A method for interoperable knowledge-based data quality assessment.

BACKGROUND: Assessing the quality of healthcare data is a complex task including the selection of suitable measurement methods (MM) and adequately assessing their results.
OBJECTIVES: To present an interoperable data quality (DQ) assessment method that formalizes MMs based on standardized data definitions and intends to support collaborative governance of DQ-assessment knowledge, e.g. which MMs to apply and how to assess their results in different situations.
METHODS: We describe and explain central concepts of our method using the example of its first real world application in a study on predictive biomarkers for rejection and other injuries of kidney transplants. We applied our open source tool-openCQA-that implements our method utilizing the openEHR specifications. Means to support collaborative governance of DQ-assessment knowledge are the version-control system git and openEHR clinical information models.
RESULTS: Applying the method on the study's dataset showed satisfactory practicability of the described concepts and produced useful results for DQ-assessment.
CONCLUSIONS: The main contribution of our work is to provide applicable concepts and a tested exemplary open source implementation for interoperable and knowledge-based DQ-assessment in healthcare that considers the need for flexible task and domain specific requirements.