Transforming Nursing Care: Leveraging AI to Prevent Patient Falls and Save on Hospital Annual Costs
In-patient falls are very common and usually encompass devastating consequences for patients, hospitals, and the healthcare system. In the US, close to 1 million hospitalized patients fall while in nursing care each year — a nursing-sensitive indicator of the quality of in-patient care. Though research shows that close to one-third of these falls could have been prevented, they are still more common than they should and usually result in fractures, lacerations, or internal bleeding, leading to increased healthcare operations and unexpected amplified costs for hospitals.
Overcoming the challenges associated with developing, implementing, and sustaining a fall prevention strategy, requires optimizing nursing care and utilizing new technologies to better manage the patients’ underlying fall risk factors and re-invent the patient-nurse relationship.
Join our 60-minute insightful session that delves into the realm of healthcare innovation, focusing specifically on the use of AI in nursing and the ways it is expected to enhance efficiency in fall prediction and workflow, while reducing hospital costs caused by annual accidents.
Learning Objectives:
- Fostering a culture of innovation among nursing teams
- Introducing innovative approaches to optimize resource allocation within nursing practices
- Utilizing AI to improve nursing efficiency and workflow, while better managing patients’ underlying fall risk factors
- Discussing the impact of inpatient falls on hospital finances and patient care outcomes
- Developing, implementing, and sustaining a fall prevention strategy
Speakers:
- Lucy Torres, Director of Nursing, Inspira Health
- Michele Szkolnicki, Senior Vice President & Chief Nursing Officer, Penn State Health
- Julie Mirkin, SVP & CNO, Brookdale University Hospital and Medical Center
- Steve Kiene, CEO, Ocuvera
