Comorbidity constructs for patients with congestive heart failure and their effect on hospital outcomes of care.

We present a study of the cumulative effect of comorbidities on hospital length of stay (LOS), and hospital mortality, for patients with Congestive Heart Failure (CHF). This condition can be life-threatening, while a burdened disease profile significantly increases the risk for negative outcomes. Our hypothesis is that coexisting conditions often co-interact, in various ways, and these interactions can have a variable effect on outcomes; clinical decision makers should, therefore, be able to recognize these joint effects. In order to study the CHF comorbidities, we used medical claims data from CMS. Firstly, we conducted cluster analysis to find the common hospital comorbidities for CHF admissions. We then extracted the most frequent cluster: {metabolism disorders, anemia, hypertension with complications, coronary atherosclerosis, chronic kidney disease} and calculated conditional probabilities in a modular manner for all combinations within this cluster. We furthermore estimated the cumulative effect of these comorbidity combinations on the two outcomes under study in a step by step, modular manner. Results were visualized with directed acyclic graphs.