Background: As the number of targeted treatments in oncology continues to grow, the importance of structured genomic data in the electronic health record becomes critical for population-level mutation queries. However, many physician-facing next generation sequencing (NGS) reports consist of free text, a data format that makes these larger analyses time-consuming and inefficient. The EPIC® genomics module allows integration of a variety of NGS results into a unified structured format, granting clinicians an efficient means to identify cohorts of patients with specific mutations that may qualify for new treatments or clinical trials. Methods: Here, we present our institution’s experience with implementation of the EPIC® genomics module from July 2021 to the present. Our genomic data conversion process required mapping mutations from a variety of NGS report formats, including but not limited to Tempus®, FoundationOne®, Invitae®, and an internal platform called SNaPShot, to a Health Level Seven (HL7) standardized format which is interoperable with the electronic health record. We outline an automated workflow so that internally ordered NGS results convert and upload into the genomics module, as well as the process of backloading prior NGS sequencing into the electronic health record. Results: Our genomics module currently contains over 16,000 somatic reports, with over 12,000 of these results backloaded into the module. In Figure 1, we present the results of an example query that identified 57 patients with a KRAS G12C mutation who could be candidates for sotorasib. The described infrastructure supports rapid identification of cohorts of patients with specific mutations with minimal overhead, and this workflow can be used to contact oncologists when new treatments or clinical trials become available that may benefit one of their patients. Conclusions: This project demonstrates the feasibility and utility of a standardized structured format for oncology NGS results in the electronic health record via the EPIC® genomics module. The experience is specific to our institution, but the pipeline is easily translated to other practices, with at least 29 institutions nationwide already implementing similar workflows. This model makes large-scale mutational queries in the electronic health record more efficient, which can translate into more rapid adoption of novel targeted therapies for patients as well as easier patient screening for clinical trials.
Finding Patients for Tumor Genotype-Informed Treatments
This figure describes the process of identifying 57 potential candidates for sotorasib, a targeted therapy approved in May 2021 for advanced or metastatic non-small cell lung cancer with a KRAS G12C mutation after one prior systemic treatment. First, open the EPIC dashboard tab (1) and click on the reports tab (2). Choose report library (3) and search for “genomics” (4). Click “New Report” to start a new search (5). Input search criteria, in this case, a KRAS G12C mutation (6). Finally, run the report query (7). Patient information, genomic results, and provider information will populate the report (8).
Citation: Journal of the National Comprehensive Cancer Network 21, 3.5; 10.6004/jnccn.2022.7165
Finding Patients for Tumor Genotype-Informed Treatments
This figure describes the process of identifying 57 potential candidates for sotorasib, a targeted therapy approved in May 2021 for advanced or metastatic non-small cell lung cancer with a KRAS G12C mutation after one prior systemic treatment. First, open the EPIC dashboard tab (1) and click on the reports tab (2). Choose report library (3) and search for “genomics” (4). Click “New Report” to start a new search (5). Input search criteria, in this case, a KRAS G12C mutation (6). Finally, run the report query (7). Patient information, genomic results, and provider information will populate the report (8).
Citation: Journal of the National Comprehensive Cancer Network 21, 3.5; 10.6004/jnccn.2022.7165
Finding Patients for Tumor Genotype-Informed Treatments
This figure describes the process of identifying 57 potential candidates for sotorasib, a targeted therapy approved in May 2021 for advanced or metastatic non-small cell lung cancer with a KRAS G12C mutation after one prior systemic treatment. First, open the EPIC dashboard tab (1) and click on the reports tab (2). Choose report library (3) and search for “genomics” (4). Click “New Report” to start a new search (5). Input search criteria, in this case, a KRAS G12C mutation (6). Finally, run the report query (7). Patient information, genomic results, and provider information will populate the report (8).
Citation: Journal of the National Comprehensive Cancer Network 21, 3.5; 10.6004/jnccn.2022.7165
