Comorbidity Patterns and Healthcare Resource Utilization in COPD Patients: A Retrospective Analysis Using Association Rules

Abstract

Background Patients with chronic obstructive pulmonary disease (COPD) frequently present with multiple concurrent chronic diseases, which has a profound impact on their quality of life. At present, there is a paucity of research investigating the interrelationships between COPD and comorbidities. Furthermore, there is a dearth of systematic and comprehensive studies in this area. Methods The data were extracted from the discharge summaries of patients whose primary diagnosis was COPD (ICD-10: J44). The 15 most frequent comorbidities in patients’ other diagnoses were identified, and the association rule mining (ARM) method with the apriori algorithm was then employed to derive comorbidity combinations associated with length of stay (LOS) and antimicrobial drug costs. Results The study encompassed data from 2,159 patients. The five most prevalent comorbidities were other respiratory diseases (41.69%), hypertension (31.91%), liver diseases (25.34%), heart diseases (20.84%), and arrhythmia (15.05%). Some comorbidity combinations identified by ARM were found to be significantly associated with longer LOS of at least seven days. Conversely, some were associated with higher antimicrobial drug costs. The combination of diabetes, heart disease, other respiratory disease, and hypertension demonstrated the strongest association with longer LOS (adjusted OR (aOR): The odds ratio was 3.03 (95% CI: 1.03–8.88). The combination of diabetes, other respiratory diseases and hypertension was associated with higher antimicrobial drug costs, amounting to a minimum of 400 RMB (aOR: 2.63, 95% CI: 1.31–5.31). Conclusion Other respiratory diseases and hypertension were among the most frequently reported comorbidities in patients with COPD in Guangzhou, China. It is possible that specific groups of comorbidities may contribute to a greater burden of healthcare resource utilization. Further investigation is required to elucidate the mechanisms underlying these associations and to identify potential measures to optimize the healthcare resource utilization.