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Published in: BMC Health Services Research 1/2021

Open Access 01-12-2021 | Research

Validity of an algorithm to identify cardiovascular deaths from administrative health records: a multi-database population-based cohort study

Authors: Lisa M. Lix, Shamsia Sobhan, Audray St-Jean, Jean-Marc Daigle, Anat Fisher, Oriana H. Y. Yu, Sophie Dell’Aniello, Nianping Hu, Shawn C. Bugden, Baiju R. Shah, Paul E. Ronksley, Silvia Alessi-Severini, Antonios Douros, Pierre Ernst, Kristian B. Filion

Published in: BMC Health Services Research | Issue 1/2021

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Abstract

Background

Cardiovascular death is a common outcome in population-based studies about new healthcare interventions or treatments, such as new prescription medications. Vital statistics registration systems are often the preferred source of information about cause-specific mortality because they capture verified information about the deceased, but they may not always be accessible for linkage with other sources of population-based data. We assessed the validity of an algorithm applied to administrative health records for identifying cardiovascular deaths in population-based data.

Methods

Administrative health records were from an existing multi-database cohort study about sodium-glucose cotransporter-2 (SGLT2) inhibitors, a new class of antidiabetic medications. Data were from 2013 to 2018 for five Canadian provinces (Alberta, British Columbia, Manitoba, Ontario, Quebec) and the United Kingdom (UK) Clinical Practice Research Datalink (CPRD). The cardiovascular mortality algorithm was based on in-hospital cardiovascular deaths identified from diagnosis codes and select out-of-hospital deaths. Sensitivity, specificity, and positive and negative predictive values (PPV, NPV) were calculated for the cardiovascular mortality algorithm using vital statistics registrations as the reference standard. Overall and stratified estimates and 95% confidence intervals (CIs) were computed; the latter were produced by site, location of death, sex, and age.

Results

The cohort included 20,607 individuals (58.3% male; 77.2% ≥70 years). When compared to vital statistics registrations, the cardiovascular mortality algorithm had overall sensitivity of 64.8% (95% CI 63.6, 66.0); site-specific estimates ranged from 54.8 to 87.3%. Overall specificity was 74.9% (95% CI 74.1, 75.6) and overall PPV was 54.5% (95% CI 53.7, 55.3), while site-specific PPV ranged from 33.9 to 72.8%. The cardiovascular mortality algorithm had sensitivity of 57.1% (95% CI 55.4, 58.8) for in-hospital deaths and 72.3% (95% CI 70.8, 73.9) for out-of-hospital deaths; specificity was 88.8% (95% CI 88.1, 89.5) for in-hospital deaths and 58.5% (95% CI 57.3, 59.7) for out-of-hospital deaths.

Conclusions

A cardiovascular mortality algorithm applied to administrative health records had moderate validity when compared to vital statistics data. Substantial variation existed across study sites representing different geographic locations and two healthcare systems. These variations may reflect different diagnostic coding practices and healthcare utilization patterns.
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Metadata
Title
Validity of an algorithm to identify cardiovascular deaths from administrative health records: a multi-database population-based cohort study
Authors
Lisa M. Lix
Shamsia Sobhan
Audray St-Jean
Jean-Marc Daigle
Anat Fisher
Oriana H. Y. Yu
Sophie Dell’Aniello
Nianping Hu
Shawn C. Bugden
Baiju R. Shah
Paul E. Ronksley
Silvia Alessi-Severini
Antonios Douros
Pierre Ernst
Kristian B. Filion
Publication date
01-12-2021
Publisher
BioMed Central
Published in
BMC Health Services Research / Issue 1/2021
Electronic ISSN: 1472-6963
DOI
https://doi.org/10.1186/s12913-021-06762-0

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