Detection of Alzheimer disease and related dementias (ADRD) is a challenge in primary care settings.
We conducted a randomized clinical trial (RCT) to evaluate the effectiveness of a combined Quick Dementia Rating System (QDRS) and Passive Digital Marker (PDM) approach for the detection of ADRD in primary care.
The QDRS is a patient-reported outcome measure, while the PDM is a machine learning algorithm that uses electronic health record (EHR) data. Both can be embedded in the EHR for ease of use.
5,325 patients from 9 urban federally qualified health centers affiliated with Eskenazi Health in Indianapolis were included in this study.
This RCT found that a combined scalable approach using PROs coupled with a PDM increased the incidence rate of ADRD diagnosis within 12 months by one-third.
Moreover, the combined approach did not require additional time, labor, or effort from the clinical team.
The scalability feature of combining the QDRS and the PDM could be replicated using other tools that use the passive data processes of the PDM and the QDRS.
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