DOI: 10.1101/19000422Jun 28, 2019Paper

The nature of clusters of multimorbid patients in the UK: a latent class analysis.

MedRxiv : the Preprint Server for Health Sciences
Yajing ZhuS. Kiddle

Abstract

Background Multimorbidity is one of the principal challenges facing health systems worldwide. To help understand the changes to services and policies that are required to deliver better care, we used a novel approach to investigate which diseases co-occur and how combinations are associated with mortality and service use. Methods Linked primary and secondary care electronic health records contributed by 382 general practices in England to the Clinical Practice Research Datalink (CPRD) were used. The study included a representative set of multimorbid adults (18 years old or more) with two or more long-term conditions (N=113,211). A random set of 80% of the multimorbid patients (N=90,571) were stratified by age and clustered using latent class analysis. Consistency between obtained disease profiles, classification quality and associations with demographic characteristics and primary outcomes (hospitalisation, polypharmacy and mortality) was validated in the remaining 20% of multimorbid patients (N=22,640). Findings We identified twenty patient clusters across four age strata. The clusters with the highest mortality comprised psychoactive substance and alcohol misuse (aged 18-64), coronary heart disease, depression and pain (aged ...Continue Reading

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