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Measuring quality in diabetes care: an expert-based statistical approach

We present a methodology for using health insurance claims data to monitor quality of care. The method uses a statistical model trained on the quality ratings of a medical expert. In a pilot study, the expert rated the quality of care received over the course of two years by 101 diabetes patients. A...

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Detalles Bibliográficos
Autores principales: Bertsimas, Dimitris, Czerwinski, David, Kane, Michael
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing AG 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3683141/
https://www.ncbi.nlm.nih.gov/pubmed/23795340
http://dx.doi.org/10.1186/2193-1801-2-226
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author Bertsimas, Dimitris
Czerwinski, David
Kane, Michael
author_facet Bertsimas, Dimitris
Czerwinski, David
Kane, Michael
author_sort Bertsimas, Dimitris
collection PubMed
description We present a methodology for using health insurance claims data to monitor quality of care. The method uses a statistical model trained on the quality ratings of a medical expert. In a pilot study, the expert rated the quality of care received over the course of two years by 101 diabetes patients. A logistic regression model accurately identified the quality of care for 86% of the patients. Because the model uses data derived from patients’ health insurance claims it can be used to monitor the care being received by a large patient population. One important use of the model is to identify potential candidates for case management, especially patients with complicated medical histories.
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spelling pubmed-36831412013-06-19 Measuring quality in diabetes care: an expert-based statistical approach Bertsimas, Dimitris Czerwinski, David Kane, Michael Springerplus Research We present a methodology for using health insurance claims data to monitor quality of care. The method uses a statistical model trained on the quality ratings of a medical expert. In a pilot study, the expert rated the quality of care received over the course of two years by 101 diabetes patients. A logistic regression model accurately identified the quality of care for 86% of the patients. Because the model uses data derived from patients’ health insurance claims it can be used to monitor the care being received by a large patient population. One important use of the model is to identify potential candidates for case management, especially patients with complicated medical histories. Springer International Publishing AG 2013-05-16 /pmc/articles/PMC3683141/ /pubmed/23795340 http://dx.doi.org/10.1186/2193-1801-2-226 Text en © Bertsimas et al.; licensee Springer. 2013 This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Bertsimas, Dimitris
Czerwinski, David
Kane, Michael
Measuring quality in diabetes care: an expert-based statistical approach
title Measuring quality in diabetes care: an expert-based statistical approach
title_full Measuring quality in diabetes care: an expert-based statistical approach
title_fullStr Measuring quality in diabetes care: an expert-based statistical approach
title_full_unstemmed Measuring quality in diabetes care: an expert-based statistical approach
title_short Measuring quality in diabetes care: an expert-based statistical approach
title_sort measuring quality in diabetes care: an expert-based statistical approach
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3683141/
https://www.ncbi.nlm.nih.gov/pubmed/23795340
http://dx.doi.org/10.1186/2193-1801-2-226
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