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How One Hospital Network Turned HCAHPS Data Into Actionable Insights

How a major hospital network turned to Unsupervised to get more out of their surveys by finding small but impactful patterns in the data.
How One Hospital Network Turned HCAHPS Data Into Actionable Insights

How One Hospital Network Turned HCAHPS Data Into Actionable Insights

Between private insurance, medicare and medicaid, there’s no shortage of funding mechanisms for hospitals. But whenever government funding is involved there are always caveats.

A portion of the $644 billion spent on medicare annually is withheld and distributed based on patient responses to the annual Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey. The survey itself is a mixture of multiple choice and free response questions. And those don’t play well with traditional BI tools or supervised learning.

Still, committed healthcare institutions strive to learn these patient surveys. One major hospital network turned to Unsupervised for a better way to unearth insights from their HCAHPS survey responses to improve their scores and maximize medicare reimbursements.

Finding Simple Action in Complexity

Within weeks, Unsupervised unearthed insights hiding in plain sight across survey responses. The hospital network found many patterns leading to new strategic opportunities quickly, but focused on three areas from their findings:

1)   Room assignments

2)   Weekend staffing

3)   Visiting Surgeon Protocols

Take room assignments. Hospital administrators were quickly able to see from the unstructured data that rooms close to the elevator and nursing desks have higher mention of noise using Unsupervised. The hospital reassessed rooming assignments: patients that spend more of the day outside of their room would be assigned the noisier ones.

This insight is something they never could have found within their dashboards, and they didn’t have the resources to manually review and track commonalities across every survey response. And even if they did, the correlation of noisiness to room assignments with a manual review would be unlikely at best.

Acting on these opportunities enabled the hospital system to boost their HCAHPS scores and thus increase funding. What’s more, whenever there are new survey responses, Unsupervised updates and finds the new patterns that matter so the hospital system is always acting on the freshest intel.

Download our Unsupervised for Healthcare to learn more about how to transform your healthcare institution into a healthcare leader with AI.

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