Evidence map›Paper›PMID 32346522›Full record

ReviewAnnals of global health2020

Unblocking Barriers of Access to Hepatitis C Treatment in China: Lessons Learned from Tianjin.

Peiwen Zhang, Ran Guo, Jun Lian, Mengjia Zhi, Chengzhen Lu, Weishen Wu, Lihong Wang, Polin Chan, Zhongdan Chen, Jing Sun

Abstract readReview
In one paragraph

Review in Annals of global health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Peiwen ZhangSchool of Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College 5 Dongdansantiao, Beijing, CH.
Ran GuoSchool of Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College 5 Dongdansantiao, Beijing, CH.
Jun LianSchool of Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College 5 Dongdansantiao, Beijing, CH.
Mengjia ZhiSchool of Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College 5 Dongdansantiao, Beijing, CH.
Chengzhen LuDepartment of Chronic Hepatitis, Tianjin No 2 People's Hospital, Tianjin, CH.
Weishen WuDepartment of Communicable Diseases Control, Tianjin Center for Disease Control and Prevention, Tianjin, CH.
Lihong WangTianjin Healthcare Security Administration and Settlement Center, Tianjin, CH.
Polin ChanHIV, Hepatitis and STI Unit, Division of Communicable Diseases, World Health Organization Western Pacific Regional Office, Manila, PH.
Zhongdan ChenHepatitis/TB/HIV/STI, World Health Organization, Office of the WHO Representative in China, Beijing, CH.
Jing SunSchool of Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College 5 Dongdansantiao, Beijing, CH.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The high price is a critical barrier of access to new direct-anting-antiviral (DAA) therapies for hepatitis C for both the patients and the society. Many countries continue to face the challenge of financing such expensive medicines. Such examples include both high-income and middle-income countries. Existing evidence about the efforts of China to address this challenge is limited. To our knowledge, this is the first detailed description of a novel financing model and comprehensive analysis of its impact on patient financial burden of hepatitis C treatment in China. Objective: To examine the evolution of approaches to navigating patients' barriers of access to DAA-based treatment of hepatitis C in Tianjin City, China. Methods: Review of publicly available literature, including published and grey literature. Conduct on-site data extraction and key informant interview. The patient financial burden of hepatitis C treatment was analyzed. The financial burden of hepatitis C patients with different treatment models and health insurance financing models was measured by calculating the number of annual income to cover patient out-of-pocket (OOP) expenditure for the standard treatment course accordingly. Findings: Tianjin is the first area to pilot a capitated provider payment program for the treatment of hepatitis C. Through which, the retirees and employees spend 0.7 and 1.0 months of their salary, and residents spend 5.6-6.8 months of their salary for the treatment, the financial burden of patients were much relieved. By the end of March 2019, the first-year pilot program had 876 hepatitis C patients registered the new insurance coverage and treated in Tianjin. Conclusions: The study showed that the financial barriers of access to new hepatitis C treatment for patients could be unblocked with government commitment and novel financing models. International experiences demonstrated that centralized bulk procurement is a good leverage for price negotiation, primarily when using innovative payment approaches. To replicate the initial success of Tianjin, continued efforts are needed for stronger strategic price negotiation, preferably at central level. The case of Tianjin brings implications to the other areas of China and even other developing countries that government commitment, novel financing model and pooled procurement are critical elements of stronger purchasing power and a better secure of treatment.

Indexed as

Health ExpendituresAntiviral AgentsCapitation FeeChinaDrug CostsFee-for-Service PlansHealthcare FinancingHealth Services AccessibilityHepatitis C, ChronicInsurance, HealthPilot ProjectsAntiviral Agents

Identifiers

PMID32346522
PMCPMC7181951

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.