J Alzheimers Dis. 2024 May 23. doi: 10.3233/JAD-240027. Online ahead of print.

ABSTRACT

BACKGROUND: Diagnostic codes can be instrumental for case identification in Alzheimer’s disease (AD) research; however, this method has known limitations and cannot distinguish between disease stages. Clinical notes may offer more detailed information including AD severity and can complement diagnostic codes for case identification.

OBJECTIVE: To estimate prevalence of mild cognitive impairment (MCI) and AD using diagnostics codes and clinical notes available in the electronic healthcare record (EHR).

METHODS: This was a retrospective study in the Veterans Affairs Healthcare System (VAHS). Health records from Veterans aged 65 years or older were reviewed during Fiscal Years (FY) 2010-2019. Overall, 274,736 and 469,569 Veterans were identified based on a rule-based algorithm as having at least one clinical note for MCI and AD, respectively; 201,211 and 149,779 Veterans had a diagnostic code for MCI and AD, respectively. During FY 2011-2018, likely MCI or AD diagnosis was defined by≥2 qualifiers (i.e., notes and/or codes)≥30 days apart. Veterans with only 1 qualifier were considered as suspected MCI/AD.

RESULTS: Over the 8-year study, 147,106 and 207,225 Veterans had likely MCI and AD, respectively. From 2011 to 2018, yearly MCI prevalence increased from 0.9% to 2.2%; yearly AD prevalence slightly decreased from 2.4% to 2.1%; mild AD changed from 22.9% to 26.8%, moderate AD changed from 26.5% to 29.1%, and severe AD changed from 24.6% to 30.7.

CONCLUSIONS: The relative distribution of AD severities was stable over time. Accurate prevalence estimation is critical for healthcare resource allocation and facilitating patients receiving innovative medicines.

PMID:38788073 | DOI:10.3233/JAD-240027