4 Healthcare IT Buzzwords Redefined: Healthcare Leaders Chime In

Data-driven applications, interoperability, population health management and artificial intelligence. The healthcare information technology industry sometimes seems like a soupy swirl of buzzwords and acronyms that leave many people scratching their heads to fully understand the true meaning.

What are some of the most popular buzzwords used by industry experts, and how exactly do they impact healthcare overall? We asked providers in human services and post-acute care to redefine four buzzwords and help others understand the true significance of the terms.

Defining interoperability

While interoperability has long been an industry buzzword, now is the time for the hospice community to embrace the concept completely. We’re still a paper-based, fax-based, hand-written industry. What we are seeing as we have been forced to be remote is how inefficient the system is.

Whether organizations use electronic health information exchange (HIE), point-to-point interfaces, Direct Secure Messaging or Carequality platforms, the ability to share patient information across organizations both internally and externally will not only make organizations more efficient but also deliver better care to the patients they serve.

John Blaschke, CIO, Care Synergy

Defining population health management

Innovations and changes within the system of care are my first thoughts when I hear population health management.

Population health management guides us in determining the best interventions for our patients.

I love collaborating with other health organizations and improving the system of care in our community for patients. We designed our model of care coordination based on risk stratification using population health and social determinants of health as our guide.

By focusing on population health within our system, we use data to address gaps in care and to improve patient outcomes. We use data to focus health promotion, disease prevention and health education to our patients based on diagnosis or health risk factor. 

Grace White, Chief Quality Officer, My Health My Resources of Tarrant County (MHMR)

Defining artificial intelligence

In healthcare, artificial intelligence can help manage and analyze data, make decisions and conduct conversations, so it has huge potential to impact diagnostic accuracy, improve patient outcomes and reduce costs.

“I’m most excited around AI research institutions are doing. For example, one of our specialties is around dementia care. I read a recent study about using AI for analyzing brain scans and brain waves based on known outcomes to predict the likelihood of someone coming down with more severe dementia.”

As a diagnosis tool, the amount of data that exists in EHRs can be analyzed by AI with an objective to do something that will pay dividends.

--Travis Gleinig, Director of IT, United Methodist Communities

Defining data-driven applications

Perhaps one of the most common buzzwords today is around “big data ” and “data-driven” applications. But what does it really mean to be data-driven?

The term describes a decision-making process that involves extracting patterns and facts from data so you can make informed decisions rather than basing decisions on intuition or observation alone.

The data derived from the application provides clear pathways to implement successful change. Within the industry, data-driven applications are often misunderstood as a place to intermittently record and reference information.

Without data-driven analysis tools, new business ventures are merely talk with no factual substance.

Dan Meyler, CFO, All Care