ORCID ID
Graduation Date
Summer 8-14-2026
Document Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Programs
Biomedical Informatics
First Advisor
Dr. Jesse Cox
Abstract
Documentation standardization using structured, discrete fields within the electronic health record (EHR) environment is vital to data computability. Programs that promote patient outcomes, such as population health, learning health systems (LHS), and research innovation, among others, require high-quality data to establish and function effectively. In addition, integrative clinical systems such as clinical decision support (CDS) and automative EHR functionality can be used to develop connections with other portions of the record, such as the problem list (PL), or to create interoperability with other systems to create efficiencies and facilitate care coordination when data elements are captured discretely. This is particularly important for the utility of data extraction and treatment of high-consequence conditions that cause cancer, as well as for cancer care coordination. To evaluate inconsistencies in the PL and the impact of PL errors on the management of higher-consequence diseases, we will qualitatively assess whether the genetically derived cancer-causing syndrome, Lynch Syndrome (LS), is present in the PL (Aim 1). This effort will include a descriptive manual chart analysis to determine whether mismatch repair deficiency (dMMR) is present in the PL and to identify where LS documentation can be found in genetic testing and oncology notes in the EHR. To assess the quality of EHR data, its accessibility, and whether it is iv captured in a standardized manner conducive to extraction, we conducted a workflow analysis through qualitative evaluation of semi-structured interviews with an oncologist, pathologist, and geneticist involved in the diagnosis and care of LS patients (Aim 2). We develop an innovative method (Aim 3) to encode all historical pediatric synoptic pathology reports from a single institution, rendering the data elements computable for extraction and use in cancer research. This work comprehensively explains why standardization and structured data capture are necessary components of an organized EHR system capable of capturing high-quality data needed for research and patient care. Most importantly, the integration efforts and interoperable concepts that promote and facilitate new cancer treatments and the coordination of patient care are supported by and enabled through standardization.
Rights
The author holds the copyright to this work and any reuse or permissions must be obtained from the author directly.
Recommended Citation
Englund, Andrea L., "Impacts of Standardized Documentation and Workflow on Cancer Data Quality and Accessibility in the EHR" (2026). Theses & Dissertations. 1085.
https://digitalcommons.unmc.edu/etd/1085