Development of a novel visualization, labeling, and tracking engine for human anatomy.

The key to tracking, collating, and communicating skin cancer data is standardization, enhanced precision, and categorization of anatomic descriptions. Imprecise and non-standardized labeling of anatomic sites for skin cancer biopsies creates challenges in communicating and identifying the skin cancer location at the time of treatment. Diagnostic biopsies often remove the visible cancer cells, and since skin cancer most commonly arises on sun- or radiation-damaged skin with numerous surrounding or contiguous discolorations, lesions, and scars, the biopsy site can be difficult to find. Furthermore, photos are not always taken at time of biopsy or are not readily available at time of surgery, and most Electronic Health Record (EHR) systems rely on free-text or non-standardized labeling of anatomic sites. This project aims to create methods to document reproducible and standardized anatomic site descriptions of skin cancer locations, to visualize skin cancer locations, and to attach data related to skin cancers at each affected anatomic site. The anatomic site descriptions are also enhanced with standardized directional modifiers for increased accuracy and precision, thereby creating a linguistic global position system (GPS) for the human body. The project involves a simplified process to attach skin cancer diagnoses and diagnostic codes to standardized anatomic sites with enhanced descriptions and visualizations across the skin surface topography. Precise and standardized anatomic labeling with corresponding visualizations will facilitate communication between clinics, increase clinical accuracy and efficiency, and enhance patient safety and understanding by reducing the risk of wrong-site surgery for skin cancer. The project also integrates functionality to regenerate anatomic site descriptions and visualizations, thus mitigating poor-quality issues with faxed photos, while simultaneously maintaining compliance with regulatory statutes. Finally, this project aims to increase clinician confidence in identifying the location of a skin cancer by using standardized, validated, and interoperable language, codes, and links that can regenerate standardized anatomic site descriptions and visualizations.