A novel case-finding strategy based on artificial intelligence for the systematic identification and management of individuals with osteoporosis or at varying risk of fragility fracture.

IF 3.1 3区 医学 Q2 ENDOCRINOLOGY & METABOLISM
Gianpaolo Voltan, Gennaro Di Giovannantonio, Giovanni Carretta, Stefano Vianello, Cristina Contessa, Nicola Veronese, Maria Luisa Brandi
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Abstract

An artificial intelligence-based case-finding strategy has been developed to systematically identify individuals with osteoporosis or at varying risk of fragility fracture. This strategy has the potential to close the critical care gap in osteoporosis treatment in primary care, thereby lessening the societal burden imposed by fragility fractures.

Background: Osteoporotic fractures represent a major cause of morbidity and, in older adults, a precursor of disability, loss of independence, poor quality of life and premature death. Despite the detrimental health impact, osteoporosis remains largely underdiagnosed and undertreated worldwide. Subjects at risk for osteoporosis-related fractures are identified either via organised screening or case finding. In the absence of a population-based screening policy, subjects at high risk of fragility fractures are opportunistically identified when a fracture occurs or because of other clinical risk factors (CRFs) for osteoporotic fracture and areal bone mineral density (aBMD) measured by dual-energy X-ray absorptiometry (DXA).

Purpose: This paper describes the development of a novel case-finding strategy, named Osteoporosis Diagnostic and Therapeutic Pathway (ODTP), which enables to identify subjects with osteoporosis or at varying risk of fragility fracture. This strategy is based on a specifically designed software tool, named "Bone Fragility Query" (BFQ), which analyses the electronic health record (EHR) databases of General Practitioners (GPs) to systematically identify individuals who should be prescribed DXA-BMD measurement, vertebral fracture assessment (VFA) and anti-osteoporosis medications (AOM).

Conclusions: The ODTP through BFQ tool is a feasible, convenient and time-saving osteoporosis model of care for GPs during routine clinical practice. It enables GPs to shift their focus from what to do (clinical guidelines) to how to do it in the primary health care setting. It also allows a systematic approach to primary and secondary prevention of fragility fractures, thereby overcoming clinical inertia and contributing to closing the gap between evidence and practice for the management of osteoporosis in primary care.

Abstract Image

基于人工智能的新型病例查找策略,用于系统识别和管理骨质疏松症患者或有不同脆性骨折风险的患者。
我们开发了一种基于人工智能的病例查找策略,用于系统识别骨质疏松症患者或有不同脆性骨折风险的患者。该策略有可能缩小初级医疗中骨质疏松症治疗的关键护理差距,从而减轻脆性骨折造成的社会负担:背景:骨质疏松性骨折是老年人发病的主要原因,也是导致残疾、丧失自理能力、生活质量低下和过早死亡的先兆。尽管骨质疏松症对健康有不利影响,但在全球范围内,骨质疏松症的诊断和治疗仍然严重不足。骨质疏松症相关骨折的高危人群是通过有组织的筛查或病例发现来确定的。在缺乏基于人群的筛查政策的情况下,脆性骨折高危人群是在发生骨折或因其他骨质疏松性骨折临床风险因素(CRFs)以及通过双能 X 射线吸收测定法(DXA)测量的平均骨矿密度(aBMD)时被偶然发现的。目的:本文介绍了一种名为 "骨质疏松症诊断和治疗路径"(ODTP)的新型病例查找策略的开发情况,该策略能够识别患有骨质疏松症或存在不同脆性骨折风险的受试者。该策略基于一个专门设计的名为 "骨脆性查询"(BFQ)的软件工具,该工具可分析全科医生(GPs)的电子健康记录(EHR)数据库,从而系统地确定哪些人应接受 DXA-BMD 测量、椎体骨折评估(VFA)和抗骨质疏松症药物治疗(AOM):结论:通过BFQ工具进行ODTP是全科医生在日常临床实践中一种可行、方便、省时的骨质疏松症护理模式。它能让全科医生将重点从 "做什么"(临床指南)转移到 "如何在初级医疗保健环境中做"。它还允许对脆性骨折的一级和二级预防采取系统的方法,从而克服临床惰性,并有助于缩小初级保健中骨质疏松症管理的证据与实践之间的差距。
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来源期刊
Archives of Osteoporosis
Archives of Osteoporosis ENDOCRINOLOGY & METABOLISMORTHOPEDICS -ORTHOPEDICS
CiteScore
5.50
自引率
10.00%
发文量
133
期刊介绍: Archives of Osteoporosis is an international multidisciplinary journal which is a joint initiative of the International Osteoporosis Foundation and the National Osteoporosis Foundation of the USA. The journal will highlight the specificities of different regions around the world concerning epidemiology, reference values for bone density and bone metabolism, as well as clinical aspects of osteoporosis and other bone diseases.
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