Fall detection, assessment, and prevention is a challenging issue across the care continuum. Despite wide recognition as a considerable problem, fall-related injuries are still the most frequently reported adverse events in hospital inpatient settings, with 3-20% of patients falling at least once during their stay. According to the Agency for Healthcare Research and Quality reports, 30% to 51% of falls result in injury. In the United States alone, the number of inpatient falls exceeds 1 million per year, with elderly individuals being the most vulnerable. As a testament to its importance, fall research was listed as a top priority in the Institute of Medicine's report to Congress on national priorities. Diverse factors contribute to falls, including patient factors (e.g., cognitive state, muscle weakness, medi- cations), environmental factors (e.g., bed/toilet positioning, trip hazards), and institutional factors (e.g., poor responsiveness to call bells or bed/chair alarms, inadequate fall prevention measures). Although hospitals em- ploy diverse programs to prevent falls and fall injuries, an essential component to a fall prevention program is accurate determination of fall events, as many falls are unseen and unreported. The body-worn FallCall system, proposed herein, will leverage powerful sensing capabilities to provide robust fall detection and to report fall locations without bothersome false alarms. The FallCall body-worn instrument will embody a reusable miniature electronics package that is encapsulated in a disposable, hypoallergenic adhesive patch. The patch can be placed anywhere on the torso to minimize interaction with other medical equipment or injury sites. The system will continuously monitor patients and issue a timely alert if a fall is detected, minimizing patient time on the ground, as well as injury assessment and treatment latencies. The FallCall system will also allow patient location to be determined (including the room and oor of the hospital) using a redundant wireless mesh network. The instrument will be powered by a miniature rechargeable battery that will last for at least one week. The FallCall system will also have the capability to issue wander and inactivity alerts. Additionally, the system can use its internal sensors to track measures of stability, providing objective data that may o er improved predictive value in identifying individuals at risk for falling and tracking fall risk longitudinally. The proposed system will represent one of the rst ways to objectively measure the response time of clinical sta when a fall occurs, and will be a key component in evaluating and improving fall prevention programs.

Public Health Relevance

The FallCall system will detect fall events and issue timely alerts (including fall location) when such events occur, in addition to providing stability and activity metrics to help ascertain an individual's fall risk and changes thereto. Use of the FallCall system will minimize response latency and time on the ground' after a fall event, and provide objective measures of sta response time. Fall determination with high sensitivity and speci city is an essential component of e ective fall assessment and prevention programs. The proposed tool will find a ready market, as the Joint Commission on Accreditation of Healthcare Organizations (JCAHO) requires health care organizations seeking accreditation to routinely assess and reassess each patient's risk for falling, and to take action to reduce the risk of falling. Furthermore, Medicare policy limits and, in some cases, prohibits reimbursement to institutions for the treatment of avoidable hospital-acquired conditions, including falls and fall-related trauma. These policy changes represent signi cant market pull and will accelerate the adoption of the FallCall instrument.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Small Business Innovation Research Grants (SBIR) - Phase I (R43)
Project #
1R43AG056224-01
Application #
9343403
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Salive, Marcel
Project Start
2017-12-01
Project End
2019-11-30
Budget Start
2017-12-01
Budget End
2019-11-30
Support Year
1
Fiscal Year
2018
Total Cost
Indirect Cost
Name
Barron Associates, Inc.
Department
Type
DUNS #
120839477
City
Charlottesville
State
VA
Country
United States
Zip Code
22901