Final Report: Analysis of Room Turnover Processes for EP and Cath Labs December 13, 2016 IOE 481 Team 1: Scott Agnew, Kim Cusmano, Brandon Duba, and Holly Johnston

UMHS’s Cardiac Procedures Unit (CPU) Electrophysiology Labs (EP) & Catheterization Labs (Cath) CPU experiencing long turnover times Turnover = Patient wheeled out to next patient wheeled in Out-of-Scope: Heart Failure Lab, EP lab 6 and patient pre-op In-Scope: EP and Cath labs turnovers Change slide design

Key Issues Patient, physician, and staff dissatisfaction Different definitions of turnover across staff No turnover measurement system No standard work

Goals Objectives Evaluated current turnover processes Identified waste/ coordination problem Established means to evaluate future turnovers Objectives Conducted time studies and interviews Developed process maps of current state Developed a means to evaluate performance Provide turnover recommendations

Historical Data Analysis Methods Historical Data Analysis Literature Search Process Maps Staff Interviews Time Study

Literature Search Method Search past student reports for: Background info Past work in CPU Search GoogleScholar for: Lean Tools of Standard Work Statistical Analysis

Historical Data Analysis Method Coordinators provided historical MiChart data Cath and EP lab operations Jan-Aug 2016 Analyzed data using R programming language Primary metrics: Turnover start time Turnover time Room ready minus room start

Time Study Method Turnovers observed: 20 Cath & 10 EP Full turnovers observed: 12 Cath & 5 EP To gain a better understanding of the tasks and staff coordination involved in the turnover process, the team observed the turnover processes for approximately 53 hours in the EP and Cath labs, witnessing 31 turnovers collectively. The team used stopwatches to map the start and end times of each step in the process and recorded it on a data collection sheet. The data collection sheet is attached in Appendix X. The major steps are outlined below: Steps Inside Lab: Patient wheeled out of room Room is cleaned and trash is disposed of New equipment for next lab is laid out Patient and inventory information is entered into computer Patient wheeled into room Steps Outside of Lab: RN wheels patient out of room and transports to recovery Hook up equipment for patient Relay post-lab data to other RN Dispose medical waste Find next patient Return with next patient The team then analyzed this data to find a baseline for the current state. To find the full turnover time the team averaged all of the full turnover times (12 for cath, 5 for EP). To find the length of each step, the team averaged the time for each step (with varying sample sizes).These numbers have been utilized to create the swim lane diagrams.

Process Maps Method District Cath & EP maps Swim lane set-up shows each staff member role Used to visualize delays & identify wastes

Current State Cath Process Map

Current State EP Process Map

Staff Interviews Methods Sets of questions based on different roles Interviewed 2 Cath Nurses, 2 Cath Techs, 4 EP Nurses, 2 EP techs & 1 EP CRNA Emailed questions to 3 Cath Physicians & 3 EP Physicians

Conclusions

Tasks inside lab not the cause of long turnovers 87% of time study observations show room was ready before next patient wheeled in 47% of Cath & 39% of EP labs idle Nurses & CRNAs: Communication issues during Pre-op activities

3. Average time between room-ready & wheels in: 47% Tasks inside lab not the cause of long turnovers 3. Average time between room-ready & wheels in: 47%

7. Average time between room-ready & wheels in: 39% Tasks inside lab not the cause of long turnovers 7. Average time between room-ready & wheels in: 39%

Current turnover times longer than goal Median Turnover Times (minutes): Goal Historical Data (N = 2320) Time Study (N = 17) Cath 15 28 16 EP 30 40 48

Variation in EP & Cath turnover processes Standardize definition of turnover reduces misconceptions [4] Order of tasks in process vary for each tech Physicians: Have unique procedure preferences

Lack of parallel workflow Parallel workflow is valuable during turnover [3] Balanced workloads led to 45% decrease in time [6] Workload is not balanced between techs

Lack of parallel workflow Cath No parallel work between techs EP No parallel work between techs

Task completed before wheels out 176% increase in frequency of short turnovers by streamlining cleaning to before wheels out [5] Tasks completed before wheels out Short turnover defined as 30 minutes

Tasks completed before patient is wheeled out Tasks completed before wheels out Cath Tasks completed before patient is wheeled out EP Wheels Out

Valuable MiChart fields not consistently entered Standardize definition and collect time data for baseline management [4] 48% of MiChart data within project scope Only 8% of data contained Room Ready field Physicians: Have unique procedure preferences Delete physician preference?

Leave lab to retrieve equipment EP Techs leave lab to retrieve equipment 80% of observations staff leaves lab during turnover to retrieve equipment Leave lab to retrieve equipment

Recommendations

Recommended Further Investigation Root Cause Analysis for Techs leaving lab Lack of equipment stocked Physician prefer different equipment Potential Causes for Out of Lab Delay Waiting for Pre-Op CRNA and RN Communication

Recommended Cath Turnover Process Red Circles are like callouts - represent changes

Recommended EP Turnover Process Red Circles are like callouts - represent changes

Recommended Future Turnover Tracking Use MiChart Metrics Room Ready: Techs Write Room Ready on Whiteboard Nurses Record Timestamps Management Posts Quarterly Reports

Next Steps Investigate Implement Utilize Distribute Project findings & recommendations Pre-op delays and EP equipment retrieval Whiteboard space for techs to record room ready Future state maps in training staff

Expected Impact Understanding of the current turnover processes Reduction of wasted actions and time Means for future evaluation & measurement Standardization of turnover processes Implementation plans for the recommendations

Thank you clients, coordinators, & professors! Janice Norville, MSN, MSBA, RN, Director of Clinical Operations Sheryl Wagner, Nursing Supervisor Jim Bloom, Allied Health Senior Supervisor Colleen Lucier, Allied Health Senior Supervisor Katie Schwalm, Industrial Engineer Andrei Duma, Industrial Engineer Mary Duck, UMHS IOE 481 Liaison Mark Van Oyen, IOE 481 Faculty Instructor Jai Sura, IOE 481 Graduate Student Instructor

Thank you, any questions?

Appendix A: Historical Data Analysis Plots

Appendix B: Historical Data Analysis Plots

Appendix C: Historical Data Analysis Plots

Appendix D: Historical Data Analysis Plots

Appendix E: Historical Data Analysis Plots

Appendix F: Historical Data Analysis Plots

Appendix G: Current State Cath Process Map 1. Tasks completed before patient is wheeled out 3. Average time between room-ready & wheels in: 47% 2. No parallel work between techs

Appendix H: Current State EP Process Map 5. Leave lab to retrieve equipment 4. Tasks completed before patient is wheeled out 6. No parallel work between techs 7. Average time between room-ready & wheels in: 39%

Appendix I: List of all Conclusions Tasks inside lab not the cause of long turnovers Current turnover times longer than goal Variation in EP & Cath turnover processes Lack of parallel workflow Task completed before wheels out Valuable MiChart fields not consistently entered EP Techs leave lab to retrieve equipment 1. 2. 3. 4. Lit search – streamlining tasks before turnover starts