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Improving Communication of Actionable Findings in Radiology Imaging Studies and Procedures Using an EMR-Independent System

  • Systems-Level Quality Improvement
  • Published:
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Abstract

The primary purpose of this study is to determine if the implementation of an actionable findings communication system (PeerVue) with explicitly defined criteria for the classification of critical results, leads to an increase in the number of actionable findings reported by radiologists. Secondary goals are to 1) analyze the adoption rate of PeerVue and 2) assess the accuracy of the classification of actionable findings within this system. Over a two-year period, 890,204 radiology reports were analyzed retrospectively in order to identify the number of actionable findings communicated before (Year 1) and after the implementation of PeerVue (Year 2) at a tertiary care academic medical center. A sub-sample of 145 actionable findings over a two-month period in Year 2 was further analyzed to assess the degree of concordance with our reporting policy. Before PeerVue, 4623/423,070 (1.09%) of radiology reports contained an actionable finding. After its implementation, this number increased to 6825/467,134 (1.46%) (p < 0.0001). PeerVue was used in 3886/6825 (56.9%) cases with actionable findings. The remaining 2939/6825 (43.1%) were reported using the legacy tagging system. From the sub-sample taken from PeerVue, 104/145 (71.7%) were consistent with the updated reporting policy. A software program (PeerVue) utilized for the communication of actionable findings contributed to a 34% (p < 0.0001) increase in the reporting rate of actionable findings. A sub-analysis within the new system indicated a 56.9% adoption rate and a 71.7% accuracy rate in reporting of actionable findings.

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Correspondence to Steven J. Baccei.

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This article is part of the Topical Collection on Systems-Level Quality Improvement

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Baccei, S.J., DiRoberto, C., Greene, J. et al. Improving Communication of Actionable Findings in Radiology Imaging Studies and Procedures Using an EMR-Independent System. J Med Syst 43, 30 (2019). https://doi.org/10.1007/s10916-018-1150-z

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  • DOI: https://doi.org/10.1007/s10916-018-1150-z

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