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DOI: 10.4338/ACI-2010-07-RA-0040
Creation of a Hyponatremia Registry Supported by an Industry-Derived Quality Control Methodology
Publication History
received:
02 July 2010
accepted:
07 February 2011
Publication Date:
16 December 2017 (online)
![](https://www.thieme-connect.de/media/10.1055-s-00035026/201101/lookinside/thumbnails/10-4338-aci-2010-07-ra-0040-1.jpg)
Summary
Background: A clinical registry encompasses a selective set of rigorously collected and stored clinical data focused on a specific condition. Hyponatremia has multiple, complex underlying causes and is one of the most frequent laboratory abnormalities. No systematic registries of hyponatremic patients have been reported in the medical literature. The purpose of this project was to create a registry for hyponatremia in order to obtain epidemiological data that will help to better understand this condition.
Objective: This paper describes the creation of a registry for hyponatremia within a single institution that employs industry-based approaches for quality management to optimize data accuracy and completeness.
Methods: A prospective registry of incident hyponatremia cases was created for this study. A formalized statistically based quality control methodology was developed and implemented to analyze and monitor all the process indicators that were developed to ensure data quality.
Results: Between December 2006 and April 2009, 2443 episodes of hyponatremia were included. Six process indicators that reflect the integrity of the system were evaluated monthly, looking for variation that would suggest systematic problems. The graphical representation of the process measures through control charts allowed us to identify and subsequently address problems with maintaining the registry.
Conclusion: In this project we have created a novel hyponatremia registry. To ensure the quality of the data in this registry we have implemented a quality control methodology based on industrial principles that allows us to monitor the performance of the registry over time through process indicators in order to detect systematic problems. We postulate that this approach could be reproduced for other registries.
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