The Japan hospice and palliative evaluation study 4: a cross-sectional questionnaire survey

Abstract Background Constant evaluation is important for maintaining and improving the quality of end-of-life care. We therefore conduct the fourth Japan Hospice and Palliative Evaluation Study (J-HOPE4) as a continuous evaluation study. In this present paper, we describe the design of J-HOPE4. The main purposes of J-HOPE4 are as follows:1) to evaluate the processes, structures, and outcomes of palliative care acute hospitals, palliative care units, and home hospice services; 2) to examine bereaved family members’ self-reported psychosocial conditions, such as grief and depression as bereavement outcomes;3) to provide data to ensure and improve the quality of care provided by participating institutions via feedback based on the results from each institution; and 4) provide clinical and academic information concerning the implications of various issues in palliative care by conducting additional studies. Methods We will conduct a cross-sectional, anonymous, self-reported questionnaire survey. In total, 190 institutions will participate in this study, meaning that 12,000 bereaved family members will be sent a questionnaire. Discussion This is one of the largest cross-sectional surveys involving hospice and palliative care, both in Japan and worldwide. Because this study will have a large sample size, the findings are expected to be generalizable to other settings

Validation study on definition of cause of death in Japanese claims data.

Identifying the cause of death is important for the study of end-of-life patients using claims data in Japan. However, the validity of how cause of death is identified using claims data remains unknown. Therefore, this study aimed to verify the validity of the method used to identify the cause of death based on Japanese claims data. Our study population included patients who died at two institutions between January 1, 2018 and December 31, 2019. Claims data consisted of medical data and Diagnosis Procedure Combination (DPC) data, and five definitions developed from disease classification in each dataset were compared with death certificates. Nine causes of death, including cancer, were included in the study. The definition with the highest positive predictive values (PPVs) and sensitivities in this study was the combination of "main disease" in both medical and DPC data. For cancer, these definitions had PPVs and sensitivities of > 90%. For heart disease, these definitions had PPVs of > 50% and sensitivities of > 70%. For cerebrovascular disease, these definitions had PPVs of > 80% and sensitivities of> 70%. For other causes of death, PPVs and sensitivities were < 50% for most definitions. Based on these results, we recommend definitions with a combination of "main disease" in both medical and DPC data for cancer and cerebrovascular disease. However, a clear argument cannot be made for other causes of death because of the small sample size. Therefore, the results of this study can be used with confidence for cancer and cerebrovascular disease but should be used with caution for other causes of death

Validation study on definition of cause of death in Japanese claims data

Identifying the cause of death is important for the study of end-of-life patients using claims data in Japan. However, the validity of how cause of death is identified using claims data remains unknown. Therefore, this study aimed to verify the validity of the method used to identify the cause of death based on Japanese claims data. Our study population included patients who died at two institutions between January 1, 2018 and December 31, 2019. Claims data consisted of medical data and Diagnosis Procedure Combination (DPC) data, and five definitions developed from disease classification in each dataset were compared with death certificates. Nine causes of death, including cancer, were included in the study. The definition with the highest positive predictive values (PPVs) and sensitivities in this study was the combination of “main disease” in both medical and DPC data. For cancer, these definitions had PPVs and sensitivities of > 90%. For heart disease, these definitions had PPVs of > 50% and sensitivities of > 70%. For cerebrovascular disease, these definitions had PPVs of > 80% and sensitivities of> 70%. For other causes of death, PPVs and sensitivities were < 50% for most definitions. Based on these results, we recommend definitions with a combination of “main disease” in both medical and DPC data for cancer and cerebrovascular disease. However, a clear argument cannot be made for other causes of death because of the small sample size. Therefore, the results of this study can be used with confidence for cancer and cerebrovascular disease but should be used with caution for other causes of death