A clinical validation study published in 2026 has extended the use of the eFalls fall risk prediction model to working-age adults (18β65 years) receiving mental health and learning disability services in the UK. The research, which appears in a peer-reviewed journal, externally validated the model in this population, addressing a gap as most fall risk tools are designed for older adults.
The study found that the eFalls model, originally developed for older inpatients, performs well in predicting falls among working-age adults with mental health conditions. This is significant because falls are a common but under-recognized safety issue in this group, often due to side effects of psychotropic medications, mobility issues, and other factors.
Researchers analyzed data from a large UK integrated care system, including electronic health records of patients aged 18β65 in mental health and learning disability services. The model showed good discrimination and calibration, indicating its reliability in identifying those at higher risk of falling.
This validation supports the broader use of eFalls in clinical practice, enabling healthcare providers to implement targeted fall prevention strategies for a population that has been historically overlooked in fall risk assessment. The findings could lead to improved patient safety and reduced fall-related injuries.
