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

Lisa M Lix1, Shamsia Sobhan2, Audray St-Jean3

  • 1Department of Community Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada. lisa.lix@umanitoba.ca.

Insights

An algorithm using administrative health records to identify cardiovascular deaths showed moderate accuracy. Its validity varied across different healthcare systems and locations, highlighting potential differences in data recording practices.

Area of Science:

  • Health Informatics
  • Cardiovascular Epidemiology
  • Data Science in Healthcare

Background:

  • Cardiovascular death is a key outcome in studies of new medical treatments.
  • Vital statistics are ideal for mortality data but may not be accessible for linkage.
  • Assessing administrative health records for cardiovascular death identification is crucial for population-based research.

Purpose of the Study:

  • To evaluate the validity of an algorithm for identifying cardiovascular deaths using administrative health records.
  • To compare algorithm performance against vital statistics registrations as the reference standard.

Main Methods:

  • Utilized administrative health records from a cohort study on sodium-glucose cotransporter-2 (SGLT2) inhibitors (2013-2018).
  • Included data from five Canadian provinces and the UK Clinical Practice Research Datalink (CPRD).
  • Calculated sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for the algorithm, stratifying by site, location of death, sex, and age.

Main Results:

  • The algorithm demonstrated moderate overall validity when compared to vital statistics.
  • Overall sensitivity was 64.8% and specificity was 74.9%.
  • Significant variation in performance was observed across different study sites and healthcare systems.

Conclusions:

  • The algorithm for identifying cardiovascular deaths from administrative health records has moderate validity.
  • Variations in algorithm performance across sites suggest differences in diagnostic coding and healthcare utilization.
  • Further refinement may be needed to improve accuracy in diverse healthcare settings.
Abstract

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