In the News: Supreme Court Judicial Interpretation, Medical Disputes and Statistical Fraud Prevention

September 18, 2018 | BY

Jacelyn Johnson

The Supreme People's Court just issued new judicial interpretation guidelines incorporating core socialist values; New laws regulating medical disputes prevention and treatment; and China seeks to improve the authenticity of its statistical data to support better policy-making.

SPC to Issue Judicial Interpretation Guidelines Incorporating Core Socialist Values

The Supreme People's Court (SPC), on Tuesday released a 2018-2023 plan to incorporate the country's core socialist values in handling judicial interpretation.

The core socialist values can be summarized as prosperity, democracy, civility, harmony, freedom, equality, justice, the rule of law, patriotism, dedication, integrity and friendliness. When issued, the new guidelines on specific legal issues will be binding across all levels of courts in China.

The top court is working on the new guidelines on judicial interpretation, and they have yet to disclose when the interpretation will be released to the public.

“The interpretation will define justifiable self-defense and protect the rights of good Samaritans, as well as encourage people to help each other and promote friendliness,” said the SPC in a statement. “The new guidelines will clarify when self-defense should be considered excessive and what penalties offenders should face.”

The court said the plan would also highlight the importance of protecting personal information, intellectual property and environmental issues through judicial interpretations.

China Issues New Regulations to Safeguard Rule of Law in Medical Disputes

The Chinese government recently issued 'The Medical Disputes Prevention and Treatment Regulation' which will be implemented on October 1.

The regulation is aimed at safeguarding the legitimate interests of medical staff and patients, maintaining medical order and ensuring medical safety. The regulation stipulates that diagnosis and treatment should be centered on patients, and health professionals should abide by strict professional ethics.

The regulations clearly define risk prevention and control of medical disputes, identifies ways to resolve medical disputes, regulates identification activities prior to litigation, and strengthens the management of medical quality and safety.

The regulation advocates mutual respect in medical treatment and implements the rule of law in safeguarding rights, fairness, justice and promptness in dealing with medical disputes.

Both doctors and patients can pursue various forms of discourse in the event of a dispute, including voluntary negotiation, mediation, asking for administrative conciliation, and filing a lawsuit with the people's court, among other approaches regulated by the law.

Local health administrative departments have been told to enhance management in tackling medical disputes, and include it in the governance system of public security. This comes in line with China's aim at reforming the medical and health system to promote a health China.

China Tightens Regulations to Improve Authenticity of Statistical Data

The State Council and the general offices of the CPC Central Committee, on September 16, disclosed a 20-clause regulation focusing on preventing and cracking down on statistical fraud and related illegal operations.

The new inspection regulation is aimed at improving the accuracy of statistical data and the authenticity of economic data to better support policy-making.

The National Bureau of Statistics has established a department for statistical law enforcement and supervision, and will be responsible for organizing and conducting statistical inspections, building a mechanism to prevent and penalize fraud and making sure violators are held accountable.

According to a report by the State Council, the National Bureau of Statistics uncovered 72 key cases of statistical fraud between January 2017 and April this year. Last year, 7,479 cases of statistical fraud were investigated by local statistical authorities.

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