Dataset Information

End-of-life cost and its determinants for cancer patients in urban China: a population-based retrospective study.

ABSTRACT:

Objective

This study aimed to define the end-of-life (EOL) healthcare utilisation and its cost and determinants for cancer patients and to proactively inform related strategies in mainland China.

Design

A population-based retrospective study.

Setting and participants

Data from 894 cancer patients were collected in urban Yichang, China from 01 July 2015 to 30 June 2017.

Outcome measures

Emergency department (ED) visits, outpatient and inpatient hospitalisation services, intensive care unit (ICU) admission and total costs were used as the main outcomes.

Results

In this study, 66.8% of the 894 patients were male, and the average age was 60.4 years. Among these patients, 37.6% died at home, and patients had an average of 4.86 outpatient services, 2.23 inpatient hospitalisation services and 1.44 ED visits. Additionally, 5.9% of these patients visited the ICU at least once. During the EOL periods, the costs in the last 6 months, 3 months, 1?month and 1?week were US$18 234, US$13 043, US$6349 and US$2085, respectively. The cost increased dramatically as death approached. The estimation results of generalised linear regression models showed that aggressive care substantially affected expenditure. Patients with Urban Employee Basic Medical Insurance spent more than those with Urban Resident-based Basic Medical Insurance or the New Rural Cooperative Medical Scheme. The place of death and the survival time are also risk factors for increased EOL cost.

Conclusion

The findings suggested that the EOL cost for cancer patients is associated with aggressive care, insurance type and survival time. Timing palliative care is urgently needed to address ineffective and irrational healthcare utilisation and to reduce costs.

Ethics and dissemination

This study was approved by the Ethics Committee of the Tongji Medical College, Huazhong University of Science and Technology (IORG No.: IORG0003571). All the data used in this study were de-identified.

SUBMITTER: Li Z

PROVIDER: S-EPMC6528019 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

End-of-life cost and its determinants for cancer patients in urban China: a population-based retrospective study.

Li Zhong Z Pan Zijing Z Zhang Liang L He Ruibo R Jiang Shan S Xu Chengzhong C Lu Fangfang F Zhang Pei P Li Boyang B

BMJ open 20190320 3

<h4>Objective</h4>This study aimed to define the end-of-life (EOL) healthcare utilisation and its cost and determinants for cancer patients and to proactively inform related strategies in mainland China.<h4>Design</h4>A population-based retrospective study.<h4>Setting and participants</h4>Data from 894 cancer patients were collected in urban Yichang, China from 01 July 2015 to 30 June 2017.<h4>Outcome measures</h4>Emergency department (ED) visits, outpatient and inpatient hospitalisation service ...[more]

PMID: 30898830

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Project description:OBJECTIVE:The lack of coordinated and appropriate healthcare across sectors has produced more patients for county hospitals in China. This study examined differences in patient choice between township and county hospitals for readmission after a first township hospitalisation, and the determinants that influenced this choice. DESIGN:A retrospective study of readmissions across hospitals after a first admission in township hospital. A township-township (TT) inpatient group and a township-county (TC) inpatient group were compared. A two-level logistic regression model was used to examine the determinants of choice for hospital readmission. SETTING:Data were drawn from a population-based health utilisation database for Qianjiang District, China, from 1 January 2008 to 31 December 2013. PARTICIPANTS:This study focused on readmitted patients whose first admission was in a township hospital. Readmission cases were identified as the same diagnosis (International Classification of Diseases, Tenth Revision) in a subsequent hospitalisation within 30 days. In total, 6764 readmissions had first admissions in township hospitals. PRIMARY OUTCOME MEASURES:Patient choice for hospital readmission after a first township hospitalisation. RESULTS:The TT group accounted for 62.5% (4225) and the TC group for 37.5% (2539) of readmissions in 6 years, and the proportion of TC readmissions in total inpatients increased from 1.66% to 1.89%. Readmission rates varied among towns (p<0.001). Differences between the TC and TT groups included: length of stay (LOS) of first admission (6.96 days vs 9.23 days), average interval between admissions (6.03 days vs 14.95 days) and disease category. Admission year, age, travel time to county hospital, interval between admissions, first admission LOS and disease category were determinants of choice for hospital readmission. CONCLUSIONS:Patients whose first admission was in a township hospital were more likely to be readmitted to a county hospital. A combination of first LOS and interval between admissions may be an effective identification index for TC readmission. TRIAL REGISTRATION NUMBER:ChiCTR-OOR-14005563.

Project description:BackgroundSocial determinants of health (SDOH) produce a broad range of life expectancy (LE) disparities. In China, limited literatures were found to report association between SDOH and LE at ecological level during a consecutive period of time from the spatial perspectives. This study aimed to determine the existence, quantify the magnitude, and interpret the association between SDOH and LE in China.MethodsProvincial-level LE were estimated from mortality records during 2005-2020 from National Mortality Surveillance System in China. A spatial panel Durbin model was used to investigate LE associated SDOH proxies. Spatial spillover effects were introduced to interpret direct and indirect effects caused by SDOH during long-term and short-term period on LE disparities.FindingsNationwide, LE increased from 73.1 (95% confidence interval (CI): 71.3, 74.4) years to 77.7 (95%CI: 76.5, 78.7) years from 2005 to 2020. Unequally spatial distribution of LE with High-High clustering in coastal areas and Low-Low clustering in western regions were observed. Locally, it was estimated that SDOH proxies statistically significant related to an increase of LE, including GDP (coefficient: 0.02, 95%CI: 0.00, 0.03), Gini index (coefficient: 2.35, 95%CI: 1.82, 2.88), number of beds in health care institutions (coefficient: 0.02, 95%CI: 0.00, 0.05) and natural growth rate of resident population (coefficient: 0.02, 95%CI: 0.01, 0.02). Direct and indirect effects decomposition during long-term and short-term of LE associated SDOH proxies demonstrated that GDP, urbanization rate, unemployment rate, education attainment, Gini index, number of beds in health care institutions, sex ratio, gross dependence ratio and natural growth rate of resident population not only affected local LE, but also exerted spatial spillover effects towards geographical neighbors.InterpretationSpatial variations of LE existed at provincial-level in China. SDOH regarding socioeconomic development and equity, healthcare resources, as well as population characteristics not only affected LE disparities at local scale but also among nearby provinces. Externalities of policy of those SDOH proxies should be took into consideration to promote health equity nationally. Comprehensive approaches on the basis of population strategy should be consolidated to optimize supportive socioeconomic environment and narrow the regional gap to reduce health disparities and increase LE.FundingNational Key Research & Development Program of China (Grant No.2018YFC1315301); Ministry of Education of China Humanities and Social Science General Program (Grant No.18YJC790138).

Dataset Information

End-of-life cost and its determinants for cancer patients in urban China: a population-based retrospective study.

Objective

Design

Setting and participants

Outcome measures

Results

Conclusion

Ethics and dissemination

Publications

End-of-life cost and its determinants for cancer patients in urban China: a population-based retrospective study.

Similar Datasets

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