Healthcare Spending Before and After Mild Cognitive Impairment Diagnosis: Evidence from the NHIS-NHID in Korea

Background/Objectives: With rapid population aging, concerns about cognitive health-especially mild cognitive impairment (MCI), a prodromal stage of dementia-are growing. Although MCI prevalence is rising, limited empirical evidence exists on changes in healthcare expenditures associated with its diagnosis. This study aimed to assess shifts in medical spending before and after MCI diagnosis and to identify factors influencing healthcare costs among Korean adults. Methods: We used data from the National Health Insurance Service-National Health Information Database (NHIS-NHID) from 2020 to 2022. This study analyzed 4162 Korean adults aged ≤84 who were newly diagnosed with MCI in 2021. Annual healthcare expenditures were tracked from 2020 to 2022. Generalized estimating equations (GEEs) were employed to examine changes over time, adjusting for sociodemographic characteristics, comorbidities, healthcare utilization, and long-term care insurance (LTCI) enrollment. Results: The average annual healthcare expenditure increased from 74,767 KRW before diagnosis to 87,902 KRW after diagnosis, reflecting a 12.51% rise. Regression analysis showed a significant decrease in costs in the year prior to diagnosis (β = -0.117, p < 0.01) and an increase in the year following diagnosis (β = 0.061, p < 0.01). Higher expenditures were associated with greater outpatient visits (β = 0.385, p < 0.01), longer hospital stays (β = 0.039, p < 0.01), LTCI enrollment (non-graded: β = 0.035, p = 0.02; graded: β = 0.027, p = 0.04) and higher comorbidity levels (CCI = 2: β = 0.088, p < 0.01, CCI ≥ 3: β = 0.192, p < 0.01). Conversely, older age (β = -0.003, p = 0.02) and female sex (β = -0.093, p < 0.01) were associated with lower costs. Sex-stratified analyses revealed consistent cost trends but different predictors for male and female patients. Conclusions: Healthcare expenditures rise significantly after MCI diagnosis. Early identification and interventions tailored to patient characteristics-such as age, sex, and comorbidity status-may help manage future costs and support equitable care for older adults.