Development of an interactive web dashboard to facilitate the reexamination of pathology reports for instances of underbilling of CPT codes

Abstract

Current Procedural Terminology Codes is a numerical coding system used to bill for medical procedures and services and crucially, represents a major reimbursement pathway. Given that pathology services represent a consequential source of hospital revenue, understanding instances where codes may have been misassigned or underbilled is critical. Several algorithms have been proposed that can identify improperly billed CPT codes in existing datasets of pathology reports. Estimation of the fiscal impacts of these reports requires a coder (i.e., billing staff) to review the original reports and manually code them again. As the re-assignment of codes using machine learning algorithms can be done quickly, the bottleneck in validating these reassignments is in this manual re-coding process, which can prove cumbersome. This work documents the development of a rapidly deployable dashboard for examination of reports that the original coder may have misbilled. Our dashboard features the following main components: (1) a bar plot to show the predicted probabilities for each CPT code, (2) an interpretation plot showing how each word in the report combines to form the overall prediction, and (3) a place for the user to input the CPT code they have chosen to assign. This dashboard utilizes the algorithms developed to accurately identify CPT codes to highlight the codes missed by the original coders. In order to demonstrate the function of this web application, we recruited pathologists to utilize it to highlight reports that had codes incorrectly assigned. We expect this application to accelerate the validation of re-assigned codes through facilitating rapid review of false-positive pathology reports. In the future, we will use this technology to review thousands of past cases in order to estimate the impact of underbilling has on departmental revenue.

Keywords: Current procedural terminology; Machine learning; Misbilling; Natural language processing; Pathology reports; Web development.

Fig. 1

Graphical depiction of key innovations: pathology report is processed by coder and NLP algorithm; coder reviews candidate underbilled codes to determine if code was actually underbilled

Fig. 2

Dashboard overview: (a) The bar plot shows the predictions for each CPT code. (b) Contains the interpretation plot for a specific report and specific CPT code. (c) Where the user selects which reports to display; it is also where the user will input their assignment. (d) Search box to search all reports for specific language.

Fig. 3

Example interpretation plot for primary CPT code 88307. This report was originally assigned 88305, but our model assigned 88307. The interpretation plot highlighted the words “fresh” and “resection” as important.