Implementation of an Automated Radiation Oncology Prescription Checking System, Revealing a Baseline Prescription Error Rate of at Least 0.2%

Abstract

<h3>Purpose/Objective(s)</h3> Radiation dose prescriptions serve as the radiation oncologist's (RO) treatment intent, containing vital information such as treatment technique, total dose, dose per fraction, and number of fractions. Despite serving as a critical communication tool, prescriptions are entered manually and prone to various forms of error. Human systems and traditional safety checks may not catch these, due to assumption of RO intent and deference to ROs. This can lead to significant wasted treatment planning resources and, if not ultimately caught, can lead to misadministration. In response to the potential for erroneous prescription entry, an automated prescription checking system was designed and implemented. <h3>Materials/Methods</h3> Rules defining clinically appropriate prescriptions were generated, examining specific types of errors: 1) Approved dose per fraction. This was based on review of 14,487 prescriptions written in 2019-2020, divided into 17 disease sites, and manually curated by disease site experts for approved doses per fraction per site. 2) Dose per fraction too large for non-stereotactic treatment technique. 3) Dose per fraction too low (in dose painting prescriptions). With a goal of catching errors as far upstream as possible to minimize their propagation, a report was created and run every 30 minutes, checking all newly written prescriptions against the above rules. When prescriptions did not fall within the bounds of the rules, an automated email was sent to the prescriber alerting them of the atypical prescription and prompting them to check if it was written as intended. The rules were continuously analyzed in an attempt at balancing error detection against false positive alerts. <h3>Results</h3> From June-December 2021, 9,577 prescriptions were checked, and 70 email alerts were triggered, for an average alert rate of 0.7%. Of the 70 alerts, 60 (85.7%) were unapproved doses per fraction, 8 (11.4%) were doses too large for non-stereotactic treatment technique, and 2 (2.9%) were doses that were too low. The alert rate was 1.1% in June and trended down to 0.6% in December. Of the 70 alerts, 23 (32.9%) prescriptions were subsequently amended suggesting that the rate of erroneous prescription entry was 0.2% (23/9,577). <h3>Conclusion</h3> A baseline error rate of radiation oncology prescription entry has not been previously reported. This data suggests that the rate of erroneous prescription entry is at least 0.2%. Given the significant consequences of erroneous prescription entry, ranging from wasted resources and treatment delays (should these errors be caught prior to treatment), to potentially serious misadministration, there is significant value in implementing automated prescription checking systems in radiation oncology clinics.