Children’s Emergency Services Children’s Emergency Services (CES) Current State and Final Recommendations for Improvement IOE 481 Team 5 Matthew Hoberman Denise Jue Josefina Moni Dr. Prashant Mahajan Ms. Elizabeth Duffy Dr. Mark Van Oyen Final Presentation 17F5-final-report 12 December 2017

Background Children’s Emergency Services (CES) provides healthcare for children and young adults Vice Chair of Emergency Medicine asked an IOE team to investigate the following: Issues with evaluation, diagnosis, treatment, and disposition Variations in LOS due to resident workload/experience level and patient acuity Delays and bottlenecks in the patient length of stay (LOS)

Goals & Objectives Record and analyze non-clinical and clinical time to improve resident/PA workflow Characterize the working behavior and tasks of residents/PA Evaluate non-clinical tasks to find bottlenecks Minimize the time from the point of initial doctor evaluation to disposition Discriminate and characterize the working behavior of resident - components of resident’s workflow and tasks Objective: eliminate non value added time

Identify Bottlenecks to reduce Length of Stay within CES Team Approach Time Studies Gemba Walk Identify Bottlenecks to reduce Length of Stay within CES Historical Data Analysis Observed Data Analysis Literature Review

Time Studies Collection Period: October 2017 - November 2017 Shadow Residents (Level 1 - 4) and Physician’s Assistants (PA) 18 providers Record patient room number, patient acuity, resident/PA workload and experience level ~100 patient cases Document each event with start time and end time ~1000 discrete events

Data Collection Sheet

Data Collection Describing Clinical and Non-Clinical Events Clinical Time In Patient Room IE: Initial Evaluation First contact with provider E: Evaluations in Room Subsequent evaluations Non-Clinical Time RC: Review Chart CX: Consults (Excluding Attendings) CA: Consult Attending WO: Write Order GC: General Charting D: Filed for Disposition N: Notes (Other)

Time Study Results Collection Period: October 2017 - November 2017 Observed Clinical (%): Total Clinical Time Total Time Observed Observed Non-Clinical (%): Total Non-Clinical Time Total Time Observed

Time Study Results Collection Period: October 2017 - November 2017 Event Sample Size (n) Mean (mm:ss) Median (mm:ss) Avg # Events per Patient Evaluation (E) 112 5:11 3 1.70 Initial Eval (IE) 58 9:12 9:15 1.00 Consult (CX) 172 2:00 1:15 2.62 Consult Att (CA) 147 2:02 1:34 2.12 Review Chart (RC) 141 1:45 1:28 2.20 General Charting (GC) 183 2:49 2 2.47 Write Orders (WO) 82 1:38 1:12 1.73 Filed for Disposition (D) 44 2:15 1:55 1.39 Total 939 (~58 hours) --

Current Value Stream Map IOE 481 Winter 2017 Team [1]

Enhanced Value Stream Map Resident/PA Task Workflow One Patient Instance - Task Order Varies No observed waiting time for the resident/PA

Time Study Events General Distribution Evaluation Initial Evaluation Consult Consult Attending Review Chart General Charting Write Orders Discharge Home ---- Cumulative Percentage

Time Study Events Provider Distribution Evaluation Initial Evaluation Consult Consult Attending Review Chart General Charting Write Orders Discharge Home

Time Studies Events Patient Acuity Distribution Evaluation Initial Evaluation Consult Consult Attending Review Chart General Charting Write Orders Discharge Home

No Correlation Found With Experience Collection Period: January 2016 - October 2017 *Only Admissions

No Correlation Found With Experience Collection Period: January 2016 - October 2017 *Only Discharges

Patient Distribution Acuity and Average Time to First Provider Contact Average* (mm:ss) 1 (0.17) 2 19:00 2 (31.69) 379 30:21 3 (42.06) 505 44:58 4 (25.25) 302 51:30 5 (0.84) 10 33:06 *Time between Arrival and First Provider Contact

Patient Fast Track

Documentation Final Observations General Charting most time consuming non-clinical task Establish best practice of documenting while evaluating (iPads/Laptops) Further investigate tradeoffs of in-room documentation General Charting (%)

Managing Interruptions Final Observations Large number of interruptions observed Phone calls during evaluations in the room High cognitive load - many patients at a time Visual Signage Develop best practices or standards in prioritization Further investigate existing policies

Further Data Collection Gather more time studies data for more statistically accurate findings Investigate disposition to discharge and admittance Explore workflow tasks of nurses and attendings

Department of Industrial Operations Engineering Contact Information Matthew Hoberman Department of Industrial Operations Engineering mhob@umich.edu Denise Jue djue@umich.edu Josefina Moni mjmoni@umich.edu

References [1] G. Gupta, A. Shermon, E. Smith, and H. Willet(2017). “Using Lean Tools to Identify Opportunities for Improvement in the Michigan Medicine Children’s Emergency Services,” Ann Arbor, MI, 2017