Cost impact of Palliative Care – how do cost types change after a Palliative Care intervention
M. Hagemann1, S. Zambrano1, S. Eychmüller1 (1Bern)
A considerable number of studies demonstrate that Palliative Care (PC) programs improve quality of care at the end of life compared to disease modifying treatment alone. However, there is a lack of data with respect to the economic impact of routinely integrating PC in end of life hospital care.
The objective of this analysis was to identify individual cost drivers of PC and to quantify their effects on hospital costs.
We performed a retrospective analysis examining cost and medical data from the last hospitalization of patients who died at a Swiss University hospital. Data originate from seven different databases including information about administrative and patient data, inhospital movement, used rendered services and items, costs per patient including medication data from regular, emergency, and ICU wards. Based on these, we constructed a cost matrix that allowed us to break all incurred costs into different cost types such as pharmacy, laboratory, staff, catering, patient management and room costs. We then compared the costs of a patient’s pre and post PC intervention hospital stay as well as investigated the role of the timing of PC interventions. P-values were calculated using the bias-corrected point estimate and the bootstrap standard errors with a normal approximation.
The analysis revealed that overall total hospital costs as well as costs per day increase after a patient receives a PC intervention. Whereas specific cost types such as catering, room and patient management costs (patient related costs) increase significantly after a PC intervention, other cost types such as laboratory, material and pharmacy (diagnostic related) decrease.
The results regarding the timing of PC intervention revealed that all cost types have lower costs when a PC patient receives a PC intervention during the first three days after hospital admission (“early PC patients”) compared to a “late PC patient” that receives a PC intervention after three days of hospital stay.
This analysis provides empirical evidence supporting decision-makers and management accountants of the cost avoidance potential of PC interventions from different cost perspectives. The results contribute to the literature comprehensive information on hospital cost drivers. PC does not reduce costs per se: diagnostic related cost types can be decreased, but this effect will be counteracted by the increase of patient related costs mainly due to the limited possibilities to discharge severely ill patients.