What is a Good Death? A Choice Experiment on Care Indicators for Patients at End of Life.

Journal Article (Journal Article)

CONTEXT: Health systems should aim to deliver on what matters most to patients. With respect to end of life (EOL) care, knowledge on patient preferences for care is currently lacking. OBJECTIVES: To quantify preference weights for key EOL care indicators. METHODS: We developed a discrete choice experiment survey with 13 key indicators related to patients' experience in the last six weeks of life. We fielded the survey to a web-panel of caregiver proxies for recently deceased care recipients. We obtained 250 responses in each of five countries: India, Singapore, Kenya, the UK and the US. Latent-class analysis was used to evaluate preference weights for each indicator within and across countries. RESULTS: A 2-class latent-class model was the best fit. Class 1 (average class probability = 64.7%) preference weights were logically ordered and highly significant, while Class 2 estimates were generally disordered, suggesting poor data quality. Class 1 results indicated health care providers' ability to control patients' pain to desired levels was most important (11.5%, 95% CI: 10.3%-12.6%), followed by clean, safe, and comfortable facilities (10.0%, 95% CI: 9.0%-11.0%); and kind and sympathetic health care providers (9.8%, 95% CI: 8.8%-10.9%). Providers' support for nonmedical concerns had the lowest preference weight (4.4%, 95% CI: 3.6%-5.3%). Differences in preference weights across countries were not statistically significant. CONCLUSION: Results reveal that not all aspects of EOL care are equally valued. Not accounting for these differences would lead to inappropriate conclusions on how best to improve EOL care.

Full Text

Duke Authors

Cited Authors

  • Sepulveda, JMG; Baid, D; Johnson, FR; Finkelstein, EA

Published Date

  • April 2022

Published In

Volume / Issue

  • 63 / 4

Start / End Page

  • 457 - 467

PubMed ID

  • 34793947

Pubmed Central ID

  • PMC9341237

Electronic International Standard Serial Number (EISSN)

  • 1873-6513

Digital Object Identifier (DOI)

  • 10.1016/j.jpainsymman.2021.11.005


  • eng

Conference Location

  • United States