返回
Developing a data element repository to support EHR-driven phenotype algorithm authoring and execution
DOI:10.1016/j.jbi.2016.07.008.png)
摘要
En 中文
The Quality Data Model (QDM) is an information model developed by the National Quality Forum for representing electronic health record (EHR)-based electronic clinical quality measures (eCQMs). In conjunction with the HL7 Health Quality Measures Format (HQMF), QDM contains core elements that make it a promising model for representing EHR-driven phenotype algorithms for clinical research. However, the current QDM specification is available only as descriptive documents suitable for human readability and interpretation, but not for machine consumption. The objective of the present study is to develop and evaluate a data element repository (DER) for providing machine-readable QDM data element service APIs to support phenotype algorithm authoring and execution. We used the ISO/IEC 11179 metadata standard to capture the structure for each data element, and leverage Semantic Web technologies to facilitate semantic representation of these metadata. We observed there are a number of underspecified areas in the QDM, including the lack of model constraints and pre-defined value sets. We propose a harmonization with the models developed in HL7 Fast Healthcare Interoperability Resources (FHIR) and Clinical Information Modeling Initiatives (CIMI) to enhance the QDM specification and enable the extensibility and better coverage of the DER. We also compared the DER with the existing QDM implementation utilized within the Measure Authoring Tool (MAT) to demonstrate the scalability and extensibility of our DER-based approach. (C) 2016 Elsevier Inc. All rights reserved.
Keyword:
Quality Data Model (QDM)
HL7 Fast Healthcare Interoperability Resources (FHIR)
Metadata standards
Semantic Web technology
Phenotype algorithms
AI总结
对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
4.5
论文数:
3.5K
被引数:
1.9W
机构
引用论文
Bispectral index monitoring of the clinical effects of propofol closed-loop target-controlled infusion
Medicine
IF0
The Electronic Medical Records and Genomics (eMERGE) Network: past, present, and future电子病历和基因组学 (eMERGE) 网络: 过去,现在和未来
GENETICS IN MEDICINE
IF6.2

