{"doi":"10.17615/87dc-2f93","title":"Integrating Surveillance Data to Estimate Race/Ethnicity-specific Hysterectomy Inequalities among Reproductive-aged Women: Who's at Risk?","abstract":"Background: Inequalities by race and ethnicity in hysterectomy for noncancerous conditions suggest that some subgroups may be shouldering an unfair burden of procedure-associated negative health impacts. We aimed to estimate race- A nd ethnicity-specific rates in contemporary hysterectomy incidence that address three challenges in the literature: Exclusion of outpatient procedures, no hysterectomy prevalence adjustment, and paucity of non-White and non-Black estimates. Methods: We used surveillance data capturing all inpatient and outpatient hysterectomy procedures performed in North Carolina from 2011 to 2014 (N = 30,429). Integrating data from the Behavior Risk Factor Surveillance System and US Census population estimates, we calculated prevalence-corrected hysterectomy incidence rates and differences by race and ethnicity. Results: Prevalence-corrected estimates show that non-Hispanic (nH) Blacks (62, 95% confidence interval [CI] = 61, 63) and nH American Indians (85, 95% CI = 79, 93) per 10,000 person-years (PY) had higher rates, compared with nH Whites (45 [95% CI = 45, 46] per 10,000 PY), while Hispanic (20, 95% CI = 20, 21) and nH Asian/Pacific Islander rates (8, 95% CI = 8.0, 8.2) per 10,000 PY were lower than nH Whites. Conclusion: Through strategic surveillance data use and application of bias correction methods, we demonstrate wide differences in hysterectomy incidence by race and ethnicity. See video abstract at, http://links.lww.com/EDE/B657.","journal":"UNC Libraries","year":2024,"id":483456,"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":1,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9363,"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":35728,"name":"B.W Pence","orcid":null,"position":1,"is_corresponding":false},{"id":334889,"name":"Robert A. Hummer","orcid":"0000-0003-3058-6383","position":2,"is_corresponding":false},{"id":421984,"name":"Paul L. Delamater","orcid":"0000-0003-3627-9739","position":3,"is_corresponding":false},{"id":387620,"name":"Jennifer L. Lund","orcid":"0000-0002-1108-0689","position":4,"is_corresponding":false},{"id":236547,"name":"Whitney R. Robinson","orcid":"0000-0003-4009-0488","position":5,"is_corresponding":false},{"id":650314,"name":"Danielle R. Gartner","orcid":"0000-0002-0152-8961","position":0,"is_corresponding":true}],"reference_count":0,"raw_metadata":null,"created_at":"2026-07-19T02:07:33.718973Z","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":[]}