Chinese Healthcare Corruption Criminal Judgments from 2019 to 2025

Zhiling Shen's dataset on figshare contains 573 criminal judgments from China Judgments Online, involving 787 defendants, dated from September 2019 to December 2025. The data was collected in January 2026 and provides a reproducible sample of judicially visible healthcare corruption in China. The study identifies typologies, risk nodes, and institutional mechanisms underlying the cases.

Use Cases

• Analyze corruption typology distribution based on the three main categories mentioned: pharmaceutical/clinical commercial bribery, embezzlement, and medical insurance fraud.
• Study sentencing patterns based on metrics like median principal penalty, probation rates, and fines.
• Identify high-risk governance nodes based on the concentration of cases in procurement, medical insurance auditing, and in-hospital finance.
• Examine actor structures and institutional mechanisms described in the embedded multiple-case analysis.

Strengths

• Contains 573 criminal judgments involving 787 defendants, providing a substantive sample.
• Covers a defined time range from September 2019 to December 2025.
• Includes detailed quantitative results, such as median principal penalty of 36 months and fine imposition rate of 91.70%.
• Uses a mixed-methods design combining descriptive analysis with embedded case studies.

Limitations

• Row count and column-level documentation are unknown; field semantics must be inferred after download.
• The 182.6 KB file size suggests a limited scope, likely containing summary analysis rather than raw case data.
• Data may reflect bias inherent to judicially visible cases, which the author notes are legally filtered governance evidence.

Provenance

Source

China Judgments Online, retrieved by author Zhiling Shen.

Collection Method

Criminal judgments were retrieved and screened in January 2026, using structured coding and embedded multiple-case analysis.

Time Range

2019-09-01 to 2025-12-31

Freshness

Last updated 2026-05-18 05:43:17.

Geography

China