Using data to guide end-of-life conversation and planning

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Medalogix Bridge

Identifying potential hospice patients and coordinating your team

A 2021 study from the Stanford School of Medicine found that although 80% of Americans say they would prefer to die at home, only 20% do. Medalogix Bridge supports patients’ wishes, using machine learning to identify patients earlier who are most likely to benefit from hospice. This leads to dramatic improvements in care quality and efficiency.

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Data science ensures compassionate and timely end-of-life planning

  • Increase care quality and patient satisfaction improving the family’s experience
  • Decrease hospitalizations and deaths on the home health census
  • Decrease unnecessary home health utilization and frequent rehospitalizations
decrease in deaths on home health census
decrease in earlier deaths on hospice census

Increases billable hospice days
by up to 180%

Our predictive model leverages EMR data to generate an ordered list of patients to be clinically evaluated for hospice appropriateness

Identifies patients on the home health census who are likely to pass away in the next 90 days

Provides workflow which allows clinicians to move patients through a customized virtual care path

Dashboards and reports that monitor utilization and patient outcomes

Our Expertise

The FY 2024 Hospice Payment Rate Update Proposed Rule: Why Quality Matters Even More

By: Cyndi Rizzitello, MSN, RN, BC On March 31, 2023, the Centers …

Medalogix Expands Executive Team to Fuel Continued Growth

Veteran Healthcare Software and Technology Services Executive Joins Mach…

Medalogix Feature: MarketWatch article - how hospice can help ease the last days.

Medalogix In the News: MarketWatch

‘We do not do the end of life well’ in America: How hospice can help eas…

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