The Impact of Low EHR-Continuity on Effect Estimates: Evidence from Two EHR-Medicare Linked Databases

Limiting analyses to patients with higher EHR-continuity can reduce IR underestimation and bias in effect estimates, particularly on the IRD scale. While PS adjustment mitigates some bias, EHR-discontinuity remains a source of bias, especially in studies using non-user comparators. These findings underscore the importance of balancing EHR-continuity with sample size considerations in pharmacoepidemiologic research.

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Journal
Clinical Epidemiology
Published
2025-12-01
DOI
https://doi.org/10.2147/clep.s549772
Primary Topic
Meta-analysis and systematic reviews
Type
article
Field-Weighted Citation Impact
0.00

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article

The Impact of Low EHR-Continuity on Effect Estimates: Evidence from Two EHR-Medicare Linked Databases

Richard Wyss, Jie Yang, Yinzhu Jin, Kueiyu Lin et al.
Clinical Epidemiology
Meta-analysis and systematic reviews
article

The Impact of Low EHR-Continuity on Effect Estimates: Evidence from Two EHR-Medicare Linked Databases

Richard Wyss, Jie Yang, Yinzhu Jin, Kueiyu Lin, Angela Tong
article en

Abstract

Limiting analyses to patients with higher EHR-continuity can reduce IR underestimation and bias in effect estimates, particularly on the IRD scale. While PS adjustment mitigates some bias, EHR-discontinuity remains a source of bias, especially in studies using non-user comparators. These findings underscore the importance of balancing EHR-continuity with sample size considerations in pharmacoepidemiologic research.

Clinical EpidemiologyVol. Volume 17
Brigham and Women's Hospital (US), Harvard University (US), Massachusetts General Hospital (US)
National Institutes of Health
Openalex Percentile: Top 29%
Meta-analysis and systematic reviews
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