HIMSS Big Data and Healthcare Analytics Forum to focus on machine learning, value-based care and population health
As Big Data continues getting bigger healthcare organizations are beginning to embrace emerging technologies such as artificial intelligence and machine learning to glean insights, transition to value-based care and advance precision medicine.
Count Stanford Health Care, El Camino Hospital and LifeBridge Health among those.
El Camino, in fact, deployed machine learning algorithms to move from predictive analytics to prescriptive analytics and ultimately reduced patient falls by 39 percent, according to Chief Nursing Officer Cheryl Reinking.
Stanford Health Care’s clinical inference and algorithms director Zeeshan Syed said machine learning can be used to uncover new knowledge and, what’s more, help healthcare executives advance precision medicine and improved care delivery tactics.
LifeBridge CIO Tressa Springmann added that putting an analytics plan in place, whether it involves machine learning now or will at some point in the future, requires a scalable roadmap replete with data governance.
And all of those set the stage for transitioning to value-based care and population health management programs.
That’s not to say it will be as easy as deploying the latest and greatest in cutting-edge software tools. Rather, the excitement that Big Data and the associated technologies hold is accompanied by confusion amid the hype, Harvard Medical School assistant professor and startup Cyft CEO Leonard D’Avolio said.
Adding to the chaos are 40-year old IT architectures misaligned with today’s clinical goals D’Avolio said which is among the reasons D’Avolio said healthcare organizations, perhaps more than any other industry, are justified in being frustrated with IT at this particular point in time.
D’Avolio, Reinking, Springmann and Syed will be among the more than 20 speakers at the HIMSS and Healthcare IT News Big Data and Healthcare Analytics Forum in San Francisco, May 15-16, 2017.
In addition to machine learning, value-based care and population health, speakers will examine the hope and hype of analytics, thriving in a big data world, check in on the state of the industry and where leadership is lacking as well as getting physicians engaged in these initiatives.
As UC Berkeley health policy professor Stefano Bertozzi, explained, healthcare data is constantly getting bigger and that means hospitals have the opportunity to improve not only care delivery but also enterprise performance — but the analytic capability is the biggest bottleneck hospitals wrangle with today.
Read more of our preview coverage of the Big Data & Healthcare Analytics Forum in San Francisco, May 15-16, 2017.
⇒ Hospital cuts costly falls by 39% due to predictive analytics
⇒ How analytics roadmaps can break organizations from vicious data cycles
⇒ Machine learning 101: The healthcare opportunities are endless
⇒ Big data is actually 'Bigger Data' for healthcare
⇒ Frustrated by Big Data? Harvard prof says it's justified