Slovis Benjamin H, Lowry Tina, Delman Bradley N, Beitia Anton Oscar, Kuperman Gilad, DiMaggio Charles, Shapiro Jason S
The Department of Emergency Medicine, Icahn School of Medicine at Mount Sinai, NY 10029, USA
The Department of Biomedical Informatics, Columbia University, NY 10032, USA.
J Am Med Inform Assoc. 2017 Jan;24(1):30-38. doi: 10.1093/jamia/ocw035. Epub 2016 May 13.
The purpose of this study was to measure the number of repeat computed tomography (CT) scans performed across an established health information exchange (HIE) in New York City. The long-term objective is to build an HIE-based duplicate CT alerting system to reduce potentially avoidable duplicate CTs.
This retrospective cohort analysis was based on HIE CT study records performed between March 2009 and July 2012. The number of CTs performed, the total number of patients receiving CTs, and the hospital locations where CTs were performed for each unique patient were calculated. Using a previously described process established by one of the authors, hospital-specific proprietary CT codes were mapped to the Logical Observation Identifiers Names and Codes (LOINC) standard terminology for inter-site comparison. The number of locations where there was a repeated CT performed with the same LOINC code was then calculated for each unique patient.
There were 717 231 CTs performed on 349 321 patients. Of these patients, 339 821 had all of their imaging studies performed at a single location, accounting for 668 938 CTs. Of these, 9500 patients had 48 293 CTs performed at more than one location. Of these, 6284 patients had 24 978 CTs with the same LOINC code performed at multiple locations. The median time between studies with the same LOINC code was 232 days (range of 0 to 1227); however, 1327 were performed within 7 days and 5000 within 30 days.
A small proportion (3%) of our cohort had CTs performed at more than one location, however this represents a large number of scans (48 293). A noteworthy portion of these CTs (51.7%) shared the same LOINC code and may represent potentially avoidable studies, especially those done within a short time frame. This represents an addressable issue, and future HIE-based alerts could be utilized to reduce potentially avoidable CT scans.
本研究旨在统计纽约市一个既定的健康信息交换（HIE）平台上重复进行计算机断层扫描（CT）的次数。长期目标是建立一个基于HIE的重复CT警报系统，以减少潜在可避免的重复CT检查。
这项回顾性队列分析基于2009年3月至2012年7月期间在HIE平台上的CT研究记录。计算了每个独特患者进行的CT次数、接受CT检查的患者总数以及进行CT检查的医院地点。使用其中一位作者先前描述的流程，将医院特定的专有CT代码映射到逻辑观察标识符名称和代码（LOINC）标准术语，以便进行站点间比较。然后计算每个独特患者在相同LOINC代码下重复进行CT检查的地点数量。
对349321名患者进行了717231次CT检查。在这些患者中，339821名患者的所有影像学检查均在单一地点进行，共计668938次CT检查。其中，9500名患者在多个地点进行了48293次CT检查。在这些患者中，6284名患者在多个地点进行了24978次具有相同LOINC代码的CT检查。具有相同LOINC代码的检查之间的中位时间为232天（范围为0至1227天）；然而，1327次检查在7天内进行，5000次在30天内进行。
我们队列中的一小部分（3%）患者在多个地点进行了CT检查，但这代表了大量的扫描（48293次）。这些CT检查中有相当一部分（51.7%）具有相同的LOINC代码，可能代表潜在可避免的检查，尤其是那些在短时间内进行的检查。这是一个可解决的问题，未来基于HIE的警报可用于减少潜在可避免的CT扫描。
