Among the most serious clinical issues for those managing facilities such as rehabilitation clinics and nursing homes is the problem of falls among the elderly. Frequent conditions like osteoporosis and unstable balance in these patients lead to alarmingly high rates of mortality and morbidity, substantially contributing to limited mobility, which inevitably results in cognitive decline and psychological distress.
The problem of falls in the elderly population is not only related to the high incidence of these adverse events but also to the alarming combination of incidence and the probability of resulting injury. Metabolic diseases and age-associated physiological changes, such as slowed protective reflexes, make even minor falls particularly dangerous. Most of these falls often result in fractures or require medical intervention.
Another risk associated with falls is post-trauma anxiety syndrome, where an individual excessively limits movement and activity out of fear of falling. This leads to reduced muscle strength and self-esteem, causing the elderly to avoid disclosing their falls, experiencing the event as a stigma.
Intervening to prevent falls and providing rapid assistance to fallen elderly individuals is crucial not only for patient safety but also in terms of public health, as octogenarians represent one of the fastest-growing demographic groups worldwide.
Certain clinical and functional disorders can predict who is most at risk: muscle weakness, gait and balance disorders, and dementia are strongly associated with falls. In some cases, these variables, along with other closely related covariates like arthritis, diabetes, and neurological diseases, have been identified.
These so-called “fragile” patients need to be discreetly monitored throughout their day to identify predictive signals of potential falls (such as wandering) and ensure immediate intervention if the patient is in difficulty. TapMyLife has developed an active patient safety service based on artificial intelligence and image recognition systems called RSACAM. This service ensures widespread and active monitoring of patients with simple cameras installed in the rooms of “at-risk” patients, allowing monitoring directly from the nurse’s station or via a smartphone. If abnormal movements are detected (e.g., getting out of bed without assistance, falling, or leaving the room), the healthcare provider is immediately alerted, can visually verify the situation from the nurse’s station console or smartphone, and assist the patient in real-time to prevent a risky situation.
TapMyLife researchers have developed sophisticated artificial intelligence algorithms with livestreaming: a highly parameterized system designed to provide the highest level of assistance available today, ensuring high safety standards even in the most critical departments.
With RSACAM, TapMyLife redefines the care of the most fragile patients based on an innovative concept of ACTIVE PATIENT SAFETY, ensuring timely intervention in high-risk situations while also improving the management of human resources and the movements of operators within the ward.
