{"doi":"10.1016/j.ekir.2020.03.019","title":"A Comparison of Death Records Between the United States Renal Data System and a Large Integrated Health Care System","abstract":"In studying treatments and outcomes of end-stage renal disease (ESRD), mortality is a major component of all studies. Thus, the completeness and accuracy of mortality data is paramount in helping researchers to assess ESRD care and to develop interventions targeted at improving survivability or quality of life. This is especially important, as the ESRD population faces one of the highest mortality rates in the nation, and the first few months after ESRD transition are the most critical.1Sim J.J. Zhou H. Shi J. et al.Disparities in early mortality among chronic kidney disease patients who transition to peritoneal dialysis and hemodialysis with and without catheters.Int Urol Nephrol. 2018; 50: 963-971Crossref PubMed Scopus (16) Google Scholar The United States Renal Data System (USRDS) maintains 1 of the largest disease registries in the United States and is a primary source of outcomes data on the U.S. ESRD population. USRDS mortality information is derived mostly from the Centers for Medicare & Medicaid Services Death Notification Form 2746 and Medical Evidence Form 2728 as reported to them by providers.2Saran R. Robinson B. Abbott K.C. et al.US Renal Data System 2017 Annual Data Report: epidemiology of kidney disease in the United States.Am J Kidney Dis. 2018; 71: A7Abstract Full Text Full Text PDF PubMed Scopus (584) Google Scholar Although a small number of studies have examined the completeness of the mortality data maintained by the USRDS,3Holley J.L. A single-center review of the death notification form: discontinuing dialysis before death is not a surrogate for withdrawal from dialysis.Am J Kidney Dis. 2002; 40: 525-530Abstract Full Text Full Text PDF PubMed Scopus (21) Google Scholar, 4Perneger T.V. Klag M.J. Whelton P.K. Cause of death in patients with end-stage renal disease: death certificates vs registry reports.Am J Public Health. 1993; 83: 1735-1738Crossref PubMed Scopus (66) Google Scholar, 5Rocco M.V. Yan G. Gassman J. et al.Comparison of causes of death using HEMO Study and HCFA end-stage renal disease death notification classification systems. The National Institutes of Health-funded Hemodialysis. Health Care Financing Administration.Am J Kidney Dis. 2002; 39: 146-153Abstract Full Text Full Text PDF PubMed Scopus (94) Google Scholar, 6USRDSHow good are the data? USRDS data validation special study.Am J Kidney Dis. 1992; 20: 68-83PubMed Google Scholar, 7USRDSCompleteness and reliability of USRDS data: comparisons with the Michigan Kidney Registry.Am J Kidney Dis. 1992; 20: 84-88Google Scholar most of this work was done many years ago, some for small subsets of the population, and therefore may not reflect the current state. To address this gap, we performed a retrospective cohort study comparing mortality records from Kaiser Permanente Southern California (KPSC) with the USRDS registry among ESRD patients between January 1, 2007 and December 31, 2016. KPSC is a large integrated healthcare system that cares for a racially/ethnically and socioeconomically diverse population of 6 million members. It maintains a comprehensive Research Data Warehouse with data from its electronic health record and other sources. Mortality information, including death date, is primarily obtained from the linkage to California State Death Master Files, supplemented by 6 data sources: California State Multiple Cause of Death Master Files, Social Security Administration (SSA) Death Master Files, KPSC hospital and emergency room records, KPSC Perinatal Services System files, KPSC Membership System files, and claims submitted to KPSC from outside facilities or information reported to the Health Plan directly.8Chen W. Yao J. Liang Z. et al.Temporal trends in mortality rates among Kaiser Permanente Southern California health plan enrollees, 2001-2016.Perm J. 2019; 23Crossref Scopus (13) Google Scholar In this cohort, KPSC members with ESRD were matched to USRDS data by Social Security Number, name, sex, and date of birth. Demographic chara","journal":"Kidney International Reports","year":2020,"id":85377,"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":6,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.6505,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2020-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":436521,"name":"John J. Sim","orcid":"0000-0001-9456-8243","position":1,"is_corresponding":false},{"id":436522,"name":"Hui Zhou","orcid":"0000-0002-6491-7745","position":2,"is_corresponding":false},{"id":436523,"name":"Jiaxiao Shi","orcid":"0000-0001-8397-3729","position":3,"is_corresponding":false},{"id":379578,"name":"Steven J. Jacobsen","orcid":null,"position":4,"is_corresponding":false},{"id":436520,"name":"Sally F. Shaw","orcid":"0000-0002-6553-1772","position":0,"is_corresponding":true}],"reference_count":9,"raw_metadata":null,"created_at":"2026-07-18T21:56:02.794896Z","pmid":"32518873","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":[]}