Hi everyone! I’m a medical student at Brown University and want to share a project that I’m working on with Dr. Hamish Fraser (@hamish), the Brown Center for Biomedical Informatics, and partners at the Mae Tao Clinic in Thailand.
We’re developing a software tool to streamline data collection from paper records by automating the digitization process. The application connects to a user’s USB webcam to capture images of filled records, and then uses optical mark recognition to automatically extract categorical information from the images (ex. checkboxes, multiple choice items, etc.). For freeform elements such as hand-written digits, the user is visually guided through the process of manual entry (we hope to automate this process using optical character recognition in the next update). Here’s a short demo video, in this case configured for the the COVID-19 Case Report Form used by the Rhode Island Department of Health.
We’re interested to hear your thoughts and feedback. In particular:
- Do you see this as a potentially valuable tool in your data collection process?
- Would you be interested in trying out the software on paper records at your institution?
We’re eager to collaborate with anyone interested in exploring the value of adding automated digitization to their information workflow. If you share with us a template for a paper record of interest (JPEG, PDF, any format really), we can configure the application to parse its layout and start the discussion around testing the software retrospectively on a set of already completed forms.
For context, this software was originally designed for the Health Information System team at the Mae Tao Clinic to help them digitize the paper delivery records in their Reproductive Health department. The results of initial on-site testing were very promising, but in light of recent COVID-19-related developments our pilot phase is currently on hold.
We believe a tool like this could streamline data collection in a number of different settings, particularly in cases where manual entry is a burden and data quality is critical. Looking forward to starting the conversation with you all!