Application of Engineering Principles to Patient Flow & Healthcare Delivery

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1 Application of Engineering Principles to Patient Flow & Healthcare Delivery Jeanne M Huddleston, MD, MS Medical Director, Health Care Systems Engineering Mayo Clinic 2013 MFMER slide-1

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3 $9.8 Billion* *Cost of health care associated infections annually MFMER slide-3

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8 St Marys Campus, Mayo Clinic Hospital

9 Annual Patient Encounters Total clinic patients: 1,260,000 Hospital admissions: 131,000 Hospital days: 608,000 Employees: > 60,000

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14 Dream Project

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16 Leadership: The Problem Domains Capacity and resource management Safety (employee and patient) Workload and treatment optimization Process efficiency and reliable care delivery Systems integration across transitions of care Workforce projections with possible staffing models Workflow reorganization in new physical space Economic analyses with generation of novel payment models Patient-centered outcomes research 2013 MFMER slide-16

17 Omission vs. Commission Mayo Clinic, Mortality Review System 2013 MFMER slide-17

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20 Example: delayed diagnosis of sepsis & delayed recognition of a postoperative complication 59 year old female underwent TAH POD #3 AKI, urinary retention with new abdominal distension and pain POD #4 AKI worse, significant abdominal pain narcotics stopped. Episode of PAF (130 s) POD #5 hypotensive (70/45) with diaphoresis and nausea RRT called but no blood pressure on their arrival Code called with > 1hr of resuscitation efforts On autopsy, abdomen filled with pus and a knick in the small bowel MFMER slide-20

21 Labs: Hb: 7.1, Leukocytes: 2.3 Creat (9/29): 3 (2-month baseline): 1.6 Case Example 44 hours 27 hours Clear change in physiologic state Met RRT Criteria RRT called 55-year-old male with CLL with MUD peripheral blood stem cell transplant 7/10 (2 months before). Dismissed 9/ MFMER slide-21

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23 Health Care Systems Engineering: Process Discovery, Design & Implementation Oversight Management Team Requirements Team Analytics Team Systems Architecture Team Clinical Verification & Validation Team Clinical Pilot Team Clinical Integration & Diffusion Team Reengineering Phase Failure Modes and Effect Analysis, Data mining, Predictive analytics, Financial Effect Analyses Workflow analyses & Simulation Modeling Implementation Phase Iterative DMAIC steps Diffusion Phase Mayo Clinic Model of Diffusion 2013 MFMER slide-23

24 System Architecture Requirements: Tiered rescue model with time limited escalation of expertise with demonstrated clinical response Bedside evaluations Increased provider vigilance RRT to be called when their specific expertise is needed Promotes teamwork and communication Makes the deterioration and results of interventions visibly obvious to bedside providers Allows all types of students, residents and fellows to learn Allows patient and family preferences to be incorporated into rescue response Makes practice constraints evident Leverages technology at the point of care (bedside) Research supported by CSHCD 2013 MFMER slide-24

25 Tiered, time-limited escalation of expertise at the bedside RN clinical verification of vital signs Validation Evaluate/treat/resolve or silence/snooze Max 2-6 hours Tier 1 First responder to bedside & notifies senior member of team Evaluate/treat/resolve or silence/snooze Max 2-3 hours Tier 2 Tier 3? RRT Second responder to bedside for eval of clinical condition, differential, goals of care, and plan for reassessment Concept derived from 7 RN focus groups & discussions with MERS, Sepsis MTR, CC- IMP & HIM quality committee including their practice leadership. MANY details to sort through as portion of Phase 2 BPR Charter. The practice must design the process and policies MFMER slide-25

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27 How about a good death? Example: palliation failure 82 year old male with severe COPD and pancreatic cancer was hospitalized for bowel obstruction. Postoperative delirium Postoperative respiratory failure Pain meds held Per nursing notes, patient routinely called out in pain and family members consistently asked that he be kept comfortable. His average pain score was 8/10 in the 24 hours preceding death. Joshua Bright: A Good Death 2 days later, patient was made comfort care only and died within hours MFMER slide-27

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29 Neurology Appointments Forecast Implemented 2013 MFMER slide-29

30 Perspectives To Be Considered 2013 MFMER slide-30

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32 Clinical Covariates = Face Validity Age Number of levels Approach Anterior Posterior Lateral Staged Cervical, thoracic or lumbar Deformity Decompression Grafting Fusion Revision Instrumentation CT scan (O-arm) 2013 MFMER slide-32

33 Return on Investment Cost reduction From 3 to 2 ORs Fewer no-hitters Decreased weekend stays of Medicare patients Less use of ORs outside of prime time Increased revenue More cases Case mix 2013 MFMER slide-33

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35 Clinical Engineering Learning Laboratory 2013 MFMER slide-35

36 domeproject.org.uk redorbit.com athensnews.com beerswithdemo.blogspot.com Clinical Engineering Learning Laboratories provide real-time practice and outcomes measurement to support interdisciplinary teams of engineers and health services researchers embedded into busy, live patient care environments MFMER slide-36

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38 Patients need us to tell their stories. Clinicians need scientific evidence. Hospitals need both NOW: stories and analytics to learn, improve flow, advance care, and save lives MFMER slide-38

39 Questions & Discussion 2013 MFMER slide-39

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