# Cluster Analysis of Healthcare Utilization Patterns in Patients with Comorbid Chronic Obstructive Pulmonary Disease and Atrial Fibrillation

## TL;DR

This study identifies three distinct patient groups with COPD and AF based on healthcare usage patterns, showing different outcomes and suggesting the need for tailored care strategies.

## Contribution

The novel use of cluster analysis on real-world data reveals distinct clinical phenotypes among patients with COPD and AF, highlighting the importance of proactive care for high-risk groups.

## Key findings

- Three distinct phenotypes were identified with differing healthcare utilization and mortality rates.
- The low-frequency utilization phenotype had the highest mortality and minimal outpatient care.
- Phenotype-specific patterns persisted until fatal outcomes, emphasizing the need for targeted interventions.

## Abstract

Background/Objectives: This study aimed to use cluster analysis of healthcare utilization patterns to identify distinct clinical phenotypes in patients with comorbid chronic obstructive pulmonary disease (COPD) and atrial fibrillation (AF) and to assess their associations with demographic characteristics and clinical outcomes. Methods: A retrospective cohort study was conducted using data from 1247 patients with COPD and AF extracted from a regional medical information system (Lipetsk Region, period 2021–2025). The k-means algorithm was used to cluster patients based on the average number of medical encounters per three-character ICD-10 categories. Groups were compared using descriptive and analytical statistical methods with correction for multiple comparisons. Results: The k-means algorithm identified three distinct clusters (phenotypes), which differed significantly in demographics, comorbidity structure, and mortality. Cluster 1 (“High-frequency utilization phenotype”, 25.3%): characterized by high utilization for acute respiratory infections, metabolic, and urological diseases; demonstrated the lowest mortality (10.1%). Cluster 2 (“Cerebrovascular Phenotype”, 32.3%): characterized by chronic cerebrovascular pathology and its sequelae (codes I67, I69); had intermediate mortality (20.8%). Cluster 3 (“Low-frequency utilization phenotype”, 42.4%): distinguished by minimal utilization for “outpatient” reasons alongside the highest mortality (31.1%) and a high proportion of deaths from respiratory failure. Analysis within the deceased patient subgroup confirmed the persistence of specific utilization patterns for each phenotype right up until the fatal outcome. Conclusions: Cluster analysis of real-world clinical practice data identified three discrete phenotypes of patients with comorbid COPD and AF, which have fundamentally different clinical–behavioral trajectories and prognoses. These findings justify the need for differentiated organizational approaches, particularly the development of proactive strategies for the active detection and engagement in follow-up care of patients with the low-frequency utilization phenotype, which is associated with the worst outcomes.