Machine Learning

ML-powered Medallia Launches Ambulatory Patient Experience Suite

Medallia

Real-time patient feedback helps drive better outcomes in one of healthcare’s fastest growing segments.

Medallia, Inc. (NYSE: MDLA), the global leader in customer and employee experience and engagement, today announced a packaged solution to enhance patient experience at ambulatory health systems – health systems that provide medical services performed on an outpatient basis.

“What we increasingly understand is the relationship between patient experience and patient outcomes,” said Chris Branner, MD, MPH, Speciality Medical Director, Urgent Care Services, Atrium Health. “Medallia helps to give real-time feedback in color, text, and graphs about what our patients are telling us about their experiences in our urgent cares. Without Medallia we would continue to look at patient experience through a backwards-facing lens.”

Ambulatory care is one of healthcare’s fastest-growing segments with projected revenue to reach $36 billion by 2023. Medallia’s Ambulatory Patient Experience Suite helps providers:

  • Effectively manage patient volume by prioritizing services and resource allocation
  • Quickly resolve service recovery issues
  • Empower employees to engage directly with patients to improve health outcomes

“With Ambulatory Care being one of the most competitive segments within healthcare today, providers can differentiate themselves, grow their business, and improve health outcomes by delivering better patient experiences.” said Toni Land, Head of Clinical Healthcare Experience, Medallia.

The solution includes:

  • A video communication platform to prioritize high-risk patients, address service recovery needs, and give patients an opportunity to leave feedback throughout the process
  • Contactless SMS communications to safely and securely schedule appointments and engage patients pre and post visit
  • Real-time feedback mechanism on patient experiences throughout the entire patient journey whether digital, telehealth or in person
  • Text analytics to identify themes and trends across the entire patient population with the use of AI and machine learning

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