Social Determinants Influencing the Severity of Dementia on Screening: An Observational Study in the Indian Population

Abstract

AbstractBackgroundWith increased longevity and decreased fertility rate, the percentage of population over 65 years of age is growing in India. Literacy rates, family size, socioeconomic status, and comorbidities are rapidly changing due to the increased migration from rural to urban areas. Data‐driven studies are required to determine the influence of social factors and comorbidities on the distribution of Alzheimer’s disease and related dementias (ADRD) and neurological care resources. We demonstrate results from a feasibility study that uses state‐of‐the‐art AI, data analytics, and a HIPAA‐compliant Telehealth platform to screen patients over 65 years in India for ADRD.MethodA primary care provider used a telemedicine platform, Artificial Intelligence (AI), and a standardized cognitive test to screen every consenting patient aged 65 years and older. The screening used an algorithm‐based intake tool, baseline Mini‐Mental Status Exam (MMSE), and clinical judgment of the primary care physician. We documented sociodemographic data and comorbidities: age, gender, education, living situation (family size), geographical location (urban/rural), the number and types of comorbidities.ResultNine patients (4 females, 5 males) over 65 years of age, consented and enrolled in this study. 55% (5 in 9 patients) had a bachelor’s degree or higher, 22% (2 in 9 patients) were high school graduates, 22% (2 in 9 patients) were 8th grade and below. 44% (4 in 9 patients) were from rural backgrounds, and 55% (5 in 9 patients) lived in urban backgrounds. 44% (4 in 9 patients) had one comorbidity, 11% (1 in 9 patients) had two comorbidities, 44% (4 in 9 patients) had three and more comorbidities. Out of four patients screened as mild dementia by AI (44%), three patients (75%) had two or more underlying comorbidities.ConclusionOur results demonstrate that medical comorbidities and social determinants may influence India’s ADRD severity scores and neurocognitive screening. We can use the results to address foreseeable gaps for ADRD screening and ensure equitable resource distribution via telemedicine in India. The data captured in this AI and telemedicine collaboration may provide the foundation for identifying new biomarkers and developing targeted treatments that work for ethnically diverse patients.