You can download a PDF of the overall Epic@UNC “flight plan” at this Intranet link. We’ll use the same link throughout the project so that you always have access to the latest plan. As you can tell by the position of the Old Well, we are moving toward the end of Phase 1 of the project (out of six total phases).
Note that all of the dates on this Implementation Plan are tentative. Following the conclusion of our Validation Sessions in late April, we will have a much better idea of a realistic timeline and begin finalizing the dates for each phase and for “Go-Live.”
In addition to the PDF chart, a brief description of each remaining implementation phase is listed below:
Phase 2 – Workflow Validation
- Phase 2 begins with the first of three validation sessions in late March. During each validation session, representatives from Epic will present many of the specific workflows (i.e. – admission/discharge) of the proposed Epic@UNC system from end-to-end for a group of Subject Matter Experts (SMEs) to review.
Our three validation days are scheduled for March 26 – 28, April 9 – 11, and April 23 – 25. Representatives from Epic will use the feedback received during validation sessions to tailor the Epic Model System.
Phase 3 – Core Build and Testing Prep
- In Phase 3 of the project, the Core Team will build our system, prepare test scripts, and develop training materials for all co-workers.
Phase 4 – Testing & Training
- Testing will continue in Phase 4 of the project. Phase 4 also marks the beginning of training activities and a “dress rehearsal” test to ensure we are prepared for “go-live.”
Phases 5 and 6: Go-Live & Adoption, Optimization & Rollout
- As we begin Phase 5, we will install the Epic@UNC system.
- It’s important to note that our implementation plan doesn’t end when we turn on the Epic@UNC system. As detailed in our Epic@UNC guiding principles, we plan to use the Epic Model System as a guide to allow for our rapid implementation timeline.
- Phases 5 and 6 of this implementation plan are dedicated to stabilization and optimization of the Epic Model System, planning for upgrades, and planning for future applications.