Analysis of Palliative Care Utilization and Medical Expenses among Patients with Chronic Diseases in Taiwan: A Population-Based Cohort Study.
Hui-Mei LinYen-Chun HuangChieh-Wen HoMing-Chih ChenPublished in: International journal of environmental research and public health (2022)
Palliative care (PC) is an important alternative treatment for patients with chronic diseases, particularly for those in the later stages of disease progression. This is because these diseases are often irreversible, with progressive worsening of symptoms. By encouraging the use of tranquility resources for good death and spiritual relief, PC can reduce the physical and psychological burden on patients at the end of their lives. Currently, most discussions on PC have focused on patients with cancers, and few have further discussed the differences in medical expenses between PC and emergency treatment in patients with chronic diseases at the end of their lives. This study analyzed the top three chronic diseases in patients who used PC resources in the past decade and identified the impact of emergency treatment on mean survival time and medical expenses based on the medical records from the National Health Insurance Research Database. In total, 4061 patients with chronic diseases who were admitted to hospice wards were included in this study; of them, 85 patients still received emergency treatment, including urinary catheterization, nasogastric intubation, and respirator use, at the end of their lives. The mean survival time of patients aged 50-64 years who received emergency treatment was longer than that of the same age group who did not receive emergency treatment. Different comparisons of the mean survival time and medical expenses using real-world data provides important insights regarding PC management that may assist in establishing health policies in the future.
Keyphrases
- healthcare
- public health
- palliative care
- emergency department
- health insurance
- end stage renal disease
- mental health
- newly diagnosed
- peritoneal dialysis
- physical activity
- machine learning
- deep learning
- climate change
- artificial intelligence
- risk factors
- social media
- emergency medical
- data analysis
- affordable care act