ArticleHealth economics review2019
Risk selection into supplemental private health insurance in China.
Article in Health economics review, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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.
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.
Who cites it
5 citing papers in PubMed.
- Adverse Selection as a Barrier to Achieving Universal Public Health Insurance Coverage in China.Risk management and healthcare policy · 2025Article
- The Role of Supplementary Insurance in Achieving Universal Health Coverage: A Comprehensive Review.Medical journal of the Islamic Republic of Iran · 2024Review
- Does supplemental private health insurance incentivize household risky financial asset investment? Evidence from the China Household Financial Survey.International journal of health economics and management · 2022Article
- Preferences for private health insurance in China: A discrete choice experiment.Frontiers in public health · 2022Article
- What Are the Determinants of the Decision to Purchase Private Health Insurance in China?International journal of environmental research and public health · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundInformation on risk selection is important for the regulation and development of supplemental private health insurance (PHI). The research on risk selection into supplemental PHI has been documented in several developed countries where the regulation of the PHI markets was relatively mature. However, evidence on this important aspect of the supplemental PHI market in China is still absent in the literature. The private insurers in China were not prohibited from discrimination against pre-existing conditions and did not guarantee ongoing enrolment. Therefore, the direction and degree of risk selection could not be inferred using the evidence from the other countries. To provide evidence on risk selection into supplemental PHI in China, we conducted a cross-sectional analysis using data from the 2015 wave of China Health and Retirement Longitudinal Study (CHARLS).
resultsUsing probit models, we found that individuals having better self-reported general health were more likely to enrol in PHI in China, suggesting advantageous selection. This result was confirmed by an alternative analysis using an instrumental variable. We also adjusted the realized occurrence of hospitalization by excluding potential moral hazard effect and showed that the adjusted hospitalization risk was negatively associated with PHI enrolment, which also indicated advantageous selection.
conclusionsThe findings suggested potential over-insurance of healthier individuals or under-insurance of less healthy individuals. The regulation of the PHI market in China should aim to address the inefficiency. The current study could also contribute to the information base for policymakers in countries where the PHI markets similarly lack strong regulation.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.