The overall goal of this multi-phase SBIR research effort is to develop a handheld fall risk assessment instrument for use by health and elder care providers. Falls occur in up to 30% of those over the age of 65 and up to 40% for people over the age of 80. Falls place each individual at risk for dangerous closed head injury and long bone fractures. The mortality rate at one year following a hip fracture has been reported to be as high as 27%, with another 22% losing the ability to ambulate. Fall-related injuries are the leading cause of injury-related deaths among elderly adults. Falls are estimated to incur costs of over $28 billion annually in the U.S. The proposed instrument will ensure that individuals at increased risk for falling are identified and provided with appropriate interventions to reduce fal occurrences. Avoidance of injurious falls will result in reduced pain and suffering and will lower the costs of patient care. Bayesian belief networks are the key technology that will enable faster and more accurate fall assessments;the Bayesian methodology allows the merging of disparate information into a unified and objective stochastic assessment of fall risk. The fall risk assessment tool will furnish a universal algorithm for initializing, adapting, and optimizing fall isk assessments based on the patient risk factor data that are available in a given setting. The proposed approach leverages two important and extant assets: (1) an extensive literature on fall risk factors and fall prevalence statistics;and (2) institution-specific patient fall risk factor nd fall outcomes data (these data can be used to train and adapt the new assessment tool, allowing accurate, clinically relevant estimates to be obtained for particular settings). These two data assets will be used effectively to close the loop between evidence and practice. The successful Phase I work demonstrated both the feasibility and the efficacy of the BENEFIT instrument. The BENEFIT instrument's accuracy surpassed that of current assessment tools by a wide margin. A retrospective analysis of a 900 patient sample in Phase I estimated that use of the proposed instrument would have realized a cost savings of nearly $2 million.
The proposed tool will provide superior identification of patients at risk for falling than presently-available screening instruments and will lead to changes in clinical practice that aect patient care through more accurate targeting of fall risk prevention interventions. The new tool will nd a ready market as the Joint Commission on Accreditation of Healthcare Organizations (JCAHO) began requiring (eective 2005) health care organizations seeking accreditation to routinely assess and periodically reassess each patient's risk for falling and to take action to reduce the risk of falling. Furthermore, recent changes to Medicare policy limit and, in some cases, prohibit reimbursement to institutions for the treatment of avoidable hospital-acquired conditions, including falls and fall-related trauma. These policy changes represent significant market pull and will stimulate and accelerate the adoption of the BENEFIT instrument.