Data-driven decisions require data that is trustworthy, available, and timely. Upping the dataops game is a worthwhile way to offer business leaders reliable insights. Measuring quality of any kind ...
An article recently published in Nature proposes a new way to evaluate data quality for artificial intelligence used in healthcare. Several documentation efforts and frameworks already exist to ...
Through literature review and collaborative design, we propose the Focus, Activity, Statistic, Scale type, and Reference (FASStR) framework to provide a systematic approach to health care operation ...
The European Medicines Agency (EMA) has finalized a document with recommendations on using the European Medicines Regulatory Network (EMRN) Data Quality Framework (DQF) when submitting premarket ...
In my years managing business intelligence projects, the limitations of traditional reporting have become abundantly clear. Early in my career, senior leaders would often wait weeks for static reports ...
This Forefront article synthesizes lessons from widely adopted health care quality metrics to inform future quality metric design and development. The evolution of health care quality metrics over the ...
As the value-based care reimbursement environment grows, there is an increasing interest in linking additional physician compensation to the achievement of quality outcomes as measured by certain ...
Ensuring excellent quality and outcomes is the essential goal of medical care. To achieve it, a multitude of quality metrics have been added to clinicians’ work. They include things such as ...
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