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Patients’ preferences for health insurance coverage of new technologies for treating chronic diseases in China: a discrete choice experiment
OBJECTIVES: Our study aimed to inform insurance decision-making in China by investigating patients’ preferences for insurance coverage of new technologies for treating chronic diseases. DESIGN: We identified six attributes of new medical technologies for treating chronic diseases and used Bayesian-e...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7513632/ https://www.ncbi.nlm.nih.gov/pubmed/32967882 http://dx.doi.org/10.1136/bmjopen-2020-038051 |
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author | Geng, Jinsong Chen, Xiaowei Bao, Haini Qian, Danmin Shao, Yuting Yu, Hao |
author_facet | Geng, Jinsong Chen, Xiaowei Bao, Haini Qian, Danmin Shao, Yuting Yu, Hao |
author_sort | Geng, Jinsong |
collection | PubMed |
description | OBJECTIVES: Our study aimed to inform insurance decision-making in China by investigating patients’ preferences for insurance coverage of new technologies for treating chronic diseases. DESIGN: We identified six attributes of new medical technologies for treating chronic diseases and used Bayesian-efficient design to generate choice sets for a discrete choice experiment (DCE). After conducting the DCE, we analysed the data by mixed logit regression to examine patient-reported preferences for each attribute. SETTING: The DCE was conducted with patients in six tertiary hospitals from four cities in Jiangsu province. PARTICIPANTS: Patients aged 18 years or older with a history of diabetes or hypertension and taking medications regularly for more than 1 year were recruited (n=408). RESULTS: The technology attributes regarding expected gains in health outcomes from the treatment, high likelihood of effective treatment and low incidence of serious adverse events were significant, positive predictors of choice by the study patients (p<0.01). The out-of-pocket cost was a significant, negative attribute for the entire study sample (β = −0.258, p<0.01) and for the patients with Urban-Rural Residents Basic Medical Insurance (URRBMI) (β = −0.511, p<0.01), but not for all the patients with Urban Employees Basic Medical Insurance (UEBMI) (β = −0.071, p>0.05). The severity of target disease was valued by patients with lower EQ-5D-5L index value as well as URRBMI enrollees. CONCLUSIONS: Patients highly valued the health benefits and risks of new technologies, which were closely linked to their feelings of disease and perceptions of health-related quality of life. However, there existed heterogeneity in preferences between URRBMI and UEBMI patients. Further efforts should be made to reduce the gap between insurance schemes and make safe and cost-effective new technologies as a priority for health insurance reimbursement. |
format | Online Article Text |
id | pubmed-7513632 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-75136322020-10-05 Patients’ preferences for health insurance coverage of new technologies for treating chronic diseases in China: a discrete choice experiment Geng, Jinsong Chen, Xiaowei Bao, Haini Qian, Danmin Shao, Yuting Yu, Hao BMJ Open Health Policy OBJECTIVES: Our study aimed to inform insurance decision-making in China by investigating patients’ preferences for insurance coverage of new technologies for treating chronic diseases. DESIGN: We identified six attributes of new medical technologies for treating chronic diseases and used Bayesian-efficient design to generate choice sets for a discrete choice experiment (DCE). After conducting the DCE, we analysed the data by mixed logit regression to examine patient-reported preferences for each attribute. SETTING: The DCE was conducted with patients in six tertiary hospitals from four cities in Jiangsu province. PARTICIPANTS: Patients aged 18 years or older with a history of diabetes or hypertension and taking medications regularly for more than 1 year were recruited (n=408). RESULTS: The technology attributes regarding expected gains in health outcomes from the treatment, high likelihood of effective treatment and low incidence of serious adverse events were significant, positive predictors of choice by the study patients (p<0.01). The out-of-pocket cost was a significant, negative attribute for the entire study sample (β = −0.258, p<0.01) and for the patients with Urban-Rural Residents Basic Medical Insurance (URRBMI) (β = −0.511, p<0.01), but not for all the patients with Urban Employees Basic Medical Insurance (UEBMI) (β = −0.071, p>0.05). The severity of target disease was valued by patients with lower EQ-5D-5L index value as well as URRBMI enrollees. CONCLUSIONS: Patients highly valued the health benefits and risks of new technologies, which were closely linked to their feelings of disease and perceptions of health-related quality of life. However, there existed heterogeneity in preferences between URRBMI and UEBMI patients. Further efforts should be made to reduce the gap between insurance schemes and make safe and cost-effective new technologies as a priority for health insurance reimbursement. BMJ Publishing Group 2020-09-23 /pmc/articles/PMC7513632/ /pubmed/32967882 http://dx.doi.org/10.1136/bmjopen-2020-038051 Text en © Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. http://creativecommons.org/licenses/by-nc/4.0/ http://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/. |
spellingShingle | Health Policy Geng, Jinsong Chen, Xiaowei Bao, Haini Qian, Danmin Shao, Yuting Yu, Hao Patients’ preferences for health insurance coverage of new technologies for treating chronic diseases in China: a discrete choice experiment |
title | Patients’ preferences for health insurance coverage of new technologies for treating chronic diseases in China: a discrete choice experiment |
title_full | Patients’ preferences for health insurance coverage of new technologies for treating chronic diseases in China: a discrete choice experiment |
title_fullStr | Patients’ preferences for health insurance coverage of new technologies for treating chronic diseases in China: a discrete choice experiment |
title_full_unstemmed | Patients’ preferences for health insurance coverage of new technologies for treating chronic diseases in China: a discrete choice experiment |
title_short | Patients’ preferences for health insurance coverage of new technologies for treating chronic diseases in China: a discrete choice experiment |
title_sort | patients’ preferences for health insurance coverage of new technologies for treating chronic diseases in china: a discrete choice experiment |
topic | Health Policy |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7513632/ https://www.ncbi.nlm.nih.gov/pubmed/32967882 http://dx.doi.org/10.1136/bmjopen-2020-038051 |
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