Lamers-Johnson Erin, Kelley Kathryn, Sánchez Damien M, Knippen Kerri Lynn, Nadelson Micki, Papoutsakis Constantina, Yakes Jimenez Elizabeth
J Acad Nutr Diet. 2022 Apr;122(4):862-872. doi: 10.1016/j.jand.2021.03.013. Epub 2021 Apr 23.
More evidence regarding registered dietitian nutritionist implementation of evidence-based nutrition practice guidelines (EBNPGs) is needed. We assessed the utility of an automated informatics tool to evaluate congruence of documented nutrition care with 13 individual recommendations in the diabetes mellitus (DM) EBNPG and with the guideline overall. A concurrent validation study was conducted using Nutrition Care Process Terminology documentation entered in the Academy of Nutrition and Dietetics Health Informatics Infrastructure by registered dietitian nutritionists caring for patients with DM. A 15% subset (n = 115) of the 790 patient encounters recorded were selected randomly, and the documented care was evaluated using the automated DM Expected Care Plan (ECP) Analyzer and expert audit. Recommendation-level congruence, as determined by each method, was compared using Cohen's κ analysis, and the accuracy, sensitivity, and specificity of the DM ECP Analyzer for assessing overall guideline-level congruence was calculated with expert audits as the "gold standard." For recommendation-level congruence, the DM ECP Analyzer identified more instances of recommendation implementation in the patient encounters, and classified more encounters as including partial or full recommendation implementation for 10 of the 13 recommendations, compared with the expert audit. There was slight to fair agreement between the DM ECP and the expert audit for most individual recommendations, with a mean ± standard deviation level of agreement of κ = .17 ± .19 across all eligible recommendations. At the guideline level, the DM Analyzer had high accuracy (98.3%) and sensitivity (99.1%) and low specificity (0%; no true negatives detected). The DM ECP Analyzer is acceptable for conducting automated audits of nutrition documentation to assess congruence of documented care with recommendations for evidence-based care. Future changes to the EBNPG, Nutrition Care Process Terminology, Academy of Nutrition and Dietetics Health Informatics Infrastructure, and the DM ECP Analyzer could potentially improve recommendation-level performance. The DM ECP Analyzer can be modified for other EBNPGs to facilitate automated assessment of guideline implementation.
我们需要更多关于注册营养师实施循证营养实践指南（EBNPGs）的证据。我们评估了一种自动化信息工具的效用，以评估记录的营养护理与糖尿病（DM）EBNPG中的13项个人建议以及整个指南的一致性。使用注册营养师在营养与饮食学会健康信息基础设施中输入的营养护理过程术语文档，对患有DM的患者进行了一项同步验证研究。从记录的790次患者会诊中随机选择15%的子集（n = 115），并使用自动化的DM预期护理计划（ECP）分析器和专家审核对记录的护理进行评估。使用科恩κ分析比较每种方法确定的推荐水平一致性，并以专家审核为“金标准”计算DM ECP分析器评估总体指南水平一致性的准确性、敏感性和特异性。对于推荐水平一致性，与专家审核相比，DM ECP分析器在患者会诊中识别出更多推荐实施的实例，并且在13项推荐中的10项中，将更多会诊分类为包括部分或全部推荐实施。对于大多数个人推荐，DM ECP与专家审核之间的一致性为轻微到中等，所有符合条件的推荐的κ一致性均值±标准差水平为κ = 0.17±0.19。在指南层面，DM分析器具有高准确性（98.3%）和敏感性（99.1%）以及低特异性（0%；未检测到真正的阴性）。DM ECP分析器可用于对营养文档进行自动化审核，以评估记录的护理与循证护理推荐的一致性。EBNPG、营养护理过程术语、营养与饮食学会健康信息基础设施以及DM ECP分析器的未来变化可能会提高推荐水平的性能。DM ECP分析器可以针对其他EBNPG进行修改，以促进对指南实施的自动化评估。
