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 ...
We developed a framework of five data quality dimensions (DQD; completeness, concordance, conformance, plausibility, and temporality). Participants signed a consent and Health Insurance Portability ...
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 ...
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 ...
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 ...
Results that may be inaccessible to you are currently showing.
Hide inaccessible results