S. Hawkins1, L. Khoury1, V. Sim1, A. Gave1, M. Panzo1, S. M. Cohn1 1Staten Island University Hospital-Northwell Health,Surgery,Staten Island, NY, USA
Introduction:
Falls in the elderly remain a growing public health burden despite decades of research on a variety of falls-prevention strategies. This trend is likely due to current strategies only capturing a limited proportion of those in the community at risk for falls. A new approach to falls-prevention focused on wider community-based dissemination of falls-prevention strategies is called for. We created a model of falls that identifies high risk areas or “hot-spots” for fall risk, identifying community-based study populations for subsequent falls-reduction strategy and implementation research.
Methods:
We queried the trauma registry of a level 1 trauma center, representing a relatively captured trauma population in a dense urban-suburban setting. We extracted the resident addresses of all patients age 60 and over who were admitted with a mechanism of falls over the period 2014 to 2017. We used geographic information systems software to map the addresses to census zones, and generated a heat map representing the fall density within each zone in our region.
Results:
The area is served by two trauma centers that capture nearly all of the trauma volume of a region with a population of nearly half a million. The county is divided into 107 populated census tracts that range from 0.3 to 1.1 square km. The incidence of falls in the elderly was consistent over the 4 years of study throughout the populated census zones within the hospital’s catchment area. The density of residents who presented to the trauma center with a fall mechanism ranged from less than 1 to 180 per sq km. There were 6 census zones with falls density above 80, which can be considered “hot-spots” for falls risk (see Figure). These zones are similar with respect to land use, population, and demographics.
Conclusion:
Using Geographic Information Systems with trauma registry data identified discreet geographic regions with a higher density of elderly falls. These “hot-spots” will be the target of future community-directed falls-reduction strategy and implementation research.
