An Evaluation of the NQF Quality Data Model for Representing Electronic Health Record Driven Phenotyping Algorithms

作者: Peggy L. Peissig , Luke V. Rasmussen , Joshua C. Denny , Jyotishman Pathak , Abel N. Kho

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摘要: The development of Electronic Health Record (EHR)-based phenotype selection algorithms is a non-trivial and highly iterative process involving domain experts informaticians. To make it easier to port across institutions, desirable represent them using an unambiguous formal specification language. For this purpose we evaluated the recently developed National Quality Forum (NQF) information model designed for EHR-based quality measures: Data Model (QDM). We selected 9 phenotyping that had been previously as part eMERGE consortium translated into QDM format. Our study concluded contains several core elements promising format EHR-driven clinical research. However, also found areas in which could be usefully extended, such representing extracted from text, ability handle do not consist Boolean combinations criteria.

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