Improving Clinical Information on Head CT Requisitions From the Emergency Department to Aid Interpretation and Billing Efficiency.

OBJECTIVE: The accuracy of radiologic interpretations is higher when appropriate clinical information is provided, as is the likelihood of reimbursement for the studies. The purpose of this project was to evaluate and improve the quality of clinical information provided on head CT requisitions from an urban emergency department (ED). SUBJECTS AND METHODS: In a prospective study conducted from July 2015 to May 2016, attending neuroradiologists evaluated 1100 randomly selected ED requisitions for unenhanced head CT, grading them for clinical and billing adequacy on a scale of 0-2. After acquisition of baseline data (400 studies), an intervention was performed that consisted of education of ED staff on the importance of clinical information in requisitions. A reminder slide was placed on a large screen in the ED staff working area with examples of appropriate history. Postintervention data (700 studies) were subsequently obtained. Mean scores and payment lag time before versus after the intervention were compared by Wilcoxon rank sum test. RESULTS: Statistically significant improvement was found in mean scores after the intervention for both clinical (1.32 to 1.43, p = 0.003) and billing (1.64 to 1.74, p = 0.02) adequacy categories. The percentage of studies with a score of 2 increased in both categories, and the percentages of 0 and 1 scores declined. There was a 21.1-day decrease in payment lag time (from 75.8 to 54.7 days, p < 0.0001). CONCLUSION: The quality of clinical information provided on imaging requisitions by ED faculty and residents improved after a fairly simple intervention. Billing efficiency improved, and payment lag time decreased substantially.

Unified Database for Rejected Image Analysis Across Multiple Vendors in Radiography.

Reject rate analysis has been part of radiography departments' quality control since the days of screen-film radiography. In the era of digital radiography, one might expect that reject rate analysis is easily facilitated because of readily available information produced by the modality during the examination procedure. Unfortunately, this is not always the case. The lack of an industry standard and the wide variety of system log entries and formats have made it difficult to implement a robust multivendor reject analysis program, and logs do not always include all relevant information. The increased use of digital detectors exacerbates this problem because of higher reject rates associated with digital radiography compared with computed radiography. In this article, the authors report on the development of a unified database for vendor-neutral reject analysis across multiple sites within an academic institution and share their experience from a team-based approach to reduce reject rates.