How to make clinical data actionable: an example of radiology quality management and peer-review system

7 pages•Published: June 4, 2018

Sergey Morozov, Ekaterina Guseva and Dmitry Safronov

Abstract

Today medical data analysis is experiencing rapid development. Large volumes of uniform and verified data are required for the application of innovative analysis solutions. This ideology was the foundation for Unified Radiological Information Service (URIS), launched in Moscow. Currently, 75 clinics are connected to the URIS. In 2016 we developed remote quality assurance system and discrepancy detection module (DDM). The software is designed to review studies, provide feedback and accumulate “big data”. We have compared the number of discrepancies before and after DDM implementation (4473 anonymized CT and MRI studies). In 12 months the number of discrepancies decreased by more than a half.

Keyphrases: information, radiological, service

In: Oleg S. Pianykh, Alexey Neznanov, Sergei Kuznetsov, Jaume Baixeries and Svetla Boytcheva (editors). WDAM-2017. Workshop on Data Analysis in Medicine, vol 6, pages 12-18.

Links:	https://easychair.org/publications/paper/vDJb
	https://doi.org/10.29007/5vjs

BibTeX entry

@inproceedings{WDAM-2017:How_make_clinical_data,
  author    = {Sergey Morozov and Ekaterina Guseva and Dmitry Safronov},
  title     = {How to make clinical data actionable: an example of radiology quality management and peer-review system},
  booktitle = {WDAM-2017. Workshop on Data Analysis in Medicine},
  editor    = {Oleg S. Pianykh and Alexey Neznanov and Sergei Kuznetsov and Jaume Baixeries and Svetla Boytcheva},
  series    = {Kalpa Publications in Computing},
  volume    = {6},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2515-1762},
  url       = {/publications/paper/vDJb},
  doi       = {10.29007/5vjs},
  pages     = {12-18},
  year      = {2018}}

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