Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, California, USA.
Geriatric Research, Education and Clinical Center, Veterans Affairs Greater Los Angeles Healthcare System, Los Angeles, California, USA.
J Gerontol A Biol Sci Med Sci. 2024 Jul 1;79(7). doi: 10.1093/gerona/glae096.
Diagnosis-code-based algorithms to identify fall injuries in Medicare data are useful for ascertaining outcomes in interventional and observational studies. However, these algorithms have not been validated against a fully external reference standard, in ICD-10-CM, or in Medicare Advantage (MA) data.
We linked self-reported fall injuries leading to medical attention (FIMA) from the Strategies to Reduce Injuries and Develop Confidence in Elders (STRIDE) trial (reference standard) to Medicare fee-for-service (FFS) and MA data from 2015-19. We measured the area under the receiver operating characteristic curve (AUC) based on sensitivity and specificity of a diagnosis-code-based algorithm against the reference standard for presence or absence of ≥1 FIMA within a specified window of dates, varying the window size to obtain points on the curve. We stratified results by source (FFS vs MA), trial arm (intervention vs control), and STRIDE's 10 participating health care systems.
Both reference standard data and Medicare data were available for 4 941 (of 5 451) participants. The reference standard and algorithm identified 2 054 and 2 067 FIMA, respectively. The algorithm had 45% sensitivity (95% confidence interval [CI]: 43%-47%) and 99% specificity (95% CI: 99%-99%) to identify reference standard FIMA within the same calendar month. The AUC was 0.79 (95% CI: 0.78-0.81) and was similar by FFS or MA data source and by trial arm but showed variation among STRIDE health care systems (AUC range by health care system, 0.71 to 0.84).
An ICD-10-CM algorithm to identify fall injuries demonstrated acceptable performance against an external reference standard, in both MA and FFS data.
基于诊断代码的算法可用于确定医疗保险数据中跌倒损伤的情况，这对于干预性和观察性研究的结果确定非常有用。然而，这些算法尚未在 ICD-10-CM 或医疗保险优势（MA）数据中与完全外部参考标准进行验证。
我们将 STRIDE 试验中自我报告的跌倒损伤导致医疗关注（FIMA）（参考标准）与 2015 年至 2019 年医疗保险费用报销（FFS）和 MA 数据进行了链接。我们基于诊断代码算法针对参考标准对特定日期窗口内是否存在≥1 次 FIMA 的敏感性和特异性计算了接收者操作特征曲线（ROC）下面积（AUC），并通过改变窗口大小来获得曲线上的点。我们按来源（FFS 与 MA）、试验组（干预与对照）和 STRIDE 的 10 个参与医疗保健系统对结果进行分层。
参考标准数据和医疗保险数据均可用于 4941 名（5451 名中的 4941 名）参与者。参考标准和算法分别确定了 2054 次和 2067 次 FIMA。该算法在同一日历月内识别参考标准 FIMA 的灵敏度为 45%（95%置信区间[CI]：43%-47%），特异性为 99%（95%CI：99%-99%）。AUC 为 0.79（95%CI：0.78-0.81），与 FFS 或 MA 数据源以及试验组均相似，但在 STRIDE 医疗保健系统之间存在差异（按医疗保健系统划分的 AUC 范围为 0.71 至 0.84）。
用于识别跌倒损伤的 ICD-10-CM 算法在 MA 和 FFS 数据中针对外部参考标准表现出可接受的性能。
