Formalization and computation of quality measures based on electronic medical records
Formalization and computation of quality measures based on electronic medical records
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DOI：
10.1136/amiajnl-2013-001921
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发表时间：
2014-03-01
影响因子：
6.4
通讯作者：
de Keizer, Nicolette F.
中科院分区：
文献类型：
--
作者：
Dentler, Kathrin;Numans, Mattijs E.;de Keizer, Nicolette F.
目的自然语言中质量度量的模糊定义阻碍了它们的自动可计算性，也阻碍了计算结果的再现性、有效性、及时性、可追溯性、可比性和可解释性。因此，质量度量应该在发布之前正式确定。我们之前已经开发并成功应用了临床指标形式化（CLIF）方法。我们当前研究的目的是测试CLIF是否具有普遍性，即适用于不同类型和不同领域的大量异质测量。材料和方法我们正式制定了一整套159项荷兰一般实践质量措施，其中包括结构、过程和结果措施，涵盖七个领域。我们依靠一个基于网络的工具来促进我们方法的应用。随后，我们根据真实患者数据的大型数据库计算了度量。结果我们的CLIF方法使我们能够完全形式化100%的措施。由于缺少功能，附带的工具只能将86%的质量度量完全形式化为结构化查询语言（Structured Query Language， SQL）查询。其余14%的度量需要通过将各自的标准直接转换为SQL来手动应用我们的CLIF方法。计算所得的结果与另外两方独立计算的结果有很强的相关性。结论CLIF方法经进一步扩展后，涵盖了所有质量指标。我们的web工具需要进一步改进，以便完全自动应用CLIF。因此，我们得出结论，CLIF具有足够的普遍性，能够将一整套荷兰质量措施正式化。
Objective Ambiguous definitions of quality measures in natural language impede their automated computability and also the reproducibility, validity, timeliness, traceability, comparability, and interpretability of computed results. Therefore, quality measures should be formalized before their release. We have previously developed and successfully applied a method for clinical indicator formalization (CLIF). The objective of our present study is to test whether CLIF is generalizablethat is, applicable to a large set of heterogeneous measures of different types and from various domains.Materials and methods We formalized the entire set of 159 Dutch quality measures for general practice, which contains structure, process, and outcome measures and covers seven domains. We relied on a web-based tool to facilitate the application of our method. Subsequently, we computed the measures on the basis of a large database of real patient data.Results Our CLIF method enabled us to fully formalize 100% of the measures. Owing to missing functionality, the accompanying tool could support full formalization of only 86% of the quality measures into Structured Query Language (SQL) queries. The remaining 14% of the measures required manual application of our CLIF method by directly translating the respective criteria into SQL. The results obtained by computing the measures show a strong correlation with results computed independently by two other parties.Conclusions The CLIF method covers all quality measures after having been extended by an additional step. Our web tool requires further refinement for CLIF to be applied completely automatically. We therefore conclude that CLIF is sufficiently generalizable to be able to formalize the entire set of Dutch quality measures for general practice.