PT  - JOURNAL ARTICLE
AU  - Attila Forgacs
AU  - Ferenc Nagy
AU  - Aron Krizsan
AU  - Laszlo Balkay
AU  - Sandor Barna
AU  - Zsolt Hascsi
AU  - Ildiko Garai
TI  - Protocol Compliance and Error Detection: a software tool to monitor workflow of Nuclear Medicine Departments
DP  - 2020 May 01
TA  - Journal of Nuclear Medicine
PG  - 1403--1403
VI  - 61
IP  - supplement 1
4099  - http://jnm.snmjournals.org/content/61/supplement_1/1403.short
4100  - http://jnm.snmjournals.org/content/61/supplement_1/1403.full
SO  - J Nucl Med2020 May 01; 61
AB  - 1403Introduction: Standard Operation Protocols (SOPs) comprise essential information (i.e. patient preparation, scanning parameters) and clear instructions for the technologists regarding to specific imaging procedures. Continuous protocol management is responsible for the maintenance the up-to-date content of SOPs. Our aim was to develop a software tool (called Q-Bot) and introduce in the clinical routine, which is capable to monitor the clinical workflow, in the aspects of patient related (e.g. Patient Id, BMI etc.) and scan related parameters (e.g. the uptake time, injected activity, CT parameters, etc.) defined in the SOPs. Materials and Methods: One of the most essential components of the Q-Bot is a database consisting of DICOM header information of patient scans performed on three PET/CT systems (GE Ltd., Philips Ltd., Mediso Ltd.) and on three SPECT systems (Mediso Ltd.). The accumulated DICOM headers include information related to the patient, the imaging system, and the acquired data set. The second essential component of Q-Bot is the digitalized SOP including acceptance limits (e.g. required injected activity with a percentage range). The third component of the Q-Bot is the graphical user interface (GUI) designed for the technologist, which displays the outliers as a result of the alteration between observed clinical data and the reference values in the digitalized SOP. Results: The first version of Q-Bot was introduced in our clinical routine in 3. January. 2019. More than 10000 18F-FDG PET/CT examinations and over 4000 99mTc-MDP SPECT bone examinations in total were evaluated on a daily basis since the installation. Approximately 4% of all cases showed outliers compared to the standardized protocols. Typo errors (i.e. patient ID, weight, height, injected activity) were found in most cases and corrected continuously prior to the medical reading and reporting. Based on the relative frequency of occurrence, several high risk points were identified in the workflow: the inaccuracy of manual radiopharmaceutical injection, as well as the deceptive parallel used units (e.g. MBq versus mCi). Discussion: Q-Bot showed significant improvement in quality assurance (QA) at two of our imaging departments as an automatic monitoring software. This included the early detection of alterations from the SOPs, typo error corrections before medical reading, and caution for risk points for error prevention. The Q-Bot minimized the error propagation, made significant data cleaning, and consequently improved data confidence for the physicians.