When a customer shares their unsolicited experiences, you know you’re doing things right! Mike Logan, CEO of Michigan Masonic Home, was published as guest columnist in a recent issue of McKnight’s Long-Term Care News, sharing the success his team experienced using SAIVA’s artificial intelligence to dramatically reduce rehospitalizations.
“I am pleased to say that, based upon our first couple of months using machine learning, we improved our overall percentage of new resident admission rehospitalizations from 20% to 10.5%. That was in a three-month period.”
Masonic Pathways, a Life Plan Community in the heart of Michigan, adopted SAIVA’s machine learning solution which produces daily reports listing patients at risk for decline and rehospitalization. Logan noted in his guest column:
- “Essentially, the machine-learning technology does the work of pouring through the resident’s chart to find trends and behaviors that predict when a resident is at risk of being rehospitalized.
- SAIVA reports help us identify early signs of imminent decline and rehospitalization risk, but organizations must still have the human critical thinking skills and clinical acumen to optimize the predictive model.
- Through machine learning, we can save time and effort and strengthen our overall clinical acumen by analyzing the daily reports.”
For more information on how SAIVA helps you prevent readmissions request a free consult.