Large-scale data extraction from the UNOS organ donor documents

The scope of our study is all UNOS data of the USA organ donors since 2008. The data is not analyzable in a large scale in the past because it was captured in PDF documents known as "Attachments", whereby every donor is represented by dozens of PDF documents in heterogenous formats. To make the data analyzable, one needs to convert the content inside these PDFs to an analyzable data format, such as a standard SQL database. In this paper we will focus on 2022 UNOS data comprised of $\approx 400,000$ PDF documents spanning millions of pages. The totality of UNOS data covers 15 years (2008--20022) and our results will be quickly extended to the entire data. Our method captures a portion of the data in DCD flowsheets, kidney perfusion data, and data captured during patient hospital stay (e.g. vital signs, ventilator settings, etc.). The current paper assumes that the reader is familiar with the content of the UNOS data. The overview of the types of data and challenges they present is a subject of another paper. Here we focus on demonstrating that the goal of building a comprehensive, analyzable database from UNOS documents is an attainable task, and we provide an overview of our methodology. The project resulted in datasets by far larger than previously available even in this preliminary phase.