Emergency General Surgery Hospitals Using Direct Standardization","abstract":"Abstract Importance Variation in outcomes for emergency general surgery conditions has been shown at the hospital level. Few have examined difference across hospitals for older adults who often present with the greatest risk. To date, no one has examined differences in the outcome for those undergoing operative and nonoperative treatment. Objective Identify high and low performing emergency general surgery (EGS) hospitals with risk-standardization to determine clinical performance differences as well as correlation between patients treated operatively and non-operatively. Design A retrospective cohort study with 30-day outcomes. Setting Nationwide study of acute care hospitals. Participants Medicare beneficiaries > 65.5 years old hospitalized for an emergency general surgery condition admitted from July 1, 2015 to June 30, 2018. Exposure Unique hospital identification. Main outcome A composite metric of 30-day mortality, adverse events, prolonged length of stay, and readmission. Results There were 536,284 total patients with a mean age of 74.4 ± 12.2 years, 55% female, 84% white with average claims-based frailty index of 0.16 ± 0.06 and mean comorbidity count of 3.57 ± 2.46. Amongst the 1866 hospitals identified, there were 3 best performing and 11 worst performing hospitals. There were weak correlations between operative and non-operative for mortality (0.10), adverse events rates (0.21), prolonged length of stay (0.32), and readmissions (0.18) at the hospital level (all p<0.001). Conclusions and Relevance Significant variation exists in EGS hospital performance with best ranked hospitals out-performing worst ranked hospitals on adverse event, mortality, prolonged length of stay and readmission. There is little association between patient outcomes for those treated with operative and non-operative care.","journal":"medRxiv","year":2024,"id":494985,"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":0.9595,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":130012,"name":"Luke Keele","orcid":"0000-0002-3859-2713","position":1,"is_corresponding":false},{"id":917169,"name":"Chris Wirtalla","orcid":null,"position":2,"is_corresponding":false},{"id":953017,"name":"Solomiya Syvyk","orcid":"0000-0003-0908-2746","position":3,"is_corresponding":false},{"id":455556,"name":"Rachel R. Kelz","orcid":"0000-0001-6635-5961","position":4,"is_corresponding":false},{"id":1341497,"name":"Drew Goldberg","orcid":"0000-0003-3768-3485","position":0,"is_corresponding":true}],"reference_count":11,"raw_metadata":null,"created_at":"2026-07-19T02:09:15.528853Z","pmid":null,"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":[]}