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Promises and pitfalls of electronic health record analysis
Routinely collected electronic health records (EHRs) are increasingly used for research. With their use comes the opportunity for large-scale, high-quality studies that can address questions not easily answered by randomised clinical trials or classical cohort studies involving bespoke data collecti...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6447497/ https://www.ncbi.nlm.nih.gov/pubmed/29247363 http://dx.doi.org/10.1007/s00125-017-4518-6 |
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author | Farmer, Ruth Mathur, Rohini Bhaskaran, Krishnan Eastwood, Sophie V. Chaturvedi, Nish Smeeth, Liam |
author_facet | Farmer, Ruth Mathur, Rohini Bhaskaran, Krishnan Eastwood, Sophie V. Chaturvedi, Nish Smeeth, Liam |
author_sort | Farmer, Ruth |
collection | PubMed |
description | Routinely collected electronic health records (EHRs) are increasingly used for research. With their use comes the opportunity for large-scale, high-quality studies that can address questions not easily answered by randomised clinical trials or classical cohort studies involving bespoke data collection. However, the use of EHRs generates challenges in terms of ensuring methodological rigour, a potential problem when studying complex chronic diseases such as diabetes. This review describes the promises and potential of EHRs in the context of diabetes research and outlines key areas for caution with examples. We consider the difficulties in identifying and classifying diabetes patients, in distinguishing between prevalent and incident cases and in dealing with the complexities of diabetes progression and treatment. We also discuss the dangers of introducing time-related biases and describe the problems of inconsistent data recording, missing data and confounding. Throughout, we provide practical recommendations for good practice in conducting EHR studies and interpreting their results. |
format | Online Article Text |
id | pubmed-6447497 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-64474972019-04-17 Promises and pitfalls of electronic health record analysis Farmer, Ruth Mathur, Rohini Bhaskaran, Krishnan Eastwood, Sophie V. Chaturvedi, Nish Smeeth, Liam Diabetologia Review Routinely collected electronic health records (EHRs) are increasingly used for research. With their use comes the opportunity for large-scale, high-quality studies that can address questions not easily answered by randomised clinical trials or classical cohort studies involving bespoke data collection. However, the use of EHRs generates challenges in terms of ensuring methodological rigour, a potential problem when studying complex chronic diseases such as diabetes. This review describes the promises and potential of EHRs in the context of diabetes research and outlines key areas for caution with examples. We consider the difficulties in identifying and classifying diabetes patients, in distinguishing between prevalent and incident cases and in dealing with the complexities of diabetes progression and treatment. We also discuss the dangers of introducing time-related biases and describe the problems of inconsistent data recording, missing data and confounding. Throughout, we provide practical recommendations for good practice in conducting EHR studies and interpreting their results. Springer Berlin Heidelberg 2017-12-15 2018 /pmc/articles/PMC6447497/ /pubmed/29247363 http://dx.doi.org/10.1007/s00125-017-4518-6 Text en © The Author(s) 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Review Farmer, Ruth Mathur, Rohini Bhaskaran, Krishnan Eastwood, Sophie V. Chaturvedi, Nish Smeeth, Liam Promises and pitfalls of electronic health record analysis |
title | Promises and pitfalls of electronic health record analysis |
title_full | Promises and pitfalls of electronic health record analysis |
title_fullStr | Promises and pitfalls of electronic health record analysis |
title_full_unstemmed | Promises and pitfalls of electronic health record analysis |
title_short | Promises and pitfalls of electronic health record analysis |
title_sort | promises and pitfalls of electronic health record analysis |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6447497/ https://www.ncbi.nlm.nih.gov/pubmed/29247363 http://dx.doi.org/10.1007/s00125-017-4518-6 |
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