Validation of Algorithms to Identify Acute Myocardial Infarction, Stroke, and Cardiovascular Death in German Health Insurance Data

Abstract

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.

Design and validation of algorithms to identify venous thromboembolism in the French National Healthcare Database

“…A previous work conducted in data from the French National Healthcare Database (Système National des Données de Santé-SNDS) echoed by a German study demonstrated that anonymized patient profiles reconstituted from claims data (i.e., reconstituted electronic health records-rEHR) were a relevant material to conduct case adjudication. 3,4 The objective of this paper is to introduce the algorithm designed in the French SNDS to identify VTE in outpatient and inpatient settings, as well as the results of the intra-database validation conducted to assess its performance. This algorithm was developed, implemented, and validated in the framework of an international PASS study focused on the safety of baricitinib in patients with rheumatoid arthritis.…”

“…Although the awareness of the risks related to outcome misclassification is high, 2 the implementation of classical validation studies relying on the linkage between claims records and patients' charts is not always possible for financial, technical, or legal issues. A previous work conducted in data from the French National Healthcare Database ( Système National des Données de Santé —SNDS) echoed by a German study demonstrated that anonymized patient profiles reconstituted from claims data (i.e., reconstituted electronic health records—rEHR) were a relevant material to conduct case adjudication 3,4 …”

Validation to correct for outcome misclassification bias

“…Suppose one were interested in occurrence of serious acute nonfatal myocardial infarction (AMI). A primary algorithm might require a primary hospital discharge diagnosis of AMI 26,27 . To assess sensitivity of this algorithm in the study population, a more sensitive screening algorithm could be developed by relaxing the requirement that the AMI diagnosis be in the primary position thus including a discharge diagnosis of AMI in any position 28 .…”

Design and validation of algorithms to identify Venous Thromboembolism in the French National Healthcare Database

“…Although the awareness of the risks related to outcome misclassification is high (2), the implementation of classical validation studies relying on the linkage between claims records and patients' charts is not always possible for financial, technical, or legal issues. A previous work conducted in data from the French National Healthcare Database (Système National des Données de Santé -SNDS) echoed by a German study demonstrated that anonymized patients profiles reconstituted from claims data (i.e., reconstituted electronic health records -rEHR) were a relevant material to conduct case adjudication (3,4).…”