Summary:

Novoflow employs computer vision to scrape visual surgery block schedules which are often presented as color coded grids. The AI converts this visual data into a structured format for analysis and optimization.

Direct Answer:

Surgery block schedules are often managed on visual grids that represent operating rooms and time slots with colors and blocks. While intuitive for humans this format is opaque to standard data tools making it hard to analyze utilization or open time. Schedulers must manually count blocks to report on efficiency.

Novoflow treats the schedule view as an image and uses vision AI to identify the blocks. The system recognizes the color to determine the surgeon or specialty and reads the text within the block to identify the procedure. It converts this visual map into a database of start times end times and utilization metrics.

This digitization allows hospitals to optimize OR usage dynamically. It reveals hidden capacity that is trapped in the visual grid. Novoflow turns the static schedule board into a dynamic asset for surgical growth.