M. Delisle1, R. Helewa1, J. Park1, D. Hochman1, A. McKay1 1University of Manitoba,Surgery,Winnipeg, MB, Canada
Introduction:
End of life healthcare for oncology patients has been criticized for being inappropriate and overly aggressive resulting in low value care and inefficient use of limited resources. Strategies exist to improve patient comfort in this critical moment of life and reduce unnecessary expenditures. The objective of this study was to identify factors associated with increased end of life costs in colorectal cancer patients to guide future quality improvement.
Methods:
This is a retrospective cohort study including patients dying of colorectal cancer in a single Canadian province between 2004 to 2012 (ICD-10-CM C18-C21). Data was obtained from a single-payer, provincial administrative claims database and a comprehensive provincial cancer registry. Inpatient hospital costs were calculated using the Canadian Institute for Health Information’s (CIHI) Resource Intensity Weights multiplied by CIHI’s average Cost per Weighted Case in 2014 Canadian dollars. Outpatient costs was the total billed to the provincial government in the last 30 days of life adjusted to 2014 Canadian dollars using Statistics Canada’s Consumer Price Index. Patients with no costs over the last six months of life were excluded to account for loss to follow-up (n=21).
The primary outcome was end of life costs, defined as total inpatient and outpatient costs accrued 30-days before death. Risk adjusted 30-day end of life costs were estimated using a negative binomial regression with the log link function, robust standard errors and an offset variable to account for patients that did not survive 30 days from diagnosis. Covariates included age, sex, cancer stage, socioeconomic status, cancer location (rectal, rectosigmoid, colon), Charlson Co-Morbidity Index, year of diagnosis and death in hospital. Multivariable Logistic regression was used to assess for baseline predictors associated with in hospital death.
Results:
A total of 1,622 patients died of colorectal cancer between 2004 and 2012 (Table 1). The largest variations in cost existed between patients who died in hospital versus those that did not. The median length of stay for patients dying in hospital was 26 days (IQR 13-41). Significant predictors associated with in hospital death included co-morbidities (OR 1.30, 95% CI 1.16-1.45, p<0.01) and more recent diagnosis (OR 1.10, 95% CI 1.02-1.17, p=0.01).
Conclusion:
In hospital deaths are associated with significantly increased end of life costs and the odds of dying in hospital appear to be increasing in this population. This study could not assess if in hospital deaths were also associated with increased patient benefits. Future studies should aim to identify cost effective strategies to optimize end of life care.