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Trends in the use of validated claims-based algorithms in Japanese post-marketing database studies
Chieko Ishiguro1, Takahiro Nonaka2
1Laboratory of Clinical Epidemiology, Department of Data Science, Center for Clinical Sciences, Japan Institute for Health Security, Tokyo, Japan.
Background:
In pharmacoepidemiological research, misclassification is a concern with claims-based algorithms (also called computable phenotypes). Validating them is crucial, particularly within regulatory settings. However, the extent of their application remains unclear globally.
Objectives:
This study aimed to investigate the frequency and trends of validated claims-based algorithms use in post-marketing database studies.
Method:
We reviewed all Japanese risk management plans published until January 2023, identifying four issue types [Effectiveness Issues (EI), Important Identified Risks (IIR), Important Potential Risks (IPR), and Important Missing Information (IMI)] that were planned to use a claims-based algorithm in post-marketing database studies. We then calculated the proportion of issues intending to use a validated claims-based algorithm, and performed subgroup analyses by issue type.
Results:
Of 68 issues (3 EI, 47 IIR, 13 IPR, 5 IMI), 15 (22.1%) planned to use a validated algorithm, all for outcome definitions; 10 to conduct new validation studies and 5 to refer to existing studies, including studies with high positive predictive value and sensitivity. Subgroup analyses by issue type showed that the proportions were 100% for EI, 17.0% for IIR, 30.8% for IPR, and 0% for IMI.
Conclusion:
Validated algorithm use was the highest for effectiveness issues but limited for safety, suggesting that results from these post-marketing database studies for safety issues may not provide sufficient evidence, highlighting the need to promote the use of validated claims-based algorithms. Future studies should use more recent data, compare the use of validated algorithms between Japan and other countries, and explore barriers to their adoption.
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