BENEFIT

益处

基本信息

批准号：
8454000
负责人：
Brian R Clark
金额：
$ 49.95万
依托单位：
BARRON ASSOCIATES, INC.
依托单位国家：
美国
项目类别：
财政年份：
2009
资助国家：
美国
起止时间：
2009-02-01 至 2014-12-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8454000
关键词：
Accreditation Acute Adoption Adult Aged, 80 and over Algorithms Assisted Living Facilities Beds Belief Boxing Caring Cessation of life Chronic Care Closed head injuries Cost Savings Data Databases Devices Elderly Ensure Environment Environmental Risk Factor Equilibrium Etiology Exercise Feedback Fracture Goals Health Hip Fractures Home Care Services Hospitals Individual Injury Institution Institutional Policy Internet Intervention Joint Commission on Accreditation of Healthcare Organizations Lead Literature Logistic Regressions Marketing Measures Medicare Methodology Methods Metric Modeling Nurses Nursing Homes Occupational Therapy Online Systems Outcome Outcome Assessment Pain Patient Care Patients Phase Phase Transition Physical Restraint Physical therapy Play Policies Prevalence Preventive Preventive Intervention Probability Procedures Provider Publishing Reporting Research Research Personnel Risk Risk Assessment Risk Estimate Risk Factors Role Sampling Small Business Innovation Research Grant Solutions Stimulus System Tablets Techniques Technology Testing Time Training Trauma Uncertainty Work base clinical practice clinically relevant cohort cost design digital fall risk falls health care service organization high risk improved instrument laptop long bone mortality programs prototype public health relevance restraint screening statistics tool usability virtual

项目摘要

DESCRIPTION (provided by applicant): 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.

描述（由申请人提供）：这项多相SBIR研究工作的总体目标是开发一种手持式秋季风险评估工具，以供健康和老年护理提供者使用。在65岁以上的人中，最多30％发生跌倒，80岁以上的人最多40％。跌倒使每个人面临危险的闭合头部受伤和长骨折的风险。据报道，髋部骨折后一年的死亡率高达27％，另外22％失去了行动能力。与跌倒有关的伤害是老年人与受伤有关的主要原因。据估计，在美国，跌倒每年产生的成本超过280亿美元，该工具将确保确定跌倒风险增加的个人并提供适当的干预措施以减少FAL发生。避免造成伤害性跌倒将导致疼痛和痛苦减轻，并降低患者护理的成本。贝叶斯信念网络是将更快，更准确的跌倒评估的关键技术；贝叶斯方法论允许将不同的信息合并为对跌倒风险的统一和客观随机评估。秋季风险评估工具将提供一种通用算法，用于根据给定设置中可用的患者风险因素数据初始化，适应和优化秋季ISK评估。拟议的方法利用了两个重要和现存的资产：（1）有关跌倒危险因素和跌倒患病率统计的广泛文献；（2）特定于机构的患者跌倒危险因素和跌倒结果数据（这些数据可用于训练和调整新的评估工具，从而可以为特定设置获得准确的，临床上相关的估计值）。这两个数据资产将有效地关闭证据和实践之间的循环。成功的I阶段工作既证明了福利工具的可行性和功效。福利工具的准确性超过了当前评估工具的准确性。对I期900例患者样本的回顾性分析估计，拟议仪器的使用将实现成本节省近200万美元。