Analytics
In the COVID-19 era, health systems recognize that existing data infrastructure is inadequate. Here are three things large datasets need to be useful.
Health is in the throes of some of the most significant changes as systems reel from a variety of rapidly changing environments. Dr Charles Alessi, Chief Clinical Officer at HIMSS, explores lessons learned, as we look cautiously to a better 2022.
At Penn Medicine, integrated product teams – comprising data scientists, physicians and software engineers, among others – are helping improve AI and machine learning applications.
While traditionally deeply skeptical of artificial intelligence in clinical settings, in today's fast-changing care delivery landscape many physicians are thinking more proactively about how AI can improve quality and patient experience.
Health systems that refuse to see themselves as engineering houses risk falling behind in their ability to properly leverage artificial intelligence and machine learning.
A bold vision for data-driven Latin American health, illustrated by a Peruvian pilot.
Germany will soon be embarking on a national project to assess the digital maturity of its 2,000 hospitals. If it focuses on understanding the impact on clinicians and patients, it can catch up with the world’s digital health leaders, says Armin Scheuer, VP international business development, HIMSS.
As COVID-19 continues to surge in Los Angeles, LANES is enabling free-flowing data insights – medical, behavioral and socioeconomic ─ to close information gaps and improve clinical decision support for better outcomes.
An integrated coaction model, or iCaM, is ideal for addressing complex multispecialty parameters associated with health inequities and COVID-19.
Data from a real-time location system, covering nearly 4.3 million square feet, offers the ability to see patients and staff who may have come into proximity with an infected person.
