The Role of Courts in Shaping Health Equity

Enforcing the right to health in private health systems through Judicialization what can we learn from the scoping review of the cross-national perspective?

BACKGROUND

Private sector acting in healthcare does not remove the public nature of a health system, nor mitigate the right to health as a human right.

METHODS

This scoping review aims to answer the question: what factors influence the pattern of lawsuits seeking to enforce the right to health in private healthcare systems? The search was carried out in Pubmed, SciELO, DOAJ and Scopus.

RESULTS

Out of 464 articles found, after inclusion and exclusion criteria, 30 articles were included. The survey covered 36 different countries and four main factors were identified. The socioeconomic context, the health system model, the incorporation of the right to health in legislation, and the model of regulation of private health.

CONCLUSIONS

Understanding these patterns help understanding the difficulties of implementing and guaranteeing universal health. Health systems must be based on responsibility, solidarity, equity, and distributive justice, since the sum of these values generates mutualism. Judicial decision-making regarding to health access must be reasoned on equity and distributive justice, scientific evidence and ethical factors. Even private health systems must be funded in a well-defined ethical platform and social moral valuation.

Ensuring trustworthy use of artificial intelligence and big data analytics in health insurance

Technological advances in big data (large amounts of highly varied data from many different sources that may be processed rapidly), data sciences and artificial intelligence can improve health-system functions and promote personalized care and public good. However, these technologies will not replace the fundamental components of the health system, such as ethical leadership and governance, or avoid the need for a robust ethical and regulatory environment. In this paper, we discuss what a robust ethical and regulatory environment might look like for big data analytics in health insurance, and describe examples of safeguards and participatory mechanisms that should be established. First, a clear and effective data governance framework is critical. Legal standards need to be enacted and insurers should be encouraged and given incentives to adopt a human-centred approach in the design and use of big data analytics and artificial intelligence. Second, a clear and accountable process is necessary to explain what information can be used and how it can be used. Third, people whose data may be used should be empowered through their active involvement in determining how their personal data may be managed and governed. Fourth, insurers and governance bodies, including regulators and policy-makers, need to work together to ensure that the big data analytics based on artificial intelligence that are developed are transparent and accurate. Unless an enabling ethical environment is in place, the use of such analytics will likely contribute to the proliferation of unconnected data systems, worsen existing inequalities, and erode trustworthiness and trust.