ArticlePopulation health metrics2006
Accuracy and completeness of mortality data in the Department of Veterans Affairs.
Article in Population health metrics, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 319 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
319 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Repurposing anti-inflammasome NRTIs for improving insulin sensitivity and reducing type 2 diabetes development.Nature communications · 2020Pooled it
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- More intensive therapy as more effective treatment for frail patients with multiple myeloma [corrected].Blood advances · 2023Trial
- Comparison of Characteristics and Outcomes of Veterans With Stable Ischemic Heart Disease Enrolled in the COURAGE Trial Versus the Veterans Affairs Clinical Assessment, Reporting, and Tracking Program.The American journal of cardiology · 2022Trial
- Identifying transient ischemic attack (TIA) patients at high-risk of adverse outcomes: development and validation of an approach using electronic health record data.BMC neurology · 2022Trial
- Colonoscopy vs. Fecal Immunochemical Test in Reducing Mortality From Colorectal Cancer (CONFIRM): Rationale for Study Design.The American journal of gastroenterology · 2017Trial
- Validation of an all-source composite mortality endpoint in the US population.Journal of comparative effectiveness research · 2026Article
- Immune Checkpoint Inhibitor-Related Myositis and Associated Triad Overlap Syndrome.Arthritis care & research · 2026Article
- Article
- Reply to "The question of whether narcolepsy increases mortality should be answered based on reliable studies".Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2026Article
- Trends in lung cancer survival: superior outcomes in US Veterans compared with the general population.JNCI cancer spectrum · 2026Article
- Association of Antidiabetic Medication Classes With Survival Outcomes in Pulmonary Hypertension Patients With Diabetes.Pulmonary circulation · 2026Article
- Digital quality measure of potentially avoidable emergency presentations among patients with colorectal cancer.BMJ quality & safety · 2026Article
- Mortality in narcolepsy and other sleep clinic patients: a 25-year propensity-matched VA cohort study.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2026Article
- Association of Intravenous Versus Oral Iron Therapy With Clinical Outcomes in Patients With Advanced CKD.Kidney medicine · 2026Article
- Concordance of Death Information Between Two Health Systems Serving the Same Region and the Social Security Administration Death Master File: Retrospective Observational Study.JMIR medical informatics · 2026Observational
- A digital quality measure for emergency presentation of pancreatic cancer.British journal of cancer · 2026Article
- Adherence to Postoperative Survivorship Quality Metrics in Early-Stage Non-Small Cell Lung Cancer.The Annals of thoracic surgery · 2026Article
- Frequency of intravenous-to-oral antibiotic switch in VA hospitalized patients with community-acquired pneumonia.Infection control and hospital epidemiology · 2026Article
- Real-world overall survival comparison between first-line Bruton tyrosine kinase inhibitors in treating chronic lymphocytic leukemia/small lymphocytic lymphoma: An analysis of Veterans Health Administration data.Journal of managed care & specialty pharmacy · 2026Article
259 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundOne of the national mortality databases in the U.S. is the Beneficiary Identification and Record Locator Subsystem (BIRLS) Death File that contains death dates of those who have received any benefits from the Department of Veterans Affairs (VA). The completeness of this database was shown to vary widely from cohort to cohort in previous studies. Three other sources of death dates are available in the VA that can complement the BIRLS Death File. The objective of this study is to evaluate the completeness and accuracy of death dates in the four sources available in the VA and to examine whether these four sources can be combined into a database with improved completeness and accuracy.
methodsA random sample of 3,000 was drawn from 8.3 million veterans who received benefits from the VA between 1997 and 1999 and were alive on January 1, 1999 according to at least one source. Death dates found in BIRLS Death File, Medical SAS Inpatient Datasets, Medicare Vital Status, and Social Security Administration (SSA) Death Master File were compared with dates obtained from the National Death Index. A combined dataset from these sources was also compared with National Death Index dates.
resultsCompared with the National Death Index, sensitivity (or the percentage of death dates correctly recorded in a source) was 77.4% for BIRLS Death File, 12.0% for Medical SAS Inpatient Datasets, 83.2% for Medicare Vital Status, and 92.1% for SSA Death Master File. Over 95% of death dates in these sources agreed exactly with dates from the National Death Index. Death dates in the combined dataset demonstrated 98.3% sensitivity and 97.6% exact agreement with dates from the National Death Index.
conclusionThe BIRLS Death File is not an adequate source of mortality data for the VA population due to incompleteness. When the four sources of mortality data are carefully combined, the resulting dataset can provide more timely data for death ascertainment than the National Death Index and has comparable accuracy and completeness.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.