Candidate for the Lee B. Lusted Student Prize Competition
Chronic diseases often occur in combination, their interaction effects possibly leading to a non-linearity in healthcare costs that is often ignored in economic evaluations. This paper aims to quantify the comparative effect of single and multiple chronic diseases on hospital resource use.
Method:
Using records of all admissions to public hospitals in the state of Victoria, Australia in 2010-2011 we estimate multiple regression models of hospital length of stay (and total annual discharges) for combinations of 11 chronic diseases. For length of stay we run separate models for patients with a 1 day stay and those with multiple day stays and adjust for observed and unobserved characteristics of patients.
Result:
Having a higher chronic disease count decreases the odds of having a same-day hospitalization (day case) exponentially while some disease combinations increased these odds. Having ischemic heart disease (IHD) & dementia doubled the odds of a day case compared to a patient with dementia only. Among overnight stays, having a mental disease had the highest single disease effect on length of stay (LOS) – increasing LOS by 3-4 days. Some diseases when combined had non-additive effects (i.e. their combined effect was greater or less than the sum of their single disease effects) on LOS while others were additive. The interaction effect in a depression-renal failure combination added 3 more days to the sum of its single disease effects, while in cancer-osteoporosis it was -2 days. We observed that disease combinations that produced a positive interaction effect were usually unrelated diseases. The number of chronic diseases an individual had was found to be positively correlated with their number of admissions. Among single diseases, cancer had the highest effect on admissions – increasing admissions by 5. Having a combination of diseases was generally found to have a less-than-additive effect on the number of admissions.
Conclusion:
Patients with chronic diseases have a resource use pattern that includes longer lengths of stays and more admissions. Combinations of unrelated diseases are particularly correlated with longer lengths of stay therefore it is the disease and combination type that is associated with higher lengths of stay and admitted episodes. Economic evaluations which assume additivity when estimating joint-disease costs could either overestimate or underestimate costs depending on the type of disease combination.