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Efficiency of a semiautomated coding and review process for notification of critical findings in diagnostic imaging
Authors:Choksi Vaishali R  Marn Charles S  Bell Yvonne  Carlos Ruth
Institution:Department of Veterans Affairs, Ann Arbor VA Healthcare System, Ann Arbor, MI 48109, USA. vrchoksi@umich.edu
Abstract:OBJECTIVE: When a significant unexpected finding such as malignancy is noted on a study, the standard of care generally holds that the radiologist communicate the findings to the referring physician and document the communication in the radiology report. Despite this standard, for a variety of reasons it remains possible that the direct care provider might receive such notification but not initiate an appropriate workup. On the basis of prior root cause analysis, we developed and instituted a semiautomated process for notification of critical diagnostic imaging findings. We now report our 12-month experience with the process. MATERIALS AND METHODS: A diagnostic code was attached to every radiology report. When a significant unexpected finding occurred, our radiologists, in addition to contacting the appropriate clinician, gave the report the designation code 8. On a weekly basis, a list of code 8 cases was passed to the cancer registrar at our institution, who tracked the cases to ensure that they were appropriately followed up. RESULTS: In the 12-month period after initiation of this system, we performed 37,736 radiologic examinations at our institute. Of these, 395 cases were given code 8. All code 8 cases were followed up by the tumor registrar. In 35 cases, no workup was documented after 2 weeks. Of these, eight cases would have been completely lost to follow-up if this safety net had not been in place. CONCLUSION: Failures of communication, documentation errors, and various system failures may lead to an untoward outcome for the patient. We devised a simple system to ensure that significant unexpected findings on imaging received appropriate attention. An additional level of redundancy has increased the probability of optimal patient outcome.
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