The clinical laboratories are constantly exposed to changes that may be caused by several factors, whether economic or not. Today clinical laboratories face several challenges, such as the pressure to reducing costs and improving service quality while facing the need of attaining ever higher levels of automation and technical quality. Being aware of such challenges and reacting to them in sufficient timing so as to assure their business survival is the main challenge of laboratories' managers, who are better prepared technically than managerially. The urgent need for a new strategy in this aerea is a reality This study aims to survey the factors that were responsible for the change in performance in Brazilian laboratories. We raised three important factors defined by type of portfolio, automation with LIS system and outsourcing, which were presented by 15 non-financial indicators. We developed a structural equation model with which we assessed the significance and magnitude of each of these factors on laboratory performance. We found that only one of such factors showed significance, which was the automation with LIS system. Thus, our research shows that this factor is the main agent of change in performance in clinical laboratories in Brazil.

This article will examine the issue of civil liability for damage caused by systems equipped with Artificial Intelligence (AI) used in medical practice, specifically robots. Taking as its starting point the idea that these autonomous entities, unlike human beings, are devoid of emotions and states of fatigue that might compromise their performance, their decisions depend solely on algorithms operating on the basis of machine learning methods, the occurrence of damage and the possible triggering of civil liability under its traditional categories based on fault and risk may prove insufficient to address that damage and identify the party responsible. To analyse this issue, we shall first briefly examine the use of mechanisms equipped with Artificial Intelligence in medical contexts and the potential triggering of civil liability for damage caused by them, before proceeding, with the necessary critical reflection, to ascertain who is liable for such damage with a view to the necessary attribution of liability for its compensation.