Use of an ultrasound picture archiving and communication system to answer research questions : Description of data cleaning methods
© 2024 The Authors. Australasian Journal of Ultrasound in Medicine published by John Wiley & Sons Australia, Ltd on behalf of Australasian Society for Ultrasound in Medicine..
Introduction/Purpose: Ultrasound picture archiving and communication system (PACS) databases are useful for quality improvement and clinical research but frequently contain free text that is not easily readable. Here, we present a method to extract and clean a semi-structured echocardiography (cardiac ultrasound) PACS database.
Methods: Echocardiography studies between 1 January 2010 and 31 December 2018 were extracted using a data mining tool. Numeric variables were recoded with extreme values excluded. Analysis of free text, including descriptions of the heart valves and right and left ventricular size and function, was performed using a rule-based system. Different levels of free text variables were initially identified using commonly used phrases and then iteratively developed. Randomly selected sets of 100 studies were compared to the electronic health record to validate the data cleaning process.
Results: The data validation step was performed three times in total, with Cohen's kappa ranging between 0.88 and 1.00 for the final set of data validation across all measures.
Conclusion: Free text cleaning of semi-structured PACS databases is possible using freely available open-source software. The accuracy of this method is high, and the resulting dataset can be linked to administrative data to answer research questions. We present a method that could be used to answer clinical questions or to develop quality improvement initiatives.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:27 |
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| Enthalten in: |
Australasian journal of ultrasound in medicine - 27(2024), 1 vom: 19. Feb., Seite 49-55 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Moore, Matthew K [VerfasserIn] |
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| Links: |
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| Anmerkungen: |
Date Revised 05.03.2024 published: Electronic-eCollection Citation Status PubMed-not-MEDLINE |
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| doi: |
10.1002/ajum.12374 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM369244176 |
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| 520 | |a © 2024 The Authors. Australasian Journal of Ultrasound in Medicine published by John Wiley & Sons Australia, Ltd on behalf of Australasian Society for Ultrasound in Medicine. | ||
| 520 | |a Introduction/Purpose: Ultrasound picture archiving and communication system (PACS) databases are useful for quality improvement and clinical research but frequently contain free text that is not easily readable. Here, we present a method to extract and clean a semi-structured echocardiography (cardiac ultrasound) PACS database | ||
| 520 | |a Methods: Echocardiography studies between 1 January 2010 and 31 December 2018 were extracted using a data mining tool. Numeric variables were recoded with extreme values excluded. Analysis of free text, including descriptions of the heart valves and right and left ventricular size and function, was performed using a rule-based system. Different levels of free text variables were initially identified using commonly used phrases and then iteratively developed. Randomly selected sets of 100 studies were compared to the electronic health record to validate the data cleaning process | ||
| 520 | |a Results: The data validation step was performed three times in total, with Cohen's kappa ranging between 0.88 and 1.00 for the final set of data validation across all measures | ||
| 520 | |a Conclusion: Free text cleaning of semi-structured PACS databases is possible using freely available open-source software. The accuracy of this method is high, and the resulting dataset can be linked to administrative data to answer research questions. We present a method that could be used to answer clinical questions or to develop quality improvement initiatives | ||
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| 700 | 1 | |a Jones, Gregory T |e verfasserin |4 aut | |
| 700 | 1 | |a Coffey, Sean |e verfasserin |4 aut | |
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