A method for interoperable knowledge-based data quality assessment

Abstract

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.