Investigating Primary Care Indications to Improve Electronic Health Record in Dementia Target Trial Emulation

TL;DR

This study explores how including primary care provider encounter data in electronic health record analyses influences the accuracy of emulating clinical trials for dementia, highlighting its potential to improve data quality.

Contribution

It introduces the use of PCP encounter indicators as a novel criterion to enhance EHR-based trial emulation, showing its impact on treatment effect estimates.

Findings

Including PCP data affects estimated drug effects on dementia onset.

Using PCP as an eligibility criterion alters treatment effect estimates.

PCP encounter information correlates with more comprehensive EHR records.

Abstract

Missing data, inaccuracies in medication lists, and recording delays in electronic health records (EHR) are major limitations for target trial emulation (TTE), the process by which EHR data are used to retrospectively emulate a randomized control trial. EHR TTE relies on recorded data that proxy true drug exposures and outcomes. We investigate the under-utilized criterion that a patient has indications of primary care provider (PCP) encounters within the EHR. Such patients tend to have more records overall and a greater proportion of the types of encounters that materialize comprehensive and up-to-date records. We examine the impact of including a PCP feature in the TTE model or as an eligibility criterion for cohort selection, contrasted with ignoring it altogether. To that end, we compare the estimated effects of two first line antidiabetic drug classes on the onset of Alzheimer's Disease and Related Dementias (ADRD). We find that the estimated treatment effect is sensitive to the consideration of a PCP feature, particularly when used as an eligibility criterion. Our work suggests that this PCP feature should be further researched.