From Memory Loss to Dementia: Real-World Insights into Dementia Diagnosis Trajectory and Clinical Practice Patterns Unveiled by Natural Language Processing (Preprint)

Abstract

Understanding the dementia disease trajectory and clinical practice patterns in outpatient settings is vital for effective management. Knowledge about the path from initial memory loss complaints to dementia diagnosis remains limited

This study aims to 1) determine the time intervals between initial memory loss complaints and dementia diagnosis in outpatient care, 2) assess the proportion of patients receiving cognition-enhancing medication prior to dementia diagnosis, and 3) identify patient and provider characteristics that influence the time between memory complaints and diagnosis, and the prescription of cognition-enhancing medication.

This retrospective cohort study utilized a large outpatient EHR database from the University of Connecticut Health Center, covering 2010-2018, with a cohort of 581 outpatients. We employed a customized deep learning-based natural language processing (NLP) pipeline to extract clinical information from electronic health record (EHR) data, focusing on cognition-related symptoms, primary caregiver relation, and medication usage. We applied descriptive statistics, linear, and logistic regression for analysis.

The NLP pipeline showed precision, recall, and F1 scores of 0.97, 0.93, and 0.95, respectively. The median time from the first memory loss complaint to dementia diagnosis was 342 days. Factors such as the location of initial complaints and diagnosis, and primary caregiver relationships significantly affected this interval. Around 25% of patients were prescribed cognition-enhancing medication before diagnosis, with the number of complaints influencing medication usage

Our NLP-guided analysis provided insights into the clinical pathways from memory complaints to dementia diagnosis and medication practices, which can enhance patient care and decision-making in outpatient settings.