Comparative Impact Analysis of Low-Deductible Insurance Versus In-house Hospital Assumption of Risk and Management on Medical Malpractice Claims.

Objectives: Claims management is critical to ensure the safe and high-quality medical care for which liability insurers and/or hospitals are responsible. The aim of this research is to determine whether increasing hospital malpractice risk exposure, with increasing deductibles, has an impact on malpractice claims and payouts.

Methods: The study was conducted at a single tertiary hospital, the Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy.

Potentiality of algorithms and artificial intelligence adoption to improve medication management in primary care: a systematic review.

Objectives: The aim of this study is to investigate the effect of artificial intelligence (AI) and/or algorithms on drug management in primary care settings comparing AI and/or algorithms with standard clinical practice. Second, we evaluated what is the most frequently reported type of medication error and the most used AI machine type.

Methods: A systematic review of literature was conducted querying PubMed, Cochrane and ISI Web of Science until November 2021.

Assessing the potentiality of algorithms and artificial intelligence adoption to disrupt patient primary care with a safer and faster medication management: a systematic review protocol.

Introduction: In primary care, almost 75% of outpatient visits by family doctors and general practitioners involve continuation or initiation of drug therapy. Due to the enormous amount of drugs used by outpatients in unmonitored situations, the potential risk of adverse events due to an error in the use or prescription of drugs is much higher than in a hospital setting. Artificial intelligence (AI) application can help healthcare professionals to take charge of patient safety by improving error detection, patient stratification and drug management.

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.

Liability of Health Care Professionals and Institutions During COVID-19 Pandemic in Italy: Symposium Proceedings and Position Statement.

Background: On May 12, 2020, a symposium titled "Liability of healthcare professionals and institutions during COVID-19 pandemic" was held in Italy with the participation of national experts in malpractice law, hospital management, legal medicine, and clinical risk management. The symposium's rationale was the highly likely inflation of criminal and civil proceedings concerning alleged errors committed by health care professionals and decision makers during the COVID-19 pandemic. Its aim was to identify and discuss the main issues of legal and medicolegal interest and thus to find solid solutions in the spirit of preparedness planning.