Dementia Prior to MCI? Exploring Frequency and Factors Associated with Diagnostic Discrepancies in a Large EMR System

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BACKGROUND: Mild cognitive impairment (MCI) is an early stage of cognitive decline, typically preceding dementia. However, the temporal order of these diagnostic categories in real-world clinical practice may be reversed, having significant clinical implications for patient care and family burden. This study investigates demographic and clinical predictors of these diagnostic discrepancies within a large metropolitan healthcare system. METHOD: We categorized patients aged 50+ who received a dementia diagnosis at UCSF Health Center (N = 10,121, Table 1) into two groups: the reference group (diagnosed with incident dementia and no subsequent MCI diagnosis, N = 8,926) and the diagnostic discrepancy group (diagnosed with incident dementia and subsequent MCI, N = 1,195). Logistic regression models estimated associations of demographic (sex, age, race/ethnicity, preferred language), clinical (CVD Burden, Charlson Comorbidity Index, and key ICD codes identified via chi-square and random forest models), and care setting (clinic specialty) factors with diagnostic discrepancies between cohorts (Figure 1). RESULT: Patients were more likely to experience diagnostic discrepancies if they were younger (OR=1.04 per year of age, 95%CI: 1.03-1.05), were Spanish-speaking (OR=1.75, 95%CI: 1.37-2.24), had higher CVD burden (OR = 1.07, 95% CI: 1.04-1.10), or were initially diagnosed in primary care/internal medicine settings (OR = 1.28, 95% CI: 1.09-1.49). ICD codes linked to higher odds of experiencing diagnostic discrepancies included dizziness (OR = 1.35, 95% CI: 1.10-1.65), gait abnormalities (OR = 1.32, 95% CI: 1.08-1.62), and general symptoms (e.g., fever) (OR = 1.68, 95% CI: 1.42-1.99; Figure 2). AUC-ROC from fully adjusted models was 0.698. CONCLUSION: This study identified demographic, clinical, and care setting variables associated with diagnostic discrepancies in a large patient population at a metropolitan health center. Our results emphasize the importance of continued efforts to understand and address inequities in diagnostic pathways, which are especially relevant in the current era of disease-modifying treatments targeting early disease processes. We will discuss the implications of these findings for clinical care and the development of targeted interventions for improved and equitable diagnostic workflows.

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