Fulfilling the Promise of Artificial Intelligence in the Health Sector: Let's Get Real.

Objectives: This study aimed to showcase the potential and key concerns and risks of artificial intelligence (AI) in the health sector, illustrating its application with current examples, and to provide policy guidance for the development, assessment, and adoption of AI technologies to advance policy objectives.

Methods: Nonsystematic scan and analysis of peer-reviewed and gray literature on AI in the health sector, focusing on key insights for policy and governance.

Results: The application of AI in the health sector is currently in the early stages.

Assessing data protection and governance in health information systems: a novel methodology of Privacy and Ethics Impact and Performance Assessment (PEIPA).

Background: Data processing of health research databases often requires a Data Protection Impact Assessment to evaluate the severity of the risk and the appropriateness of measures taken to comply with the European Union (EU) General Data Protection Regulation (GDPR). We aimed to define and apply a comprehensive method for the evaluation of privacy, data governance and ethics among research networks involved in the EU Project Bridge Health.

Methods: Computerised survey among associated partners of main EU Consortia, using a targeted instrument designed by the principal investigator and progressively refined in collaboration with an international advisory panel.

Data Rich, Information Poor: Can We Use Electronic Health Records to Create a Learning Healthcare System for Pharmaceuticals?

Judicious use of real-world data (RWD) is expected to make all steps in the development and use of pharmaceuticals more effective and efficient, including research and development, regulatory decision making, health technology assessment, pricing, and reimbursement decisions and treatment. A "learning healthcare system" based on electronic health records and other routinely collected data will be required to harness the full potential of RWD to complement evidence based on randomized controlled trials. We describe and illustrate with examples the growing demand for a learning healthcare system; we contrast the exigencies of an efficient pharmaceutical ecosystem in the future with current deficiencies highlighted in recently published Organisation for Economic Co-operation and Development (OECD) reports; and we reflect on the steps necessary to enable the transition from healthcare data to actionable information.

Development of a population-based microsimulation mode of physical activity in Canada.

Background: Computer simulation modeling makes it possible to project physical activity levels and the prevalence of related health outcomes. Such projections can help to inform programs that aim to increase physical activity levels and improve population health.

Data And Methods: The Population Health Model (POHEM) platform was used to develop a dynamic microsimulation model of physical activity among Canadian adults.

International comparisons of health system performance among OECD countries: opportunities and data privacy protection challenges.

Objective: Health data constitute a significant resource in most OECD countries that could be used to improve health system performance. Well-intended policies to allay concerns about breaches of confidentiality and to reduce potential misuse of personal health information may be limiting data use. A survey of 20 OECD countries explored the extent to which countries have developed and use personal health data and the reasons why data use may be problematic in some.

Informing policy makers about future health spending: a comparative analysis of forecasting methods in OECD countries.

Objective: Concerns about health care expenditure growth and its long-term sustainability have risen to the top of the policy agenda in many OECD countries. As continued growth in spending places pressure on government budgets, health services provision and patients' personal finances, policy makers have launched forecasting projects to support policy planning. This comparative analysis reviewed 25 models that were developed for policy analysis in OECD countries by governments, research agencies, academics and international organisations.

Health behavior change following chronic illness in middle and later life.

Objectives: Understanding lifestyle improvements among individuals with chronic illness is vital for targeting interventions that can increase longevity and improve quality of life.

Methods: Data from the U.S.

Trajectories of health-related quality of life by socio-economic status in a nationally representative Canadian cohort.

Background: Mortality and morbidity have been shown to follow a 'social gradient' in Canada and many other countries around the world. Comparatively little, however, is known about whether ageing amplifies, diminishes or sustains socio-economic inequalities in health.

Methods: Growth curve analysis of seven cycles of the Canadian National Population Health Survey (n=13,682) for adults aged 20 and older at baseline (1994/95).