Analytics

Artificial intelligence and machine learning can be leveraged to improve healthcare outcomes and costs -- here's how to monitor AI.

To get the most out of AI, doctors and nurses need to be properly trained, a new challenge that requires a new mindset.

Safran is responsible for leading efforts to use data, measurement, incentives and reporting to improve the quality, outcomes and affordability of care.

While AI has already shown promise in automating certain tasks, it doesn't seem likely that it will replace flesh-and-blood clinicians anytime soon.

Case study: Revised paper statements and new digital patient portal drove a 38% improvement in self-pay collections, a 21% reduction in cost-per-dollar collected and patient satisfaction rose from 28% to more than 50%.

Financial trust was high for about half of the CIOs surveyed, but most said they want to make changes, especially in how the data is accessed.

John Daniels, VP of HIMSS Analytics, says there is more to digitizing an organization than installing EMR functions, and discusses other adoption and maturity models including infrastructure, AI and continuity of care.

Jane Miller, COO of Royal Children's Hospital in Melbourne, Australia, says her organization, which reached the elite stage 7 EMRAM, treated EMR implementation as a clinical transformation project, not an IT project.

Sam Hanna, associate dean of graduate and professional studies and program director in healthcare management at American University, discusses why workforce development is needed to use data and technology to create targeted therapies.

There are a lot more blockchain jobs than there were at this time last year, and they may coming to healthcare sooner than people think.