Agreement between cytotechnologists and cytopathologists as a new measure of cytopathologist performance in gynecologic cytology

Developing dashboards for performance improvement in cytopathology

INTRODUCTION

Cytopathology has well-defined and objective quality metrics for monitoring the performance of cytopathologists (CPs) and cytotechnologists (CTs). We transformed these metrics into dashboards for real-time visualization and on-demand feedback.

METHODS

Dashboards were constructed with data from the previous 10 calendar years using the software Tableau. The dashboards for CPs were designed to display 2 gynecologic metrics and 1 nongynecologic metric: the ASCUS:SIL ratio, the percentage of high-risk human papillomavirus (HPV)-positive ASCUS interpretations (HPV+ ASCUS rate), and the proportion of AUS/FLUS thyroid interpretations. CT dashboards were designed to include these plus 2 others: the percentage of Papanicolaou tests referred for CP review and the percentage of Papanicolaou tests interpreted as unsatisfactory. Established professional benchmarks or standard deviations were used to set color-coded "goal," "borderline," and "attention" zones.

RESULTS

Personal dashboards were successfully developed and implemented for CPs and CTs in the laboratory, with results that are automatically updated every week, requiring minimal curation. Each CP and CT has a unique link that allows them access to their results at any time. Color-coded displays show the individual their quality metrics over the past 10 years, with a snapshot of data from the past 3 months. The laboratory director has a unique link that allows the director access to results for each individual and the laboratory in aggregate.

CONCLUSIONS

Personalized dashboards enable individuals to access their performance metrics on demand and examine recent performance as well as patterns over time. This facilitates self-motivation to improve performance and adhere to professional benchmarks.

CytoBrowser: a browser-based collaborative annotation platform for whole slide images

We present CytoBrowser, an open-source (GPLv3) JavaScript and Node.js driven environment for fast and accessible collaborative online visualization, assessment, and annotation of very large microscopy images, including, but not limited to, z-stacks (focus stacks) of cytology or histology whole slide images. CytoBrowser provides a web-based viewer for high-resolution zoomable images and facilitates easy remote collaboration, with options for joint-view visualization and simultaneous collaborative annotation of very large datasets. It delivers a unique combination of functionalities not found in other software solutions, making it a preferred tool for large scale annotation of whole slide image data. The web browser interface is directly accessible on any modern computer or even on a mobile phone, without need for additional software. By sharing a "session", several remote users can interactively explore and jointly annotate whole slide image data, thereby reaching improved data understanding and annotation quality, effortless project scaling and distribution of resources to/from remote locations, efficient creation of "ground truth" annotations for methods' evaluation and training of machine learning-based approaches, a user-friendly learning environment for medical students, to just name a few. Rectangle and polygon region annotations complement point-based annotations, each with a selectable annotation-class as well as free-form text fields. The default setting of CytoBrowser presents an interface for the Bethesda cancer grading system, while other annotation schemes can easily be incorporated. Automatic server side storage of annotations is complemented by JSON-based import/export options facilitating easy interoperability with other tools. CytoBrowser is available here: https://mida-group.github.io/CytoBrowser/.