Electronic health record data can identify gaps in maps used for quality improvement for high-risk processes such as hospital discharge when using the Failure Mode and Effects Analysis (FMEA) approach ...

Good data quality is crucial for successful data and analytics initiatives and is increasingly pivotal to artificial intelligence impact. D&A leaders, including chief data and analytics officers, are ...

Organizations are increasingly utilizing artificial intelligence (AI) to support their decision-making. It’s enabled them to be more proactive rather than reactive, predicting and eliminating areas of ...

Continuous electronic monitoring with telemetry is an important hospital practice for monitoring patients who are at high risk of serious cardiac events. Unfortunately, it is often overutilized. When ...

It is undeniable that artificial intelligence (AI) has permeated every aspect of our lives in a modern, digital world − from entertainment and manufacturing, to security and even healthcare. The AI ...

Quality Improvement (QI) projects require a series of distinct steps and timely data collection that will allow clinics to see if changes are yielding results, a consultant told attendees at a ...

The higher education accreditation system relies on infrequent, resource-intensive reviews that occur every five to 10 years, often creating lags in identifying and addressing quality concerns at ...

Linying Dong is affiliated with Ryerson University, and volunteers at the Board of Directors of Carefirst. Karim Keshavjee is the CEO and majority shareholder of InfoClin Inc, an organization that ...

The Veterans Affairs Department should improve the process it has to find missing or erroneous data in its reports on economic stimulus law funding, according to a new audit from the department’s ...