PURPOSE: Effective use of routine data to support integrated chronic disease management
(CDM) and population health is dependent on underlying data quality (DQ) and, for cross …

Over the past decade, there has been a notable surge in AI-driven research, specifically
geared toward enhancing crucial clinical processes and outcomes. The potential of AI …

The growing amount of data in operational electronic health record systems provides
unprecedented opportunity for its reuse for many tasks, including comparative effectiveness …

Objective: To create practical recommendations for the curation of routinely collected health
data and artificial intelligence (AI) in primary care with a focus on ensuring their ethical use …

The transition towards a Circular Economy (CE) has been receiving an increasing amount of
attention in the built asset industry. One of the key aspects of CE is traceability, which can …

Background The increased use of electronic medical records (EMRs) in Canadian primary
health care practice has resulted in an expansion of the availability of EMR data. Potential …

Methods: We describe a data quality analysis tool (called Achilles Heel) developed by the
Observational Health Data Sciences and Informatics Collaborative (OHDSI) and compare …

In any country the health sector is important in terms of human wellbeing and large in terms
of economics. The health sector might therefore be expected to be a finely tuned enterprise …

Purpose Recruitment to trials is often difficult. Many trials fail to meet recruitment targets
resulting in underpowered studies which waste resources and the time of those who …

Background In the context of the Medical Informatics Initiative, medical data integration
centers (DICs) have implemented complex data flows to transfer routine health care data …