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Platzbecker-et-al_2022_Validation of Algorithms to Identify Acute Myocardial Infarction.pdf 586,90KB
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1000 Titel
  • Validation of Algorithms to Identify Acute Myocardial Infarction, Stroke, and Cardiovascular Death in German Health Insurance Data
1000 Autor/in
  1. Platzbecker, Katharina |
  2. Voss, Annemarie |
  3. Reinold, Jonas |
  4. Elbrecht, Anne |
  5. Biewener, Wolfgang |
  6. Prieto-Alhambra, Daniel |
  7. Jödicke, Annika |
  8. Schink, Tania |
1000 Erscheinungsjahr 2022
1000 LeibnizOpen
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2022-11-10
1000 Erschienen in
1000 Quellenangabe
  • 14:1351-1361
1000 FRL-Sammlung
1000 Copyrightjahr
  • 2022
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.2147/CLEP.S380314 |
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9661914/ |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • PURPOSE: Validation of outcomes allows measurement of and correction for potential misclassification and targeted adjustment of algorithms for case definition. The purpose of our study was to validate algorithms for identifying cases of acute myocardial infarction (AMI), stroke, and cardiovascular (CV) death using patient profiles, ie, chronological tabular summaries of relevant available information on a patient, extracted from pseudonymized German claims data. PATIENTS AND METHODS: Based on the German Pharmacoepidemiological Research Database (GePaRD), 250 cases were randomly selected (50% males) for each outcome between 2016 and 2017 based on the inclusion criteria age ≥ 50 years and continuous insurance ≥ 1 year and applying the following algorithms: hospitalization with a main diagnosis of AMI (ICD-10-GM codes I21.- and I22.-) or stroke (I63, I61, I64) or death with a hospitalization in the 60 days before with a main diagnosis of CV disease. Patient profiles were built including (i) age and sex, (ii) hospitalizations incl. diagnoses, procedures, discharge reasons, (iii) outpatient diagnoses incl. diagnostic certainty, physician specialty, (iv) outpatient encounters, and (v) outpatient dispensings. Using adjudication criteria based on clinical guidelines and risk factors, two trained physicians independently classified cases as “certain”, “probable”, “unlikely” or “not assessable”. Positive predictive values (PPVs) were calculated as percentage of confirmed cases among all assessable cases. RESULTS: For AMI, the overall PPV was 97.6% [95% confidence interval 94.8– 99.1]. The PPV for any stroke was 94.8% [91.3– 97.2] and higher for ischemic (98.3% [95.0– 99.6]) than for hemorrhagic stroke (86.5% [76.5– 93.3]). The PPV for CV death was 79.9% [74.4– 84.4]. It increased to 91.7% [87.2– 95.0] after excluding 32 cases with data insufficient for a decision. CONCLUSION: Algorithms based on hospital diagnoses can identify AMI, stroke, and CV death from German claims data with high PPV. This was the first study to show that German claims data contain information suitable for outcome validation.
1000 Sacherschließung
lokal claims data
lokal positive predictive value
lokal algorithm validation
lokal patient profiles
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
  1. https://orcid.org/0000-0003-2075-7978|https://orcid.org/0000-0001-8109-1108|https://orcid.org/0000-0001-8266-2574|https://orcid.org/0000-0003-3599-5469|https://frl.publisso.de/adhoc/uri/Qmlld2VuZXIsIFdvbGZnYW5n|https://orcid.org/0000-0002-3950-6346|https://frl.publisso.de/adhoc/uri/SsO2ZGlja2UsIEFubmlrYQ==|https://orcid.org/0000-0002-0224-1866
1000 (Academic) Editor
1000 Label
1000 Förderer
  1. UCB Biopharma UCL |
1000 Fördernummer
  1. -
1000 Förderprogramm
  1. -
1000 Dateien
1000 Förderung
  1. 1000 joinedFunding-child
    1000 Förderer UCB Biopharma UCL |
    1000 Förderprogramm -
    1000 Fördernummer -
1000 Objektart article
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1000 @id frl:6440666.rdf
1000 Erstellt am 2023-03-14T11:06:19.291+0100
1000 Erstellt von 266
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1000 Bearbeitet von 317
1000 Zuletzt bearbeitet 2023-04-21T13:42:31.371+0200
1000 Objekt bearb. Tue Mar 14 13:43:55 CET 2023
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  1. oai:frl.publisso.de:frl:6440666 |
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