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Data variability across Canadian administrative health databases: Differences in content, coding, and completeness.

Carla M Doyle1, Lisa M Lix2, Brenda R Hemmelgarn3,4

  • 1Centre for Clinical Epidemiology, Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Canada.

Pharmacoepidemiology and Drug Safety
|September 12, 2019
PubMed
Summary
This summary is machine-generated.

Database differences impact drug safety studies. Variations in administrative data across Canadian research centers led to differing results for domperidone and cardiac risk, highlighting the need to account for data heterogeneity in distributed networks.

Keywords:
administrative health databasespharmacoepidemiologyprovincial Canadian databaseresearch networks

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Area of Science:

  • Pharmacovigilance
  • Health Services Research
  • Epidemiology

Background:

  • The Canadian Network for Observational Drug Effect Studies (CNODES) utilizes administrative data for drug safety and effectiveness research.
  • Distributed databases enable rapid drug safety signal detection but can be subject to variations.

Purpose of the Study:

  • To compare provincial administrative databases within CNODES.
  • To illustrate how database differences can impact a study on domperidone and the risk of ventricular tachyarrhythmia and sudden cardiac death (VT/SCD).

Main Methods:

  • Assessed variations in International Classification of Diseases (ICD) coding systems and hospital discharge abstract data across CNODES sites.
  • Examined the impact of missing hospital diagnosis types on outcome misclassification and risk estimates.

Main Results:

  • Incidence rates of VT/SCD varied significantly across provinces, from 19.8 in British Columbia to 53.4 per 10,000 person-years in Quebec.
  • Missing hospital diagnosis data led to outcome misclassification and varied risk estimates.
  • Most provinces showed an increased risk of VT/SCD with domperidone, but Quebec observed a null effect (rate ratio 1.06; 95% CI 0.79-1.41).

Conclusions:

  • Variations in administrative data characteristics across research centers can influence study results in distributed networks.
  • Identifying sources of database heterogeneity is crucial for evaluating potential biases.
  • Considering data variation is essential for accurate drug safety and effectiveness studies in distributed research networks.