Niznik Joshua D, Sileanu Florentia E, Zhao Xinhua, Tran Kelvin, Hanson Laura C, Kinlaw Alan, Radomski Thomas R, Ehlert Alexa, Springer Sydney, Cao Binxin, Schleiden Loren J, Thorpe Carolyn T
Division of Geriatric Medicine, University of North Carolina at Chapel Hill, School of Medicine, Chapel Hill, NC, USA; Center for Aging and Health, University of North Carolina at Chapel Hill, School of Medicine, Chapel Hill, NC, USA; Division of Pharmaceutical Outcomes and Policy, University of North Carolina at Chapel Hill, Eshelman School of Pharmacy, Chapel Hill, NC, USA; Center for Health Equity Research and Promotion, Veterans Affairs (VA) Pittsburgh Healthcare System, Pittsburgh, PA, USA.
Center for Health Equity Research and Promotion, Veterans Affairs (VA) Pittsburgh Healthcare System, Pittsburgh, PA, USA.
J Am Med Dir Assoc. 2025 Apr;26(4):105481. doi: 10.1016/j.jamda.2024.105481. Epub 2025 Feb 7.
Identifying people with possible dementia in health care systems is important to study outcomes and target improvements in care. This study sought to compare the performance of diagnostic codes and Minimum Data Set (MDS)-based measures for identifying dementia and cognitive impairment in older veteran nursing home residents.
Retrospective, cross-sectional analysis.
We used real-world health care data from the Veterans Affairs (VA) Residential History File, VA Corporate Data Warehouse (CDW), Medicare claims, and the MDS to assemble a cohort of VA Community Living Center (CLC) admissions over 2015 to 2021 for veterans aged ≥ 65 with dual VA and Medicare enrollment (n = 54,234).
We defined 3 measures of possible dementia: (1) claims/CDW diagnoses using Chronic Conditions Warehouse (CCW) algorithms for Alzheimer's disease or non-Alzheimer's dementia; (2) MDS active diagnosis items for Alzheimer's disease and non-Alzheimer's dementia; and (3) MDS Cognitive Function Scale (CFS) assessment indicating at least mild cognitive impairment. We calculated proportions identified with each definition, and sensitivity, specificity, and positive predictive value of claims/CDW diagnoses and MDS indicators for dementia for identifying CFS impairment.
Among VA CLC residents, 61.4% met at least 1 criterion for possible dementia (38.6% claims/CDW, 23.3% MDS active diagnosis, 50.8% CFS). Diagnoses from claims/CDW had 56.5% sensitivity and 80.0% specificity for identifying veterans with CFS cognitive impairment. Active diagnoses from the MDS exhibited poorer sensitivity (38.1%), but higher specificity (92.0%) identifying veterans with cognitive impairment on the CFS.
Consistent with what has been reported in Medicare nursing home residents, we observed only partial overlap between indicators of possible dementia across diagnosis codes and other indicators vs cognitive assessments in MDS. Our findings support the utility of these measures for identifying individuals with possible dementia across different systems, but further work is needed to understand implications when using diagnosis codes or cognitive assessments.
在医疗保健系统中识别可能患有痴呆症的人对于研究治疗结果和确定护理改进目标很重要。本研究旨在比较诊断代码和基于最小数据集（MDS）的措施在识别老年退伍军人疗养院居民中的痴呆症和认知障碍方面的表现。
回顾性横断面分析。
我们使用了来自退伍军人事务部（VA）居住历史档案、VA企业数据仓库（CDW）、医疗保险理赔数据和MDS的真实世界医疗保健数据，以组建一个2015年至2021年期间年龄≥65岁且同时参加VA和医疗保险的退伍军人VA社区生活中心（CLC）入院队列（n = 54,234）。
我们定义了三种可能患有痴呆症的衡量标准：（1）使用慢性病仓库（CCW）算法对阿尔茨海默病或非阿尔茨海默病痴呆症进行理赔/CDW诊断；（2）MDS中阿尔茨海默病和非阿尔茨海默病痴呆症的现行诊断项目；（3）MDS认知功能量表（CFS）评估表明至少有轻度认知障碍。我们计算了每种定义所识别出的比例，以及理赔/CDW诊断和MDS痴呆症指标在识别CFS损伤方面的敏感性、特异性和阳性预测值。
在VA CLC居民中，61.4%至少符合一项可能患有痴呆症的标准（38.6%通过理赔/CDW，23.3%通过MDS现行诊断，50.8%通过CFS）。理赔/CDW诊断在识别患有CFS认知障碍的退伍军人方面的敏感性为56.5%，特异性为80.0%。MDS的现行诊断在识别CFS上有认知障碍的退伍军人方面敏感性较差（38.1%），但特异性较高（92.0%）。
与医疗保险疗养院居民中所报告的情况一致，我们观察到诊断代码和其他指标与MDS中的认知评估之间，可能患有痴呆症的指标仅有部分重叠。我们的研究结果支持这些措施在跨不同系统识别可能患有痴呆症的个体方面的效用，但在使用诊断代码或认知评估时，还需要进一步开展工作以了解其影响。
