Bridge

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

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About Medalogix Bridge

Identifying potential hospice patients and coordinating your team

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

Our Solutions

Using data science to ensure compassionate and timely, end-of-life planning

  • Increase care quality, patient satisfaction and improve the family’s experience
  • Our predictive model leverages EMR data to generate an ordered list of patients to be clinically evaluated for end-of-life conversation and planning
  • Decreases hospitalizations and deaths on the home health census
  • Decrease unnecessary home health utilization and frequent rehospitalizations
%
decrease of deaths on the home health census
%
decrease in early deaths on the 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

Identify 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

Aveanna Healthcare Launches Homecare Homebase and Medalogix Platforms Across Home Health and Hospice Divisions

May 17, 2022, Dallas, TX – Aveanna Healthcare (the “Company”) (NASDAQ: A…

Hospice Public Reporting of New Claims-Based Quality Measures Begins in May 2022

How to prepare for New Claims-Based Quality Measures with Hospice Public…

Data-Driven Care Decisions at End-of-Life

Let the Data Do the Work: Bridging the Home Health to Hospice Continuum.

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Product Interest