Medical teams, a quick question: Are any of your patients currently at risk of falling right now?

Ever found yourself wishing you could foresee when critical patients might attempt to leave their bed unassisted? Or head to the bathroom alone? Can you assess the risk in real-time for all patients simultaneously?

Falls in hospitals are a significant concern both in terms of patient safety and economic costs.

Here’s a comprehensive overview of how the collaboration between HOOBOX and Intel’s AI team is revolutionizing patient care:

1. Incidence:

•  In the U.S., it’s estimated that between 700,000 and 1,000,000 people fall in hospitals each year.
• Fall rates in acute care settings range from 3.3 to 11.5 falls per 1,000 patient days, with the rates varying based on the type of hospital unit.

2. Injury Rate:

• About 30-35% of falls result in some form of injury.
• Major injuries such as fractures, lacerations, or internal bleeding occur in 4-6% of falls.

3. Economic Costs:

• The costs associated with falls can be extensive. A single fall can increase the cost of a hospital stay by over $14,000 on average.
• Falls result in an extended hospital stay by 6.3 days on average.
• When considering indirect costs, like litigation, the financial toll of falls can be even higher.

4. Other Considerations:

• Falls can lead to a prolonged hospital stay, reduced quality of life, and, in severe cases, increased mortality.
• Hospitals might face penalties or reduced reimbursements from insurance providers due to high fall rates.
• Additionally, falls can be a source of legal claims, further elevating the costs for healthcare facilities.

5. Preventive Measures:

• Investing in preventive measures, such as fall prevention technologies can be cost-effective in the short run.
• The initial investment in training, technology, or protocols can lead to significant savings by reducing the number of fall-related injuries and the associated costs.
• The considerations are that prevention technology must be precise and, in general, they are not democratized. They are expensive, allowing only a few large hospitals to acquire the solutions.”

Enter the SADIA Solution – an innovative leap towards redefining patient safety

Recognizing this challenge, HOOBOX Robotics and Intel have come together to revolutionize patient care with the SADIA Solution.

SADIA, a state-of-the-art solution assesses hundreds of essential data points, pinpointing fall risks in real-time, giving medical teams the vital opportunity to prevent potential incidents.

A core aspect of this data is understanding the patient’s current position along with their movement intentions. With the combined brilliance of engineers and scientists from the Intel AI Program and HOOBOX, our model captures these movements with high precision.

Latest Breakthrough:

HOOBOX & Intel AI Program Pave the Way for Universal Patient Care Solutions

In our latest update, SADIA is now enhanced and optimized by Intel technology including Neural Network Compression Framework (NNCF) and Intel® Distribution of OpenVINO™ Toolkit.

The computer vision model is no longer exclusive to large-scale hospitals and allows local medical facilities (not just in Brazil, but also in other nations facing similar challenges) to process vast amounts of patient and visual data in a cost-effective manner.

In essence, HOOBOX and Intel are charting a path towards enhanced and safer patient care globally.

Congratulations to Intel AI team and HOOBOX for the remarkable recent breakthroughs!