Management of Medico-Legal Risks in Digital Health Era: A Scoping Review

Artificial intelligence needs big data to develop reliable predictions. Therefore, storing and processing health data is essential for the new diagnostic and decisional technologies but, at the same time, represents a risk for privacy protection. This scoping review is aimed at underlying the medico-legal and ethical implications of the main artificial intelligence applications to healthcare, also focusing on the issues of the COVID-19 era. Starting from a summary of the United States (US) and European Union (EU) regulatory frameworks, the current medico-legal and ethical challenges are discussed in general terms before focusing on the specific issues regarding informed consent, medical malpractice/cognitive biases, automation and interconnectedness of medical devices, diagnostic algorithms and telemedicine. We aim at underlying that education of physicians on the management of this (new) kind of clinical risks can enhance compliance with regulations and avoid legal risks for the healthcare professionals and institutions.

How is risk different in family and non-family businesses? – a comparative statistical analysis during the COVID-19 pandemic

PurposeRisk is part of corporate activity and a consequence of the businesses' demands, the market and the changes in companies and their surroundings. The way that risk is managed is different between family and non-family businesses. The paper aims to compare the different risk types experienced in the context of the coronavirus disease (COVID-19) pandemic among family and non-family businesses and to analyze whether operational, legal, strategic and image risks influence financial risks.Design/methodology/approachThe nature of the study is quantitative and based on a questionnaire survey that analyses the perception of risks by 1,090 family businesses and 557 non-family businesses.FindingsThe results show the existence of statistically significant differences in the perception of financial and legal risks between family and non-family businesses, where the former being the businesses that give more importance to these risks. The perception of operational, legal, strategic and image risks have a positive influence on the perception of financial risk in family and non-family businesses.Originality/valueThe results obtained in the study are important because they allow an understanding about the differences in risk management between family and non-family businesses, which can lead to greater corporate sustainability and increased financial performance.

Changes in New Private Law of the Czech Republic and Implementation of Basel III

Competition in the financial market puts currently new requirements for cost reduction on financial institutions. Available sources of cost reduction are seen i.a. in minimizing legal risks, which can reduce the uncertainty associated with enforcement and interpretation of legal acts, treaties and regulations in the field of contractual obligations. In this regard, banks in the Czech Republic are looking for new ways to reduce costs in the ongoing implementation of Basel II and preparation for implementation of Basel III. The central problem to which attention is focused is to ensure the required level of capital adequacy. This is conditioned i.a. by their risk management system. Capital adequacy may affect credit risk substantially. Besides others, the level of credit risk may be affected to a considerable extent by application of hedging instruments. This paper presents conclusions of the executed comparison of the existing and new private law provisions in the Czech Republic and, based on that, draws new opportunities and difficulties for banks in managing their credit risk and capital adequacy. The focus is only on the hedging instruments that may affect the activities of banks in a significant way.

Federated Learning and Privacy

Centralized data collection can expose individuals to privacy risks and organizations to legal risks if data is not properly managed. Federated learning is a machine learning setting where multiple entities collaborate in solving a machine learning problem, under the coordination of a central server or service provider. Each client's raw data is stored locally and not exchanged or transferred; instead, focused updates intended for immediate aggregation are used to achieve the learning objective. This article provides a brief introduction to key concepts in federated learning and analytics with an emphasis on how privacy technologies may be combined in real-world systems and how their use charts a path toward societal benefit from aggregate statistics in new domains and with minimized risk to individuals and to the organizations who are custodians of the data.

Regulatory restrictions on the use of valproate in girls and women of childbearing potential: status update

In 2019, some restrictions for use of valproic acid in women with reproductive potential by regulatory authorities and the original drug manufacturer based on the results of studies in real clinical practice were introduced. During 2019–2021, there were a further clinical data accumulation and labeling changes. The review presents a critical analysis of the changes in prescribing information and product label. There is a long lead time from the moment when safety data become known to the moment when changes are made to the medicinal product label and patient brochures. Some of the changes, including the need for high doses of folic acid to prevent neural tube defects, are debatable. Repealing the provision for mandatory archiving of informed consent forms for valproic acid use in girls and women raises legal risks. Improvements in pregnancy prevention programs and further research on the safety of valproic acid in real-world clinical settings are needed.

A Brief Analysis of the Risk Control Issues of ChemChina’s Overseas M&A of Syngenta

In the past 20 years, overseas M&As have gradually become an important investment channel and have an important position in foreign investment. According to the background information of ChemChina’s overseas M&A of Syngenta, the specific circumstances of legal risks, financial risks and cultural risks in the process of ChemChina’s overseas M&A of Syngenta are the starting point for analysis to analyze the reasons for the formation of specific risk factors in this case, summarizing the risk prevention and control measures of Chinese enterprises’ overseas M&A from both macro and micro perspectives.

Legal Risks and Coping Strategies of Block Chain Managing Trade Secrets: Enlightenment of Chinese Experience

The management and legal protection of trade secrets is the common goal for all countres. Block Chain was found a huge advantage in protecting trade secrets as an advanced form of mathematical application. To better protect trade secrets for solutions, this study was to find out the legal risks faced with Block Chain. Basic theories of trade secrets and Block Chain were analyzed after reviewed literatures and empirical. The contemporary risks faced were put forward combined in practice. The better ways to protect trade secrets were discussed based on the current judicial practice of China. It was argued that problems of electronic storage and evidence collection of trade secrets would be solved Block Chain protection of trade secrets. Great risks and challenges would be confronted ahead albeit confirmed by the judiciary. It was concluded that a long time was dispensable for Block Chain managing and protecting trade secrets.

Legal risks of using artificial intelligence in personnel management

The article discusses the possibilities of using artificial intelligence in personnel management (interviewing job seekers, monitoring employee performance and control). Particular attention is paid to the issues of observance of workers' rights. It is concluded that, in some cases, the use of opaque algorithms of artificial intelligence may violate the prohibition of discrimination in the labor sphere provided for by Russian legislation. Changes to the current legislation are proposed.