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Application program to detect unrecognized information regarding malignant tumors in radiology reports

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Abstract

Purpose

Accurate disease diagnosis from radiology reports is important in medical treatment. Preventing physicians from overlooking the findings of relevant radiology reports is thus an important global issue. This study is part of a project that aims to develop and verify a program that detects and notifies physicians of diagnoses that do not appear in the patient’s medical records.

Methods

In this study, we developed software functions that (1) extract diagnoses from radiology reports, (2) search medical records for the extracted diagnoses and output them and their corresponding ICD10 codes, which do not appear in the patients’ medical records, and (3) automatically execute all processes daily and notify auditors by email. We verified seven cases including diagnoses suspected of being overlooked that are automatically extracted by our system from 1,194 radiology reports.

Results

By checking the output obtained from the system constructed by incorporating a high-performance sentence classifier for disease name polarity classification with AUC = 0.972, it was possible to extract disease names that physicians might have overlooked. We could extract a past actual overlooked case by this algorithm. From verifying seven cases, we assessed that the physician might not have considered one diagnosis in one case.

Conclusion

These results demonstrate that the developed system is useful when auditors check patients’ medical records to confirm the status of overlooked reports and diagnoses. In future work, we will develop additional functions and tools for incorporation into the proposed system to facilitate its application in clinical practice.

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Authors and Affiliations

  1. Department of Healthcare Information Systems, The University of Tokyo Hospital, Tokyo, Japan

    Shinichiroh Yokota, Shunsuke Doi, Satomi Nagashima & Kazuhiko Ohe

  2. Department of Biomedical Informatics, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan

    Masakazu Fukuhara, Tomohiro Mitani & Kazuhiko Ohe

  3. Department of Radiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan

    Wataru Gonoi

  4. Center for Disease Biology and Integrative Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan

    Takeshi Imai

Authors
  1. Shinichiroh Yokota
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  2. Shunsuke Doi
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  3. Masakazu Fukuhara
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  4. Tomohiro Mitani
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  5. Satomi Nagashima
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  6. Wataru Gonoi
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  7. Takeshi Imai
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  8. Kazuhiko Ohe
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Contributions

All authors contributed to the study conception, design and analysis. Data collection, system development were performed by Shinichiroh Yokota. The first draft of the manuscript was written by Shinichiroh Yokota and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Shinichiroh Yokota.

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Ethics approval

This research was conducted with the approval of the Graduate School of Medicine/Faculty of Medicine Ethics Committee in our university (2018159NI).

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Yokota, S., Doi, S., Fukuhara, M. et al. Application program to detect unrecognized information regarding malignant tumors in radiology reports. Health Technol. 13, 65–73 (2023). https://doi.org/10.1007/s12553-022-00724-0

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  • DOI: https://doi.org/10.1007/s12553-022-00724-0

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