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Home Health, Hospice Operators and Their Patients Benefit from Predictive Modeling

Posted by fivebyfive on September 09, 2013

The U.S. Department of Health and Human Services has indicated that expanding the reach of hospice care holds enormous potential benefits for those nearing the end of life, whether they are in nursing homes, their own homes or in hospitals.

Additionally, numerous studies have shown that patients benefit from hospice’s objective, which is to treat the patient and his pain instead of wrestling the patient’s disease.

A Gallup poll revealed that nine in 10 adults would prefer to die in their homes, free of pain, surrounded by family and loved ones. Hospice works to make this happen.
National Hospice and Palliative Care Organization research showed that a 74.2 percent of patients cite their pain easing to a comfortable level within 48 hours of their initial hospice assessment.
Judging the appropriate time for hospice transfer can be difficult. When is it too soon to forego disease treatment and when is disease treatment a moot practice that prolongs suffering?

Medalogix’s predictive modeling-based hospice transfer solution can help. It pools through patient and home care agency data to deliver concrete insights that help clinicians and patients’ families understand when care should focus primarily on treating the patient rather than the disease.

By analyzing clinical and demographic Oasis-C variables, patient medication histories, comorbid acuities, vital signs and home care agency specific data, Medalogix’s hospice transfer tool generates a new report every 24 hours that details the top 5, 10 and 25 percent of patients who would benefit most from palliative care.

This equips clinicians with concrete information that can help them, physicians, patients and patients’ families determine if it’s the right time to transfer out of home health into hospice care.

How Medalogix’s hospice transfer solution developed:

Our hospice transfer notification solution is perfect for dual home care/hospice operators, because it was originally developed as a custom solution for one of our dual operator clients.

The particular client learned about our readmission reduction predictive modeling solution, and had an “ah ha moment:” If Medalogix predictive modeling could identify patients who were at the greatest risk of hospital readmission, it could recognize the patients best suited for transfer to hospice.

When we realized how this solution could benefit our client and our client’s patients, we created a custom model. It has proven so effective; we’ve added it to our permanent suite of predictive modeling solutions.

Do you have needs predictive modeling could help you and your organization with? Let us know your ideas in the comment section below.

   

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