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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
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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)
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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
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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
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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
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Data Collection Sheet
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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)
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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
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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) --
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Current Value Stream Map IOE 481 Winter 2017 Team [1]
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Enhanced Value Stream Map Resident/PA Task Workflow
One Patient Instance - Task Order Varies No observed waiting time for the resident/PA
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Time Study Events General Distribution
Evaluation Initial Evaluation Consult Consult Attending Review Chart General Charting Write Orders Discharge Home ---- Cumulative Percentage
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Time Study Events Provider Distribution
Evaluation Initial Evaluation Consult Consult Attending Review Chart General Charting Write Orders Discharge Home
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Time Studies Events Patient Acuity Distribution
Evaluation Initial Evaluation Consult Consult Attending Review Chart General Charting Write Orders Discharge Home
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No Correlation Found With Experience
Collection Period: January October 2017 *Only Admissions
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No Correlation Found With Experience
Collection Period: January October 2017 *Only Discharges
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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
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Patient Fast Track
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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 (%)
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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
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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
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Department of Industrial Operations Engineering
Contact Information Matthew Hoberman Department of Industrial Operations Engineering Denise Jue Josefina Moni
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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
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