ArticleClinical epidemiology2025
The Impact of Low EHR-Continuity on Effect Estimates: Evidence from Two EHR-Medicare Linked Databases.
Article in Clinical epidemiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
5 authors.
Funding
Abstract
Purpose: To compare the effect estimates obtained from patients with different levels of electronic health record (EHR)-continuity in four empirical studies: risk of pneumonia among 1) new users of proton pump inhibitors (PPI) vs H2 receptor antagonists, or 2) new users of PPI vs non-PPI users; risk of major bleeding among 3) new users of warfarin vs direct-acting oral anticoagulants, or 4) new users of oral anti-coagulants (OAC) vs non-OAC users. Patients and Methods: Patients were identified in 2 US EHR systems (MA system, NC system) linked with Medicare claims data (2007/1/1 - 2014/12/31) separately. We calculated incidence rates (IR), incidence rate differences (IRD), and hazard ratios (HR) in the total linked study population and after excluding patients with the lowest 25%, 50%, or 75% of EHR-continuity scores. We quantified bias in IRD and propensity score (PS) decile-adjusted HR. Results: In the MA system, IRs based on EHR-only data underestimated true rates by 44.1% to 76.2%, reduced to 12.9% to 46.5%. After excluding the lowest 75% of EHR-continuity patients, underestimation was more pronounced in non-user comparator designs. Absolute IRD bias was small for PPI vs H2RA (0.4%) and warfarin vs DOAC (0.7%), but larger for PPI vs non-PPI (19.1%) and OAC vs non-OAC (7.8%). Relative HR bias was 13.3% (PPI vs H2RA), 18.9% (PPI vs non-PPI), 3.0% (warfarin vs DOAC), and 31.5% (OAC vs non-OAC). Excluding lower-continuity patients and PS adjustment reduced IRD bias, while restricting to higher-continuity patients modestly improved HR bias. Conclusion: 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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