ArticleBMJ open2019
Implementation of an algorithm for the identification of breast cancer deaths in German health insurance claims data: a validation study based on a record linkage with administrative mortality data.
Article in BMJ open, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 13 citations in OpenAlex.
- The EU project Real4Reg: unlocking real-world data with AI.Health research policy and systems · 2025Article
- Implementation and Evaluation of a Breast Cancer Disease Model Using Real-World Claims Data in Germany from 2010 to 2020.Cancers · 2024Article
- The Lack of a Standardized Definition of Chronic Dialysis Treatment in German Statutory Health Insurance Claims Data—Effects on Estimated Incidence and Mortality.Deutsches Arzteblatt international · 2024Observational
- Novel Algorithm for the Estimation of Cancer Incidence Using Claims Data in Japan: A Feasibility Study.JCO global oncology · 2023Article
- Effectiveness of Mammography Screening on Breast Cancer Mortality - A Study Protocol for Emulation of Target Trials Using German Health Claims Data.Clinical epidemiology · 2022Article
- Validity of claims-based algorithms for selected cancers in Japan: Results from the VALIDATE-J study.Pharmacoepidemiology and drug safety · 2021Article
- Machine-learning model to predict the cause of death using a stacking ensemble method for observational data.Journal of the American Medical Informatics Association : JAMIA · 2021Article
- Development of algorithms for identifying patients with Crohn's disease in the Japanese health insurance claims database.PloS one · 2021Article
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Authors and funding
6 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo adapt a Canadian algorithm for the identification of female cases of breast cancer (BC) deaths to German health insurance claims data and to test and validate the algorithm by comparing results with official cause of death (CoD) data on the individual and the population level.
designValidation study, secondary data, medical claims.
settingClaims data of two statutory health insurance providers (SHIs) for inpatient and outpatient care, CoD added via record linkage with epidemiological cancer registry (ECR).
main outcome measuresBased on inpatient and outpatient diagnoses in the year before death, six algorithms were derived and the accordance of the algorithm-based CoD with the official CoD was evaluated calculating specificity, sensitivity, negative and positive predictive values (NPV, PPV). Furthermore, algorithm-based age-specific BC mortality rates covering several calendar years were calculated for the entire insured female population and compared with official national rates.
resultsOur final algorithm, derived from the NRW subsample, comprised codes indicating the presence of BC, metastases, a terminal illness phase and the absence of codes for other tumours. Overall, specificity, sensitivity, NPV and PPV of this algorithm were 97.4%, 91.3%, 98.9% and 81.7%, respectively. In the age range 40-80 years, sensitivity and PPV slightly decreased with increasing age. Algorithm-based age-specific BC mortality rates agreed well with official rates except for the age group 85 years and older.
conclusionsThe algorithm-based identification of BC deaths in German claims data is feasible and valid, except for higher ages. The algorithm to ascertain BC mortality rates in an epidemiological study seems applicable when information on the official CoD is not available in the original database.
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