A turn for the better: Intelligent health operations

Healthcare continues to change in dramatic and often unpredictable ways. It’s a scramble for organizations in the industry to simply keep up.

For many healthcare businesses, operations are a tangle of complex and disconnected technologies and processes, making it hard to manage costs, improve service quality and become more consumer-centric.

What’s the answer? Accenture research identifies three keys to transforming healthcare organizations: make operations more “intelligent” to transform key business processes; make better decisions, faster; and create more compelling customer experiences.

In this paper, we discuss the key elements of intelligent operations and how healthcare organizations can get on the path to building them.

RELATED: A turn for the better: Intelligent Health Operations
RELATED: Accenture Operations

Healthcare organizations need Intelligent Operations

The intelligent operations healthcare organizations need to compete and grow are driven by a mix of critical elements: innovative talent, rich data, applied intelligence, cloud and ecosystem partnerships.

Combined the right way, these elements enable organizations to transform business processes and make better decisions, more quickly and confidently.

Consider the healthcare claims process, for example. Through digital monitoring tools, intelligent operations alert processors about claims that may be stranded in inventory a few days shy of entering the penalty box. Digital alerts can prevent the insurer from incurring late-payment interest charges and help avoid fielding calls from providers inquiring about payment status.

How does it work?

Transforming processes through intelligent operations, and creating the tools that support them, requires a fundamental understanding of several key details:

• The type of work the process involves;
• What kind of people are needed to do that work;
• Whether there are opportunities to automate some or all of the work; and,
• Which type of automation makes the most sense (for example, Robotic Process Automation or artificial intelligence).

Once these items are understood, human ingenuity will be needed to build and manage these automation tools—and these uniquely human skills will become even more critical as organizations deploy data analytics to create deep, actionable insights and use more advanced technologies to manage processes.

In fact, with increased automation, an organization’s process experts will gradually change roles, moving from processor to decision maker, making conclusions based on the data the AI tools present and taking appropriate actions.