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Development of a clinical decision support system for diabetes care: A pilot study

Management of complex chronic diseases such as diabetes requires the assimilation and interpretation of multiple laboratory test results. Traditional electronic health records tend to display laboratory results in a piecemeal and segregated fashion. This makes the assembly and interpretation of resu...

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Autores principales: Sim, Livvi Li Wei, Ban, Kenneth Hon Kim, Tan, Tin Wee, Sethi, Sunil Kumar, Loh, Tze Ping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5325565/
https://www.ncbi.nlm.nih.gov/pubmed/28235017
http://dx.doi.org/10.1371/journal.pone.0173021
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author Sim, Livvi Li Wei
Ban, Kenneth Hon Kim
Tan, Tin Wee
Sethi, Sunil Kumar
Loh, Tze Ping
author_facet Sim, Livvi Li Wei
Ban, Kenneth Hon Kim
Tan, Tin Wee
Sethi, Sunil Kumar
Loh, Tze Ping
author_sort Sim, Livvi Li Wei
collection PubMed
description Management of complex chronic diseases such as diabetes requires the assimilation and interpretation of multiple laboratory test results. Traditional electronic health records tend to display laboratory results in a piecemeal and segregated fashion. This makes the assembly and interpretation of results related to diabetes care challenging. We developed a diabetes-specific clinical decision support system (Diabetes Dashboard) interface for displaying glycemic, lipid and renal function results, in an integrated form with decision support capabilities, based on local clinical practice guidelines. The clinical decision support system included a dashboard feature that graphically summarized all relevant laboratory results and displayed them in a color-coded system that allowed quick interpretation of the metabolic control of the patients. An alert module informs the user of tests that are due for repeat testing. An interactive graph module was also developed for better visual appreciation of the trends of the laboratory results of the patient. In a pilot study involving case scenarios administered via an electronic questionnaire, the Diabetes Dashboard, compared to the existing laboratory reporting interface, significantly improved the identification of abnormal laboratory results, of the long-term trend of the laboratory tests and of tests due for repeat testing. However, the Diabetes Dashboard did not significantly improve the identification of patients requiring treatment adjustment or the amount of time spent on each case scenario. In conclusion, we have developed and shown that the use of the Diabetes Dashboard, which incorporates several decision support features, can improve the management of diabetes. It is anticipated that this dashboard will be most helpful when deployed in an outpatient setting, where physicians can quickly make clinical decisions based on summarized information and be alerted to pertinent areas of care that require additional attention.
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spelling pubmed-53255652017-03-09 Development of a clinical decision support system for diabetes care: A pilot study Sim, Livvi Li Wei Ban, Kenneth Hon Kim Tan, Tin Wee Sethi, Sunil Kumar Loh, Tze Ping PLoS One Research Article Management of complex chronic diseases such as diabetes requires the assimilation and interpretation of multiple laboratory test results. Traditional electronic health records tend to display laboratory results in a piecemeal and segregated fashion. This makes the assembly and interpretation of results related to diabetes care challenging. We developed a diabetes-specific clinical decision support system (Diabetes Dashboard) interface for displaying glycemic, lipid and renal function results, in an integrated form with decision support capabilities, based on local clinical practice guidelines. The clinical decision support system included a dashboard feature that graphically summarized all relevant laboratory results and displayed them in a color-coded system that allowed quick interpretation of the metabolic control of the patients. An alert module informs the user of tests that are due for repeat testing. An interactive graph module was also developed for better visual appreciation of the trends of the laboratory results of the patient. In a pilot study involving case scenarios administered via an electronic questionnaire, the Diabetes Dashboard, compared to the existing laboratory reporting interface, significantly improved the identification of abnormal laboratory results, of the long-term trend of the laboratory tests and of tests due for repeat testing. However, the Diabetes Dashboard did not significantly improve the identification of patients requiring treatment adjustment or the amount of time spent on each case scenario. In conclusion, we have developed and shown that the use of the Diabetes Dashboard, which incorporates several decision support features, can improve the management of diabetes. It is anticipated that this dashboard will be most helpful when deployed in an outpatient setting, where physicians can quickly make clinical decisions based on summarized information and be alerted to pertinent areas of care that require additional attention. Public Library of Science 2017-02-24 /pmc/articles/PMC5325565/ /pubmed/28235017 http://dx.doi.org/10.1371/journal.pone.0173021 Text en © 2017 Sim et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Sim, Livvi Li Wei
Ban, Kenneth Hon Kim
Tan, Tin Wee
Sethi, Sunil Kumar
Loh, Tze Ping
Development of a clinical decision support system for diabetes care: A pilot study
title Development of a clinical decision support system for diabetes care: A pilot study
title_full Development of a clinical decision support system for diabetes care: A pilot study
title_fullStr Development of a clinical decision support system for diabetes care: A pilot study
title_full_unstemmed Development of a clinical decision support system for diabetes care: A pilot study
title_short Development of a clinical decision support system for diabetes care: A pilot study
title_sort development of a clinical decision support system for diabetes care: a pilot study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5325565/
https://www.ncbi.nlm.nih.gov/pubmed/28235017
http://dx.doi.org/10.1371/journal.pone.0173021
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