Related Experiment Video
Updated: Jan 19, 2026

TBase - an Integrated Electronic Health Record and Research Database for Kidney Transplant Recipients
Published on: April 13, 2021
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.
Purpose:
The Canadian Network for Observational Drug Effect Studies (CNODES) is a network of Canadian research centres using administrative data to conduct distributed drug safety and effectiveness studies. In this study, we compare the provincial administrative databases and illustrate the potential impact of database differences on a CNODES study about domperidone and the risk of ventricular tachyarrhythmia and sudden cardiac death (VT/SCD).
Methods:
We assessed the impact of varying versions and precision of the International Classification of Diseases coding system in physician claims data, and the content and completeness of hospital discharge abstracts across CNODES sites, as these variations can introduce differences in the study cohorts formed and affect study results.
Results:
In our study of 214 962 patients, hospital diagnosis type (such as most responsible, admitting, or secondary diagnosis) was missing in some provinces, resulting in misclassification of the outcome and variation in rates and risk estimates. Incidence rates of VT/SCD ranged from 19.8 (95% confidence interval [CI] 17.7-22.2) per 10 000 person-years in British Columbia to 53.4 (95% CI 50.3-56.5) in Quebec. While most provinces reported an increased risk of VT/SCD, a null effect was observed in Quebec (rate ratio 1.06; 95% CI 0.79-1.41).
Conclusions:
Distributed analyses allow for rapid responses to drug safety signals. However, variation in characteristics of the administrative data across research centres can influence study results. By identifying the sources of database heterogeneity, one can evaluate the potential biases these differences may introduce, highlighting the importance of considering such variation in distributed networks.
Insights
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.
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.
More Related Videos
09:43Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering
Published on: November 22, 2019
06:55Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
Published on: January 8, 2020
Related Concept Videos
09:00TBase - an Integrated Electronic Health Record and Research Database for Kidney Transplant Recipients
09:43Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering
06:55Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index
13:44Project-Based Learning Guidelines for Health Sciences Students: An Analysis with Data Mining and Qualitative Techniques
07:31Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
08:12Calculating Heart Rate Variability from ECG Data from Youth with Cerebral Palsy During Active Video Game Sessions