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A comparison of two algorithms to identify sudden cardiac deaths in computerized databases
Jea Young Min1,2, Carlos G Grijalva1,2, James A Morrow2
1Veterans Health Administration Tennessee Valley Healthcare System, Geriatric Research and Education Clinical Center (GRECC), HSR&D Center, Nashville, Tennessee, USA.
Pharmacoepidemiology and Drug Safety
|August 8, 2019
Summary
Two algorithms for identifying sudden cardiac death (SCD) showed low agreement. Differences in definitions and data sources, such as hospital claims and death certificates, explain the low agreement in SCD identification.
Area of Science:
- Cardiovascular Disease Epidemiology
- Health Services Research
- Biostatistics
Background:
- Sudden cardiac death (SCD) is a critical public health concern.
- Administrative data and death certificates are used to identify SCD cases.
- Previous algorithms showed high positive predictive value for SCD identification.
Purpose of the Study:
- To evaluate the agreement between two validated algorithms for identifying sudden cardiac death (SCD).
- To compare SCD identification using hospital/emergency department (ED) claims versus death certificates and claims data.
Main Methods:
- A cross-sectional study analyzed Tennessee Medicaid and death certificate data (2007-2014).
- The study population included deceased patients aged 18-64 with Medicaid enrollment.
- Algorithm 1 used ED claims; Algorithm 2 used death certificates and exclusion criteria.
Main Results:
- 34,107 deaths were identified; 4,372 were potential SCDs.
- Algorithm 1 identified 71.3% of potential SCDs; Algorithm 2 identified 39.2%.
- Only 10.5% of potential SCDs were identified by both algorithms, indicating low agreement.
Conclusions:
- There is low agreement between the two SCD identification algorithms.
- Discrepancies stem from differing SCD definitions and data sources.
- Algorithm performance varies based on data inputs (claims vs. death certificates).
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