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Bayesian Fall Risk Assessment Instrument

贝叶斯跌倒风险评估仪

基本信息

批准号：
7611258
负责人：
Brian R Clark
金额：
$ 13.44万
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 2011-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/7611258
关键词：
Accreditation Acute Address Affect Aged, 80 and over Algorithms Archives Assisted Living Facilities Beds Behavioral Belief Boxing Caring Cellular Phone Chronic Care Closed head injuries Collection Computer software Data Data Analyses Data Collection Databases Devices Discrimination Elderly Ensure Environment Environmental Risk Factor Equilibrium Etiology Evaluation Exercise Fracture Goals Health Hip Fractures Home Care Services Hospitals Individual Inpatients Institution Institutional Policy Internet Intervention Joint Commission on Accreditation of Healthcare Organizations Lead Life Literature Logistic Regressions Marketing Measures Medical Medicare Methodology Methods Metric Mission Modeling National Institute on Aging Nurses Nursing Assessment Nursing Homes Occupational Therapy Operative Surgical Procedures Outcome Outcome Assessment Pain Patient Care Patients Performance Phase Phase Transition Physical Restraint Physicians Play Population Prevalence Preventive Preventive Intervention Private Practice Probability Procedures Prospective Studies Provider Publishing Rehabilitation therapy Reporting Research Research Personnel Research Project Grants Retrospective Studies Review Literature Risk Risk Assessment Risk Estimate Risk Factors Role Screening procedure Sensitivity and Specificity Small Business Innovation Research Grant Solutions Specificity Stimulus Stratification System Techniques Technology Time Training Uncertainty United States Work base clinical practice clinically relevant clinically significant cohort contextual factors cost experience falls health care service organization high risk improved innovation insight instrument long bone mortality older patient prevent programs prospective prototype public health relevance restraint social statistics success tool 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. The new instrument will ensure that individuals at increased risk for falling are identified and provided with appropriate interventions to reduce fall occurrences. Avoidance of injurious falls will result in reduced pain and suffering and will lower costs of patient care, the bulk of which are borne by Medicare. 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 risk assessments based on the patient risk factor data that are available in a given setting. The proposed approach will leverage 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 and 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. PUBLIC HEALTH RELEVANCE: 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 affect patient care through more accurate targeting of fall risk prevention interventions. The new tool will find a ready market as the Joint Commission on Accreditation of Healthcare Organizations (JCAHO) began requiring (effective 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.

描述（由申请人提供）：这项多阶段SBIR研究工作的总体目标是开发一种手持式跌倒风险评估仪器，供健康和老年护理提供者使用。福尔斯在65岁以上的人中发生率高达30%，在80岁以上的人中高达40%。福尔斯使每个人都面临着危险的闭合性头部损伤和长骨骨折的风险。据报道，髋部骨折后一年的死亡率高达27%，另有22%的人失去行走能力。新的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，以减少跌倒的发生。避免受伤的福尔斯将减少疼痛和痛苦，并将降低病人护理的成本，其中大部分由医疗保险承担。贝叶斯信念网络是实现更快、更准确的跌倒评估的关键技术;贝叶斯方法允许将不同的信息合并为统一、客观的跌倒风险随机评估。跌倒风险评估工具将提供一种通用算法，用于根据给定环境中可用的患者风险因素数据初始化、调整和优化跌倒风险评估。所提出的方法将利用两个重要和现存的资产：（1）关于跌倒风险因素和跌倒患病率统计的广泛文献;以及（2）机构特定的患者跌倒风险因素和跌倒结局数据（这些数据可用于培训和调整新的评估工具，从而获得特定环境下准确的临床相关估计）。这两个数据资产将被有效地用于关闭证据和实践之间的循环。公共卫生相关性：拟议的工具将提供上级识别患者的风险下降比目前可用的筛选工具，并将导致临床实践的变化，通过更准确的目标跌倒风险预防干预影响病人的护理。随着医疗机构认证联合委员会（JCAHO）开始要求（自2005年起）寻求认证的医疗机构定期评估和定期重新评估每位患者的跌倒风险，并采取行动降低跌倒风险，新工具将找到现成的市场。