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Single-Center Experience Implementing the LOINC-RSNA Radiology Playbook for Adult Abdomen/Pelvis CT and MR Procedures Using a Semi-Automated Method

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Abstract

The LOINC-RSNA Radiology Playbook represents the future direction of standardization for radiology procedure names. We developed a software solution (“RadMatch”) utilizing Python 2.7 and FuzzyWuzzy, an open-source fuzzy string matching algorithm created by SeatGeek, to implement the LOINC-RSNA Radiology Playbook for adult abdomen and pelvis CT and MR procedures performed at our institution. Execution of this semi-automated method resulted in the assignment of appropriate LOINC numbers to 86% of local CT procedures. For local MR procedures, appropriate LOINC numbers were assigned to 75% of these procedures whereas 12.5% of local MR procedures could only be partially mapped. For the standardized local procedures, only 63% of CT and 71% of MR procedures had corresponding RadLex Playbook identifier (RPID) codes in the LOINC-RSNA Radiology Playbook, which limited the utility of RPID codes. RadMatch is a semi-automated open-source software tool that can assist radiology departments seeking to standardize their radiology procedures via implementation of the LOINC-RSNA Radiology Playbook.

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References

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Acknowledgements

We would like to thank SeatGeek for publishing FuzzyWuzzy as an open-source solution. We would also like to thank the creators of easygui.

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Correspondence to Ranjit S. Sandhu.

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This article does not contain any studies with human participants or animals performed by any of the authors.

Electronic supplementary material

Table 3

Complete table of CT abdomen/pelvis local procedures with RadMatch results and radiologist match selection (PDF 451 kb)

Table 4

Complete table of CT abdomen/pelvis local procedures with RadMatch results and radiologist match selection (PDF 385 kb)

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Sandhu, R.S., Shin, J., Wang, K.C. et al. Single-Center Experience Implementing the LOINC-RSNA Radiology Playbook for Adult Abdomen/Pelvis CT and MR Procedures Using a Semi-Automated Method. J Digit Imaging 31, 124–132 (2018). https://doi.org/10.1007/s10278-017-0016-0

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  • DOI: https://doi.org/10.1007/s10278-017-0016-0

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