"Utilizing EPIC to Improve Efficiency of Pre-anesthesia Evaluations for" by Karol Harshaw-Ellis¹,, Sarah B. Budrovic et al.
 

Document Type

Poster

Original Publication Date

2025

Comments

Presented at SPAQI 2025 (Society for Perioperative Assessment and Quality Improvement) Conference, Denver, CO

Date of Submission

February 2025

Abstract

Background: Preoperative anesthesia evaluations of elective procedures are important to anesthesia care and imperative to prevent postoperative complications and unnecessary surgical cancellations¹. Triaging cases are complex, requiring clinical skills to facilitate the process. Triaging is cumbersome and, in most organizations, done manually. In 2021, our healthcare institution transitioned to EPIC² and formed a team of anesthesiologists, surgeons, informaticists, and EPIC analysts to automate the triage process which was nonexistent.

Purpose: Utilizing EPIC logic and a surgical risk classification (SRC) (Table 1) developed by the team cases are triaged as high, medium, or low. The SRC is based on blood loss, length of procedure and potential for hemodynamic instability and assigned upon case request. In turn, a 30-day surgical case report is generated for in-person scheduling of high-risk cases. For medium and low risk, a score is calculated based on the SRC and specific risk factors based on SNOMED³ CT (Systematized Nomenclature of Medicine Clinical Terms) codes (Table 2). These risk factors are analyzed based on the problem list and questionnaire. An Advanced Practice Provider (APP) triage report is generated in EPIC for low and medium-risk cases. Medium-risk with a score of one or above are auto-assigned an in-person visit. An APP triages the low-risk and medium-risk (score of 0) to either a phone screen or in-person visit after a comprehensive chart review. In addition, high-alert medications such as anticoagulants, Glucagon-like Peptides, and Sodium-glucose cotransporter-2 Inhibitors are displayed on the triage report to facilitate early triaging, so medications can be held in a timely manner.

Results: Automation of the triage process has been effective at reducing the manual work. There was an increase in the number of APP triages completed (Table 3) from 200-300 to 500-800 range.

Conclusion: This triage process is not without flaws and has required ongoing enhancements with the latest being collaborating with medical colleagues to ensure medical histories are up to date.

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