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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
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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Conflict of Interest
All listed authors declare that we have no financial and personal relationships with other people or organizations that may inappropriately influence or bias the objectivity of submitted content and/or its acceptance for publication in this journal.
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References
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- 4 Lee WH, Packer M. Prognostic importance of serum sodium concentration and its modification by converting-enzyme inhibition in patients with severe chronic heart failure. Circulation 1986; 73 (02) 257-267.
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- 6 Hoorn EJ, Halperin ML, Zietse R. Diagnostic approach to a patient with hyponatraemia: traditional versus physiology-based options. Qjm 2005; 98 (07) 529-540.
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- 8 Malone TW CK, Herman GA. Organizing Business Knowledge: The MIT Process Handbook. ed. T. M. Press; 2003. Massachusetts, United States of America.:
- 9 Quality Control Charts.. Electronic Textbook Statsoft. 2003; Available from: www.statsoft.com/textbook/stquacon.html.
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- 11 What are control charts? SQC online. 2007 Available at: http://www.sqconline.com/six-sigma-control-charts.html 4.
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Correspondence to:
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References
- 1 10013 NI Guidelines for developing quality manuals. International Organization for Standarization. 1995 Genéve:
- 2 Goldberg J, Gelfand HM, Levy PS. Registry evaluation methods: a review and case study. Epidemiol Rev 1980; 2: 210-220.
- 3 Freda BJ, Davidson MB, Hall PM. Evaluation of hyponatremia: a little physiology goes a long way. Cleve Clin J Med 2004; 71 (08) 639-560.
- 4 Lee WH, Packer M. Prognostic importance of serum sodium concentration and its modification by converting-enzyme inhibition in patients with severe chronic heart failure. Circulation 1986; 73 (02) 257-267.
- 5 Spigset O, Hedenmalm K. Hyponatremia in relation to treatment with antidepressants: a survey of reports in the World Health Organization data base for spontaneous reporting of adverse drug reactions. Pharmacotherapy 1997; 17 (02) 348-352.
- 6 Hoorn EJ, Halperin ML, Zietse R. Diagnostic approach to a patient with hyponatraemia: traditional versus physiology-based options. Qjm 2005; 98 (07) 529-540.
- 7 ISO 10013 Guidelines for developing quality manuals. International Organization for Standarization. 1995 Genéve:
- 8 Malone TW CK, Herman GA. Organizing Business Knowledge: The MIT Process Handbook. ed. T. M. Press; 2003. Massachusetts, United States of America.:
- 9 Quality Control Charts.. Electronic Textbook Statsoft. 2003; Available from: www.statsoft.com/textbook/stquacon.html.
- 10 Amin SG. Control charts 101: a guide to health care applications. Qual Manag Health Care 2001; 9 (03) 1-27.
- 11 What are control charts? SQC online. 2007 Available at: http://www.sqconline.com/six-sigma-control-charts.html 4.
- 12 Evans JR, Lindsay WM. Administración y Control de la Calidad 1995. Mexico DF, Mexico: Grupo Editorial Iberoamérica.;
- 13 Nelson rules.. Wikipedia, the free encyclopedia. 20 February 2010; Available from: http://en.wikipedia.org/wiki/Nelson_rules.
- 14 Deming W. La salida de la crisis, in Calidad, productividad y competititvidad. 1989. Madrid.:
- 15 Streiner D, Norman G. Basic Concepts. In: Health Measurement Scales, A practical guide to development and use. Ontario, Canada: 1994: 4-13.
- 16 Saturno, Cómo diseñar una evaluación sobre la calidad asistencial en atención primaria, C.d.l. S. A.d. M. F.y. Comunitaria, Editor. Sevilla: 1992
- 17 Thor J. et al. Application of statistical process control in healthcare improvement: systematic review. Qual Saf Health Care 2007; 16 (05) 387-399.