Analytics

AI promises automation and augmentation, but risks include input poisoning into large amounts of data.

More than half of the respondents cited software and technology as one of their top three strategic priorities, a big leap from last year.

EHR systems rated as being difficult to operate did not perform well in safety tests, which suggests the need to optimize EHRs for ease of use.

Hippocratic AI cofounder and CEO Munjal Shah says if you build a healthcare LLM from the ground up it understands the vocabulary of healthcare better.  

Clinical leaders want data, and it’s up to the analysts to provide the tools, but both need to be integrated, says Dr. Oscar C. Marroquin, chief healthcare data and analytics officer at UPMC.  

Payel Das, principal research staff member and manager in the Trusted AI department of IBM, and an IBM master inventor, said LLMs can help to fill gaps in distribution and generate insights based on the missing data.  

AI built into the EHR can be used for clinical decision support to give a better understanding to patient treatment, says R. Ryan Sadeghian, CMIO of Hunterdon Healthcare System.

Lawrence Whittle, CCO at Verana Health, said advanced technology can harvest more insights into what's happening on a patient's journey.

Integration of the technology picks up on the nuances of a patient's health, improves workflow, aids clinical decision making and reduces burden for nurses, says Chad B. Carroll, a health informaticist on the HIMSS Nursing Informatics Committee.

LGBTQ+ care can be enhanced via data collection, according to Gabriel Garcia-Lopez, director, health information systems, at the Los Angeles LGBT Center.