Bery Anand K, Anzaldi Laura J, Boyd Cynthia M, Leff Bruce, Kharrazi Hadi
Division of Neurology, Department of Medicine, The Ottawa Hospital, 1053 Carling Avenue, Ottawa, ON, K1Y 4E9, Canada; Center for Population Health IT, Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, 624 N Broadway, Baltimore, MD, 21205, United States.
Center for Population Health IT, Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, 624 N Broadway, Baltimore, MD, 21205, United States.
Arch Gerontol Geriatr. 2020 Nov/Dec;91:104224. doi: 10.1016/j.archger.2020.104224. Epub 2020 Aug 12.
Despite the availability of many frailty measures to identify older adults at risk, frailty instruments are not routinely used for risk assessment in population health management. Here, we assessed the potential value of electronic health records (EHRs) and administrative claims in providing the necessary data for variables used across various frailty instruments.
The review focused on studies conducted worldwide. Participants included older people aged 50 and older.
We identified frailty instruments published between 2011 and 2018. Frailty variables used in each of the frailty instruments were extracted, grouped, and categorized across health determinants and various clinical factors.
The availability of the extracted frailty variables across various data sources (e.g., EHRs, administrative claims, and surveys) was evaluated by experts.
We identified 135 frailty instruments, which contained 593 unique variables. Clinical determinants of health were the best represented variables across frailty instruments (n = 516; 87 %), unlike social and health services factors (n = 33; ∼5% and n = 32; ∼5%). Most frailty instruments require at least one variable that is not routinely available in EHRs or claims (n = 113; ∼83 %). Only 22 frailty instruments have the potential to completely rely on EHR (structured or free-text data) and/or claims data, and possibly be operationalized on a population-level.
Frailty instruments continue to be highly survey-based. More research is therefore needed to develop EHR-based frailty instruments for population health management. This will permit organizations and societies to stratify risk and better allocate resources among different older adult populations.
尽管有许多衰弱测量方法可用于识别有风险的老年人，但衰弱评估工具在人群健康管理中并未常规用于风险评估。在此，我们评估了电子健康记录（EHR）和行政索赔在为各种衰弱评估工具中使用的变量提供必要数据方面的潜在价值。
该综述聚焦于全球范围内开展的研究。参与者包括50岁及以上的老年人。
我们识别了2011年至2018年间发表的衰弱评估工具。提取了每个衰弱评估工具中使用的衰弱变量，并根据健康决定因素和各种临床因素进行分组和分类。
由专家评估提取的衰弱变量在各种数据源（如电子健康记录、行政索赔和调查）中的可得性。
我们识别了135种衰弱评估工具，其中包含593个独特变量。健康的临床决定因素是衰弱评估工具中代表性最好的变量（n = 516；87%），而社会和健康服务因素则不然（n = 33；约5%和n = 32；约5%）。大多数衰弱评估工具至少需要一个在电子健康记录或索赔中不常有的变量（n = 113；约83%）。只有22种衰弱评估工具有可能完全依赖电子健康记录（结构化或自由文本数据）和/或索赔数据，并可能在人群层面实施。
衰弱评估工具仍然高度依赖调查。因此，需要更多研究来开发基于电子健康记录的用于人群健康管理的衰弱评估工具。这将使组织和社会能够对风险进行分层，并在不同老年人群体中更好地分配资源。
