Aruska N D'Souza, Catherine L Granger, Nina E Leggett, Melanie S Tomkins, Jacqueline E Kay, Catherine M Said
{"title":"预测急诊普通病房老年人的出院去向:对 23 种评估工具心理计量特性的系统性回顾。","authors":"Aruska N D'Souza, Catherine L Granger, Nina E Leggett, Melanie S Tomkins, Jacqueline E Kay, Catherine M Said","doi":"10.1519/JPT.0000000000000401","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Predicting discharge in older people from general medicine wards is challenging. It requires consideration of function, mobility, and cognitive levels, which vary within the cohort and may fluctuate over a short period. A previous systematic review identified 23 assessment tools associated with discharge destination in this cohort; however, the psychometric properties of these tools have not been explored.</p><p><strong>Purpose: </strong>To evaluate, synthesize, and compare the psychometric properties of 23 assessment tools used to predict discharge destination from acute general medical wards.</p><p><strong>Methods: </strong>Four databases were systematically searched: Medline (Ovid), Embase (Ovid), Cumulative Index of Nursing and Allied Health Literature (CINAHL), and Evidence-Based Medicine Review databases. Studies were included if participants were from general medicine or acute geriatric wards and investigated at least one psychometric property (reliability, internal consistency, measurement error, responsiveness, hypothesis testing, and structural or criterion validity) in 23 previously identified assessment tools. Data were extracted and methodological quality were assessed independently by 2 assessors using the COnsensus-based Standards for selection of health Measure INstruments (COSMIN) checklist. As per the COSMIN checklist, results were rated against \"sufficient,\" \"insufficient,\" or \"indeterminate.\"</p><p><strong>Results: </strong>Forty-one studies were included. The de Morton Mobility Index (DEMMI) was the most rigorously evaluated assessment tool; it scored \"sufficient\" psychometric properties in 5 of 7 psychometric categories. The Alpha Functional Independence Measure (AlphaFIM), Barthel Index, and Mini-Mental State Examination (MMSE) demonstrated \"sufficient\" psychometric properties in at least 3 psychometric categories. The remainder of the tools (n = 19, 83%) had \"sufficient\" psychometric properties in 2 or fewer psychometric categories.</p><p><strong>Discussion and conclusion: </strong>Based on current evidence, out of 23 assessment tools associated with discharge destination in acute general medicine, the DEMMI has the strongest psychometric properties. Other tools with substantial evidence in this cohort include the AlphaFIM, MMSE, and Barthel Index. Research is required to thoroughly evaluate the psychometric properties of the remaining tools, which have been insufficiently researched to date. Results can be used by physical therapists to guide selection of appropriate tools to assess mobility and predict discharge destination.</p><p><strong>Trial registration: </strong>A priori, PROSPERO (CRD 42017064209).</p>","PeriodicalId":49035,"journal":{"name":"Journal of Geriatric Physical Therapy","volume":" ","pages":"E109-E123"},"PeriodicalIF":1.5000,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Predicting Discharge Destination in Older People From Acute General Medical Wards: A Systematic Review of the Psychometric Properties of 23 Assessment Tools.\",\"authors\":\"Aruska N D'Souza, Catherine L Granger, Nina E Leggett, Melanie S Tomkins, Jacqueline E Kay, Catherine M Said\",\"doi\":\"10.1519/JPT.0000000000000401\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Predicting discharge in older people from general medicine wards is challenging. It requires consideration of function, mobility, and cognitive levels, which vary within the cohort and may fluctuate over a short period. A previous systematic review identified 23 assessment tools associated with discharge destination in this cohort; however, the psychometric properties of these tools have not been explored.</p><p><strong>Purpose: </strong>To evaluate, synthesize, and compare the psychometric properties of 23 assessment tools used to predict discharge destination from acute general medical wards.</p><p><strong>Methods: </strong>Four databases were systematically searched: Medline (Ovid), Embase (Ovid), Cumulative Index of Nursing and Allied Health Literature (CINAHL), and Evidence-Based Medicine Review databases. Studies were included if participants were from general medicine or acute geriatric wards and investigated at least one psychometric property (reliability, internal consistency, measurement error, responsiveness, hypothesis testing, and structural or criterion validity) in 23 previously identified assessment tools. Data were extracted and methodological quality were assessed independently by 2 assessors using the COnsensus-based Standards for selection of health Measure INstruments (COSMIN) checklist. As per the COSMIN checklist, results were rated against \\\"sufficient,\\\" \\\"insufficient,\\\" or \\\"indeterminate.\\\"</p><p><strong>Results: </strong>Forty-one studies were included. The de Morton Mobility Index (DEMMI) was the most rigorously evaluated assessment tool; it scored \\\"sufficient\\\" psychometric properties in 5 of 7 psychometric categories. The Alpha Functional Independence Measure (AlphaFIM), Barthel Index, and Mini-Mental State Examination (MMSE) demonstrated \\\"sufficient\\\" psychometric properties in at least 3 psychometric categories. The remainder of the tools (n = 19, 83%) had \\\"sufficient\\\" psychometric properties in 2 or fewer psychometric categories.</p><p><strong>Discussion and conclusion: </strong>Based on current evidence, out of 23 assessment tools associated with discharge destination in acute general medicine, the DEMMI has the strongest psychometric properties. Other tools with substantial evidence in this cohort include the AlphaFIM, MMSE, and Barthel Index. Research is required to thoroughly evaluate the psychometric properties of the remaining tools, which have been insufficiently researched to date. 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引用次数: 0
摘要
背景:预测老年人从普通病房出院是一项挑战。它需要考虑功能、活动能力和认知水平,而这些因素在人群中各不相同,并可能在短期内波动。目的:评估、综合并比较 23 种用于预测急性全科病房老年人出院去向的评估工具的心理测量特性:方法:系统检索了四个数据库:Medline(Ovid)、Embase(Ovid)、Cumulative Index of Nursing and Allied Health Literature(CINAHL)和Evidence-Based Medicine Review数据库。如果研究对象来自普通内科或急诊老年病房,并对 23 种先前确定的评估工具中的至少一种心理测量特性(可靠性、内部一致性、测量误差、反应性、假设检验、结构或标准有效性)进行了调查,则可纳入研究。数据提取和方法学质量由两名评估员使用基于共识的健康测量工具选择标准(COSMIN)核对表进行独立评估。根据 COSMIN 核对表,评估结果分为 "充分"、"不充分 "或 "不确定":共纳入 41 项研究。德莫顿移动指数(DEMMI)是经过最严格评估的评估工具;在 7 个心理测量类别中,有 5 个类别的心理测量属性为 "充分"。阿尔法功能独立性测量(AlphaFIM)、巴特尔指数(Barthel Index)和迷你精神状态检查(MMSE)至少在 3 个心理测量类别中表现出 "充分 "的心理测量特性。其余工具(n = 19,83%)在 2 个或更少的心理测量类别中具有 "充分 "的心理测量特性:根据目前的证据,在与急诊全科出院目的地相关的 23 种评估工具中,DEMMI 具有最强的心理测量特性。其他在该队列中具有实质性证据的工具包括 AlphaFIM、MMSE 和 Barthel 指数。其余工具的心理测量特性还需要进行深入研究,因为迄今为止对这些工具的研究还不够充分。物理治疗师可利用研究结果指导选择合适的工具来评估活动能力和预测出院去向:先验,PROSPERO(CRD 42017064209)。
Predicting Discharge Destination in Older People From Acute General Medical Wards: A Systematic Review of the Psychometric Properties of 23 Assessment Tools.
Background: Predicting discharge in older people from general medicine wards is challenging. It requires consideration of function, mobility, and cognitive levels, which vary within the cohort and may fluctuate over a short period. A previous systematic review identified 23 assessment tools associated with discharge destination in this cohort; however, the psychometric properties of these tools have not been explored.
Purpose: To evaluate, synthesize, and compare the psychometric properties of 23 assessment tools used to predict discharge destination from acute general medical wards.
Methods: Four databases were systematically searched: Medline (Ovid), Embase (Ovid), Cumulative Index of Nursing and Allied Health Literature (CINAHL), and Evidence-Based Medicine Review databases. Studies were included if participants were from general medicine or acute geriatric wards and investigated at least one psychometric property (reliability, internal consistency, measurement error, responsiveness, hypothesis testing, and structural or criterion validity) in 23 previously identified assessment tools. Data were extracted and methodological quality were assessed independently by 2 assessors using the COnsensus-based Standards for selection of health Measure INstruments (COSMIN) checklist. As per the COSMIN checklist, results were rated against "sufficient," "insufficient," or "indeterminate."
Results: Forty-one studies were included. The de Morton Mobility Index (DEMMI) was the most rigorously evaluated assessment tool; it scored "sufficient" psychometric properties in 5 of 7 psychometric categories. The Alpha Functional Independence Measure (AlphaFIM), Barthel Index, and Mini-Mental State Examination (MMSE) demonstrated "sufficient" psychometric properties in at least 3 psychometric categories. The remainder of the tools (n = 19, 83%) had "sufficient" psychometric properties in 2 or fewer psychometric categories.
Discussion and conclusion: Based on current evidence, out of 23 assessment tools associated with discharge destination in acute general medicine, the DEMMI has the strongest psychometric properties. Other tools with substantial evidence in this cohort include the AlphaFIM, MMSE, and Barthel Index. Research is required to thoroughly evaluate the psychometric properties of the remaining tools, which have been insufficiently researched to date. Results can be used by physical therapists to guide selection of appropriate tools to assess mobility and predict discharge destination.
Trial registration: A priori, PROSPERO (CRD 42017064209).
期刊介绍:
Journal of Geriatric Physical Therapy is the leading source of clinically applicable evidence for achieving optimal health, wellness, mobility, and physical function across the continuum of health status for the aging adult.
The mission of the Academy of Geriatric Physical Therapy is building a community that advances the profession of physical therapy to optimize the experience of aging.