Heather Holmquist, RN
10:23 AM

With automation, turnaround times are now 40-45 days – way down from 90-120, previously. And before the tools were in place, the team was credentialing eight applicants per month – now that number is 35.

09:47 PM

AI has permeated various aspects of daily life in recent years, but its impact on healthcare has been hailed as revolutionary. Studies have predicted that by the end of 2026, 55% of healthcare organisations in Asia Pacific will have data governance frameworks that prioritise AI’s ethical and explainable use. 

Readers evaluating an X-ray image
02:52 AM

Also, Mater has added more specialties to its eConsultant service.

Digitally-created image of a network with various devices
10:19 AM

Also: OM1 now offers a platform that translates population patterns for clinical decision-making at the provider level.

Kelly Vaughn of Nebraska Medicine on AI
11:01 AM

The accomplishment puts the health system in a better position to attract and retain the talent that is so critical to its ability to serve its patients, says its VP of operations.

A doctor in a remote call using a desktop computer
05:18 AM

Also, Canberra Antenatal Care has digitised its patient pathway for expectant parents.

KLAS HIMSS Global Conference booth banner
10:54 AM

Researchers recognized Epic, athenahealth, Impact Advisors, Evergreen, Chartis and others for notable performances based on customer experience feedback from this past year.

Helen Waters of Meditech on AI
10:24 AM

Helen Waters, chief operating officer at the EHR giant, describes the company's artificial intelligence strategy and shows how provider organizations can benefit today from NLP, LLMs, generative AI and more.

Puzzle pieces fitting together, showing connection and success
11:20 AM

Real-world examples from Premier Inc. showcase how machine learning and natural language processing are helping providers use structured and unstructured data to drive more efficient operations, innovate care delivery and improve patient experience.

CGI brain image - Yuichiro Chino/Getty Images

As health systems deploy AI – using it for everything from simple process automations, to helping reduce provider burden, to advanced clinical decision support models, to expanding the possibilities of patient care – they're confronting some key challenges, such as algorithmic bias, model transparency and sometimes clinician mistrust.