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.


Journal

BMJ open
ISSN: 2044-6055
Titre abrégé: BMJ Open
Pays: England
ID NLM: 101552874

Informations de publication

Date de publication:
26 07 2019
Historique:
entrez: 28 7 2019
pubmed: 28 7 2019
medline: 7 7 2020
Statut: epublish

Résumé

To 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. Validation study, secondary data, medical claims. Claims data of two statutory health insurance providers (SHIs) for inpatient and outpatient care, CoD added via record linkage with epidemiological cancer registry (ECR). Based 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. Our 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. The 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.

Identifiants

pubmed: 31350240
pii: bmjopen-2018-026834
doi: 10.1136/bmjopen-2018-026834
pmc: PMC6661554
doi:

Types de publication

Journal Article Multicenter Study Research Support, Non-U.S. Gov't Validation Study

Langues

eng

Sous-ensembles de citation

IM

Pagination

e026834

Informations de copyright

© Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

Déclaration de conflit d'intérêts

Competing interests: None declared.

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Auteurs

Ingo Langner (I)

Clinical Epidemiology, Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany.

Christoph Ohlmeier (C)

Health Services Research, IGES Institut GmbH, Berlin, Germany.

Ulrike Haug (U)

Clinical Epidemiology, Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany.
High-Profile Research Area Health Sciences, University of Bremen, Bremen, Germany.

Hans Werner Hense (HW)

Institute of Epidemiology and Social Medicine, Westfälische Wilhelms-Universität Münster, Münster, Germany.
State Cancer Registry North Rhine Westphalia, Münster, Germany.

Jonas Czwikla (J)

High-Profile Research Area Health Sciences, University of Bremen, Bremen, Germany.
SOCIUM Research Center on Inequality and Social Policy, University of Bremen, Bremen, Germany.

Hajo Zeeb (H)

Clinical Epidemiology, Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany.
High-Profile Research Area Health Sciences, University of Bremen, Bremen, Germany.

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Classifications MeSH