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Data Science in Healthcare - The Evolution of the Revenue Cycle

Getting the most out of staff and systems requires aligning task to talent. Is your team and your technology aligned to let each of them do what they do best?

A shift is underway in the healthcare industry to move beyond using technology to assist in daily efforts to the point of allowing technology to identify and solve problems as they happen. While many healthcare organizations are embracing these new opportunities on the clinical side of their patient experience, too often they are struggling with questions regarding how to integrate their office and back-end systems, such as the revenue cycle, to take advantage of these new tools.

Where do I start? How do I manage my people through changes in their daily activities? What resources will I need? And what’s next? These are common and, more importantly, appropriate questions to be asking.

Does your organization have a strategy for this new digital landscape and how to thrive as a result of it? As a result of viewing this on-demand webinar, you should be able to:

  • Identify what machine learning is and what it's not (and what it can and cannot do for an organization)
  • Recognize how organizations are achieving efficiencies of 50 percent in their revenue cycles with data science
  • Determine what skill sets are needed in organizations to implement these projects and how to manage them as ongoing programs
  • Identify considerations for managing staff in the adoption of these new tools
  • Measure the quick and continual payoff of these programs
  • Determine steps to implement now to help capitalize on the use of these tools

Using data science and machine learning to drive business is not a decade away. It's happening now. Tomorrow's leading organizations understand this change is here and that not only will their operations be accelerated by the change, but it will be demanded by the next generation of employees. They will not be satisfied processing the same reports and performing the same tasks repeatedly.

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Christine Campbell