Abstract
1. Understand the role of Lean Six Sigma in optimizing clinical operations for opioid prescribing practices.
2. Apply clinical understanding and local practice-based operations to self-report ways that Lean Six Sigma might optimize their clinical workflow.
Naloxone co-prescribing is emerging as an essential component to combating the risk of overdose and deaths in patients on long-term opioid therapy. The use of Lean Six Sigma principles to optimize automated screening and practices for high-risk opioid use patients can significantly improve the co-prescribing of naloxone.
Naloxone co-prescribing is emerging as an essential component to combating the risk of overdose and deaths in patients on long-term opioid therapy (1). However, such prescriptions are often ordered at a very low rate (2).
Our team set out to improve the rate of naloxone co-prescription in patients who were at high risk for overdose using Lean Six Sigma principles.
Lean Six Sigma DMADV (Define, Measure, Analyze, Design, Validate) methodology was utilized to create a new process for naloxone prescription in high-risk patients. Using EPIC EMR, the morphine equivalent daily dosing (MEDD) was calculated automatically. For patients whose MEDD was greater than 90 meq, a best practice advisory (BPA) was triggered to order naloxone if not previously completed. Data was tracked using EPIC dashboard metrics, which listed the total number of high-risk patients, if naloxone was prescribed, and the percentage completed monthly. QI Macros v2024 was used for data analysis.
Before intervention between January 2022 and November 2022, the average number of high-risk patients not being prescribed naloxone was 90%, with a range of 88-93% with relative process stability over a 9-month period. During development and initial testing between November 2022 and September 2023, the average was 85% (range 75% to 90%). Several new processes were developed to correct EMR data capture and BPA notification during this stage, which resulted in mild changes in prescribing practices. Post-implementation between October 2023 and June 2024 saw a decline to an average of 35% (range 31% to 45%) with improved process stability over 6 months. Overall, the process improved naloxone prescriptions for high-risk patients by 55%.
The use of automated screening for high-risk patients and best practice advisories was able to substantially increase naloxone prescriptions by 55% in high-risk patients.
1. Mueller SR, Walley AY, Calcaterra SL, Glanz JM, Binswanger IA. A Review of Opioid Overdose Prevention and Naloxone Prescribing: Implications for Translating Community Programming Into Clinical Practice. Subst Abus. 2015;36(2):240-53. 2. Guy GP, Jr., Strahan AE, Haegerich T, Losby JL, Ragan K, Evans ME, et al. Concurrent Naloxone Dispensing Among Individuals with High-Risk Opioid Prescriptions, USA, 2015-2019. Journal of General Internal Medicine. 2021;36(10):3254-6.