Poster Session #2: UC Ballroom

Presentation Type

Poster

Faculty Mentor’s Full Name

Tom Gallagher

Faculty Mentor’s Department

Department of Applied Computing & Electronics, Missoula College

Abstract / Artist's Statement

Electronic Health Record (EHR) databases are an important tool for clinician trainers and information system developers, yet access to actual EHRs remains difficult due to patient privacy concerns. A synthetic EHR would prove valuable provided it was realistic in representing the same characteristics as the actual EHR. The approach is unique as it does not involve the use of any patient Protected Health Information (PHI). Using publicly available data, a process was developed to generate the demographic attributes of a synthetic EHR based upon a given geographic region. The resulting EHR provides a realistic representation of a patient that a clinician would expect to encounter during a visit. This project is a component of a larger research effort aimed at generating a database of Realistic Synthetic EHRs (RS-EHR) from publicly available data sets.

Category

Physical Sciences

Share

COinS
 
Apr 11th, 3:00 PM Apr 11th, 4:00 PM

Generating the Demographic Attributes of the Synthetic Electronic Health Record

Electronic Health Record (EHR) databases are an important tool for clinician trainers and information system developers, yet access to actual EHRs remains difficult due to patient privacy concerns. A synthetic EHR would prove valuable provided it was realistic in representing the same characteristics as the actual EHR. The approach is unique as it does not involve the use of any patient Protected Health Information (PHI). Using publicly available data, a process was developed to generate the demographic attributes of a synthetic EHR based upon a given geographic region. The resulting EHR provides a realistic representation of a patient that a clinician would expect to encounter during a visit. This project is a component of a larger research effort aimed at generating a database of Realistic Synthetic EHRs (RS-EHR) from publicly available data sets.