Temporal Patterns of Multiple Long-Term Conditions in Individuals with Intellectual Disability Living in Wales: An Unsupervised Clustering Approach to Disease Trajectories

TL;DR

This study uses unsupervised clustering on electronic health records to identify disease trajectory patterns in individuals with intellectual disabilities, revealing age and gender-specific clusters that can inform personalized healthcare strategies.

Contribution

It introduces an unsupervised clustering method to characterize long-term condition trajectories in individuals with ID using EHR data, highlighting distinct age and gender-specific disease clusters.

Findings

Identified age and gender-specific disease clusters in individuals with ID.

Neurological conditions dominate in younger males, while circulatory and digestive conditions are prevalent in older groups.

Common conditions include mental illness, epilepsy, and reflux across all clusters.

Abstract

Identifying and understanding the co-occurrence of multiple long-term conditions (MLTC) in individuals with intellectual disabilities (ID) is vital for effective healthcare management. These individuals often face earlier onset and higher prevalence of MLTCs, yet specific co-occurrence patterns remain unexplored. This study applies an unsupervised approach to characterise MLTC clusters based on shared disease trajectories using electronic health records (EHRs) from 13069 individuals with ID in Wales (2000-2021). Disease associations and temporal directionality were assessed, followed by spectral clustering to group shared trajectories. The population consisted of 52.3% males and 47.7% females, with an average of 4.5 conditions per patient. Males under 45 formed a single cluster dominated by neurological conditions (32.4%), while males above 45 had three clusters, the largest characterised circulatory (51.8%). Females under 45 formed one cluster with digestive conditions (24.6%) as most prevalent, while those aged 45 and older showed two clusters: one dominated by circulatory (34.1%), and the other by digestive (25.9%) and musculoskeletal (21.9%) system conditions. Mental illness, epilepsy, and reflux were common across groups. These clusters offer insights into disease progression in individuals with ID, informing targeted interventions and personalised healthcare strategies.