Zhang Tingting, McCreedy Ellen, Dionne Laura, Conard Ryan, Mor Vincent
Center for Gerontology & Healthcare Research, Brown University School of Public Health, Providence, RI, USA; Department of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, RI, USA; Center for Long-Term Care Quality & Innovation, Brown University School of Public Health, Providence, RI, USA.
Center for Gerontology & Healthcare Research, Brown University School of Public Health, Providence, RI, USA; Department of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, RI, USA; Center for Long-Term Care Quality & Innovation, Brown University School of Public Health, Providence, RI, USA.
J Am Med Dir Assoc. 2024 Apr;25(4):606-609.e1. doi: 10.1016/j.jamda.2023.07.005. Epub 2023 Aug 10.
Nursing home (NH) Minimum Data Set (MDS) have frequently been used to measure medication use in epidemiologic studies, but there is little evidence on the accuracy of MDS-based medication records. We compared antipsychotic use estimated using 2 data sources-MDS and NH electronic medication administration records (eMAR).
Cross-sectional comparison.
This analysis was based on MDS and linked eMAR data of 604 NH residents with dementia at 54 NHs in 10 states, participating in a cluster-randomized pragmatic trial (METRIcAL), from June 2019 to February 2020.
One admission, quarterly, or annual MDS assessment was chosen for each participant. The MDS assessment recorded the number of antipsychotic treatment days during a 7-day window. We then identified antipsychotic administrations during the corresponding window in the eMAR. We used Cohen kappa to assess agreement in the proportion of participants on antipsychotics during the week and used intraclass correlation coefficient (ICC) to assess the agreement of treatment days. We further used the eMAR data as a reference to calculate validity parameters.
A total of 29.5% of study participants were identified as antipsychotic users based on the MDS vs 28.3% based on the eMAR data (kappa value: 0.96). MDS-based average treatment duration was estimated to be 2.0, consistent with eMAR-based estimate (1.8 days, ICC: 0.96). The sensitivity was 98.8% (95% CI 95.8%-99.9%), the specificity was 97.9% (95% CI 96.1%-99.1%), the positive predictive value was 94.9% (95% CI 90.8%-97.3%), and the negative predictive value was 99.5% (95% CI 98.2%-99.9%).
Agreement between the MDS and eMAR in antipsychotic use is high, suggesting that the MDS is a valid tool to measure antipsychotic use in epidemiologic studies. Further studies with large and diverse populations are warranted to confirm our findings.
疗养院（NH）最小数据集（MDS）在流行病学研究中经常被用于衡量药物使用情况，但基于MDS的用药记录准确性的证据很少。我们比较了使用两种数据源——MDS和NH电子用药管理记录（eMAR）——估算的抗精神病药物使用情况。
横断面比较。
本分析基于2019年6月至2020年2月期间参与一项整群随机实用试验（METRIcAL）的10个州54家NH中604名患有痴呆症的NH居民的MDS以及关联的eMAR数据。
为每位参与者选择一次入院、季度或年度MDS评估。MDS评估记录了7天窗口期内抗精神病药物治疗天数。然后我们在eMAR中确定相应窗口期内的抗精神病药物给药情况。我们使用科恩kappa系数评估一周内使用抗精神病药物的参与者比例的一致性，并使用组内相关系数（ICC）评估治疗天数的一致性。我们进一步以eMAR数据为参考计算有效性参数。
基于MDS，共有29.5%的研究参与者被确定为抗精神病药物使用者，而基于eMAR数据这一比例为28.3%（kappa值：0.96）。基于MDS的平均治疗持续时间估计为2.0天，与基于eMAR的估计值（1.8天，ICC：0.96）一致。灵敏度为98.8%（95%置信区间95.8%-99.9%），特异度为97.9%（95%置信区间96.1%-99.1%），阳性预测值为94.9%（95%置信区间90.8%-97.3%），阴性预测值为99.5%（95%置信区间98.2%-99.9%）。
MDS和eMAR在抗精神病药物使用方面的一致性很高，表明MDS是流行病学研究中衡量抗精神病药物使用的有效工具。有必要开展针对大量不同人群的进一步研究以证实我们的发现。
