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A novel method to create realistic synthetic medication data
OBJECTIVE: Synthea is a synthetic patient generator that creates synthetic medical records, including medication profiles. Prior to our work, Synthea produced unrealistic medication data that did not accurately reflect prescribing patterns. This project aimed to create an open-source synthetic medic...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10343944/ https://www.ncbi.nlm.nih.gov/pubmed/37457749 http://dx.doi.org/10.1093/jamiaopen/ooad052 |
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author | Hodges, Robert Tokunaga, Kristen LeGrand, Joseph |
author_facet | Hodges, Robert Tokunaga, Kristen LeGrand, Joseph |
author_sort | Hodges, Robert |
collection | PubMed |
description | OBJECTIVE: Synthea is a synthetic patient generator that creates synthetic medical records, including medication profiles. Prior to our work, Synthea produced unrealistic medication data that did not accurately reflect prescribing patterns. This project aimed to create an open-source synthetic medication database that could integrate with Synthea to create realistic patient medication profiles. MATERIALS AND METHODS: The Medication Diversification Tool (MDT) created from this study combines publicly available prescription data from the Medical Expenditure Panel Survey (MEPS) and standard medication terminology/classifications from RxNorm/RxClass to produce machine-readable information about medication use in the United States. RESULTS: The MDT was validated using a chi-square goodness-of-fit test by comparing medication distributions from Synthea, Synthea+MDT, and the MEPS. Using a pediatric asthma population, results show that Synthea+MDT had no statistical difference compared to the real-world MEPS with a P value = .84. DISCUSSION: The MDT is designed to generate realistic medication distributions for drugs and populations. This tool can be used to enhance medication records generated by Synthea by calculating medication-use data at a national level or specific to patient subpopulations. MDT’s contributions to synthetic data may enable the acceleration of application development, access to more realistic healthcare datasets for education, and patient-centered outcomes’ research. CONCLUSIONS: The MDT, when used with Synthea, provides a free and open-source method for making synthetic patient medication profiles that mimic the real world. |
format | Online Article Text |
id | pubmed-10343944 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-103439442023-07-14 A novel method to create realistic synthetic medication data Hodges, Robert Tokunaga, Kristen LeGrand, Joseph JAMIA Open Research and Applications OBJECTIVE: Synthea is a synthetic patient generator that creates synthetic medical records, including medication profiles. Prior to our work, Synthea produced unrealistic medication data that did not accurately reflect prescribing patterns. This project aimed to create an open-source synthetic medication database that could integrate with Synthea to create realistic patient medication profiles. MATERIALS AND METHODS: The Medication Diversification Tool (MDT) created from this study combines publicly available prescription data from the Medical Expenditure Panel Survey (MEPS) and standard medication terminology/classifications from RxNorm/RxClass to produce machine-readable information about medication use in the United States. RESULTS: The MDT was validated using a chi-square goodness-of-fit test by comparing medication distributions from Synthea, Synthea+MDT, and the MEPS. Using a pediatric asthma population, results show that Synthea+MDT had no statistical difference compared to the real-world MEPS with a P value = .84. DISCUSSION: The MDT is designed to generate realistic medication distributions for drugs and populations. This tool can be used to enhance medication records generated by Synthea by calculating medication-use data at a national level or specific to patient subpopulations. MDT’s contributions to synthetic data may enable the acceleration of application development, access to more realistic healthcare datasets for education, and patient-centered outcomes’ research. CONCLUSIONS: The MDT, when used with Synthea, provides a free and open-source method for making synthetic patient medication profiles that mimic the real world. Oxford University Press 2023-07-13 /pmc/articles/PMC10343944/ /pubmed/37457749 http://dx.doi.org/10.1093/jamiaopen/ooad052 Text en © The Author(s) 2023. Published by Oxford University Press on behalf of the American Medical Informatics Association. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Research and Applications Hodges, Robert Tokunaga, Kristen LeGrand, Joseph A novel method to create realistic synthetic medication data |
title | A novel method to create realistic synthetic medication data |
title_full | A novel method to create realistic synthetic medication data |
title_fullStr | A novel method to create realistic synthetic medication data |
title_full_unstemmed | A novel method to create realistic synthetic medication data |
title_short | A novel method to create realistic synthetic medication data |
title_sort | novel method to create realistic synthetic medication data |
topic | Research and Applications |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10343944/ https://www.ncbi.nlm.nih.gov/pubmed/37457749 http://dx.doi.org/10.1093/jamiaopen/ooad052 |
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