Impact of multimorbidity patterns in hospital admissions: the case study of asthma

Background: Most previous studies assessing multimorbidity in asthma assessed the frequency of individual comorbid diseases. Objective: We aimed to assess the frequency and clinical and economic impact of co-occurring groups of comorbidities (comorbidity patterns using the Charlson Comorbidity Index) on asthma hospitalizations. Methods: We assessed the dataset containing a registration of all Portuguese hospitalizations between 2011-2015. We applied three different approaches (regression models, association rule mining, and decision trees) to assess both the frequency and impact of comorbidities patterns in the length-of-stay, in-hospital mortality and hospital charges. For each approach, separate analyses were performed for episodes with asthma as main and as secondary diagnosis. Separate analyses were performed by participants' age group. Results: We assessed 198340 hospitalizations in patients >18 years old. Both in hospitalizations with asthma as main or secondary diagnosis, combinations of diseases involving cancer, metastasis, cerebrovascular disease, hemiplegia/paraplegia, and liver disease displayed a relevant clinical and economic burden. In hospitalizations having asthma as a secondary diagnosis, we identified several comorbidity patterns involving asthma and associated with increased length-of-stay (average impact of 1.3 [95%CI=0.6-2.0]-3.2 [95%CI=1.8-4.6] additional days), in-hospital mortality (OR range=1.4 [95%CI=1.0-2.0]-7.9 [95%CI=2.6-23.5]) and hospital charges (average additional charges of 351.0 [95%CI=219.1-482.8] to 1470.8 [95%CI=1004.6-1937.0]) Euro compared with hospitalizations without any registered Charlson comorbidity). Consistent results were observed with association rules mining and decision tree approaches. Conclusions: Our findings highlight the importance not only of a complete assessment of patients with asthma, but also of considering the presence of asthma in patients admitted by other diseases, as it may have a relevant impact on clinical and health services outcomes.