The Impact of Hospice Care on Survival and Healthcare Costs for Patients with Lung Cancer: A National Longitudinal Population-Based Study in Taiwan

BACKGROUND: The healthcare costs of cancer care are highest in the last month of life. The effect of hospice care on end-of-life (EOL) healthcare costs is not clearly understood. PURPOSE: The purpose of this study was to evaluate the effect of hospice care on survival and healthcare costs for lung cancer patients in their final month of life. METHODS: We adopted Taiwan’s National Health Insurance Research Claims Database to analyze data for 3399 adult lung cancer patients who died in 1997–2011. A logistic regression analysis was performed to determine the predictors of high healthcare cost, defined as costs falling above the 90th percentile. Patients who received hospice cares were assigned to a hospice (H) group and those who did not were assigned to a non-hospice (non-H) group. RESULTS: The patients in the H group had a longer mean (median) survival time than those in the non-H group did (1.40 ± 1.61 y (0.86) vs. 1.10 ± 1.47 (0.61), p<0.001). The non-H group had a lower mean healthcare cost than the H group (US $1,821 ± 2,441 vs. US $1,839 ± 1,638, p<0.001). And, there were a total of 340 patients (10%) with the healthcare costs exceeding the 90th percentile (US $4,721) as the cutoff value of high cost. The non-H group had a higher risk of high cost than the H group because many more cases in the non-H group had lower costs. Moreover, the risk of high health care costs were predicted for patients who did not receive hospice care (odds ratio [OR]: 3.68, 95% confidence interval [CI]: 2.44–5.79), received chemotherapy (OR: 1.51, 95% CI: 1.18–1.96) and intubation (OR: 2.63, 95% CI: 1.64–4.16), and those who had more emergency department visits (OR: 1.78, 95% CI: 1.24–2.52), longer hospital admission in days (OR: 1.08, 95% CI: 1.07–1.09), and received radiotherapy (OR: 1.33, 95% CI: 1.00–1.78). Lower risks of high health care costs were observed in patients with low socioeconomic status (OR: 0.58, 95% CI: 0.40–0.83), or previous employment (OR: 0.66, 95% CI: 0.47–0.92). After propensity-score matching, the patients of the non-H group had a higher mean cost and a higher risk of high cost. Similar results were obtained from logistic regression analysis in propensity score-matched patients. CONCLUSIONS: The survival of the hospice group was longer than non-H group, and patients in the non-H group were 3.74 times more likely to have high healthcare costs at EOL. The positive predictors for high health care costs were patients who did not receive hospice care, who received chemotherapy and intubation, who had more emergency department visits and longer hospital admission, and who received radiotherapy. Negative predictors were patients who had a low socioeconomic status or previous employment. The issue of how to reduce the high health care costs for patients with lung cancer in the last month of life is a challenge for policy makers and health care providers.