Microsoft PowerPoint - Future of OR May 08

The Future of the Operating Room: Patient Safety, Simulation, New Technology Andrew S. Wright MD Institute for Surgical and Interventional Simulation BioRobotics Laboratory University of Washington Disclosure Research Support Covidien Simulab LifeCell Ownership Interest Mindstreet Multimedia LLC *There will be no discussion of products from these companies Institute for Surgical and Interventional Simulation Operating Room Pre-op Anesthesia Post-op Recovery Discharge Planning Healthcare Environment Operating Room Pre-op Anesthesia Post-op Recovery Discharge Planning Healthcare Environment Operating Room Operating Room Pre-op Anesthesia Nurses Surgeon Post-op Recovery Discharge Anesthesia Planning Techs Patient Disease Healthcare Environment Operating Room Pre-op Anesthesia Nurses Surgeon Post-op Recovery OR Team Patient Disease Discharge Anesthesia Planning Techs Healthcare Environment OR Suite Operating Room Pre-op Anesthesia Nurses Surgeon Post-op Recovery OR Team Patient Disease Discharge Anesthesia Planning Techs Healthcare Environment Hospital Operating Suite Logistics OR Suite Operating Room Information Systems Central Supply Post-op Recovery Pre-op Anesthesia Nurses Surgeon OR Team Patient Disease Discharge Anesthesia Planning Techs Patient Centered Care Reduce Errors Improve Outcomes Patient Medical Error “To Err is Human” Institute of Medicine 1999 Up to 100,000 lives lost due to medical errors Cost $17-29 Billion Medical Error “To Err is Human” Institute of Medicine 1999 Up to 100,000 lives lost due to medical errors Cost $17-29 Billion Discharge Zero Tolerance for Errors Planning Medicare “Never Events” October 2008 Object inadvertently left in after surgery Air embolism Blood incompatibility Catheter associated urinary tract infection Pressure ulcer (decubitus ulcer) Vascular catheter associated infection Surgical site infection- Mediastinitis (infection in the chest) after coronary artery bypass graft surgery Certain types of falls and trauma Medicare “Never Events” Proposed Surgical-site infections after total knee replacement, laparoscopic gastric bypass and gastroenterostomy, or ligation and stripping of varicose veins. Legionnaires’ disease Extreme blood sugar derangement Iatrogenic pneumothorax Delirium Ventilator-associated pneumonia Deep vein thrombosis/Pulmonary Embolism Staphylococcus aureus septicemia Clostridium difficile associated disease Quality Gap Wide variations in utilization Wide variations in outcomes Leapfrog, Etc. NSQIP CMS Pay for Performance Geographic Variations in Utilization of Healthcare From: Primer on Geographic Variation in Healthcare http://www.acponline.org/ Hospital Variations in Quality NSQIP ACS National Surgery Quality Improvement Program Risk-adjusted Outcomes O/E ratios http://www.acsnsqip.org/ How do we improve outcomes and prevent harmful errors? How do we improve outcomes and prevent harmful errors? * And what do we do when a bad event occurs Three Strategies for Improving Outcomes and Preventing Errors 1. 2. 3. Training and simulation Real-time data collection, analysis, and feedback Implementation of new technology Three Strategies for Improving Outcomes and Preventing Errors 1. 2. 3. Training and simulation Real-time data collection, analysis, and feedback Implementation of new technology Training and Education What is the current model? Lectures/Seminars On-the-job What is wrong with the current model? Disorganized Time consuming Inconsistent with needs of adult learners Costly Assessment/Certification difficult Impacts patient safety Adult learning theory 3-stage learning process Cognitive stage Associative stage Autonomous stage Skill retention Value of repetition Requires appropriate guidance Kneebone 2001 Med Educ Learning in the OR Surgery residents Annual cost $53 million $54.23 per case 12.64 minutes $47,790 per graduating chief resident 197 additional hours 92% of Program Directors feel training outside OR is necessary Bridges and Diamond 1999 Am J Surg Haluck et al. 2001 J Am Coll Surg Simulation-based Training What is simulation? Simplified reality Learner-centered Needs of learner, not of patient Repeated practice Immediate feedback At own pace “Permission to fail” Objective evidence of performance “Competency-based” Gorman et al. 2000 Am J Surg Kneebone and ApSimon 2001 Med Educ Simulation in Industry Automobile Nuclear Power Industry Bus Locomotive Recreation Industry 777 Airline Industry Military Simulators in aviation All pilots and crew must train and be certified on a flight simulator Specific to each aircraft Focus on safety Exposure to unusual or unexpected situations Skill Training Not just for skill training… Team training Crew Resource Management Error Disclosure Team Training Team Training Error Disclosure Training May 18, 2008 Not just for trainees… Pre-procedure warm-up Maintenance of Skills Introduction of new technology Introduction of new procedures Credentialing Team improvement Credentialing Fundamentals of Laparoscopic Surgery Joint program of ACS/SAGES Interactive multimedia Practice exercises Well-validated Flsprogram.org Team Improvement Harvard Risk Management Foundation 10% Malpractice discount Team training Factors degrading L&D performance Communication strategies in Event Management Strategies for debriefing events and disclosing medical errors Developing a culture of safety http://harvardmedsim.org Barriers to Adoption Lack of familiarity Cost Limited time for non-clinical activities Limited proof of efficacy H. Res 487 (EH) Bill Number: H. Res. 487 (EH) Bill Title: Whereas the United States of America is a great and prosperous Nation, and modeling and simulation contribute significantly to that greatness and prosperity; (Engrossed as Agreed to or Passed by House) Sponsor: Rep Forbes, J. Randy Introduced: 2007/06/14 Latest Major Action: 2007/07/16 Passed/agreed to in House. Status: On motion to suspend the rules and agree to the resolution Agreed to by voice vote. HRES 487 EH H. Res. 487 In the House of Representatives, U. S., July 16, 2007. Whereas the United States of America is a great and prosperous Nation, and modeling and simulation contribute significantly to that greatness and prosperity; Whereas modeling and simulation in the United States is a unique application of computer science and mathematics that depends on the validity, verification, and reproducibility of the model or simulation, and depends also on the capability of the thousands of Americans in modeling and simulation careers to develop these models; Whereas members of the modeling and simulation community in government, industry, and academia have made significant contributions to the general welfare of the United States, and while these contributions are too numerous to enumerate, modeling and simulation efforts have contributed to the United States by– onducted live and required 5 years, 14,000 personnel, and $250,000,000 for development; (4) preserving countless human lives, as well as military and civilian aircraft, ships, and other vehicles through the rehearsal of repeatable, simulated emergencies that otherwise could not have been practiced; (5) increasing the quality of health care through the development of medical simulation training, which led the Food and Drug Administration to require such training for physicians before certain high-risk procedures to treat heart disease and strokes; What are we doing at the UW? Skills training for all residents Defined Curriculum Defined performance targets Team training Code/Rapid Response teams Error disclosure OB/GYN Credentialing FLS certification Central Line Placement Research Tie education to patient outcomes Three Strategies for Improving Outcomes and Preventing Errors 1. 2. 3. Training and simulation Real-time data collection, analysis, and feedback Implementation of new technology Rationale You can’t fix what you can’t measure STEP 1 Capture the Data STEP 2 Analyze the Data STEP 3 Report the Data STEP 4 Act on the Data acsnsqip.org NSQIP Data Collection DEMOGRAPHICS SURGICAL PROFILE 9 variables 9 variables PRE-OPERATIVE DATA 40 clinical variables 13 laboratory variables 18 clinical variables 3 occurrence variables 20 occurrence variables 12 laboratory variables 9 discharge variables INTRA-OPERATIVE DATA POST-OPERATIVE DATA NSQIP Data Analysis NSQIP Act VA NSQIP Results 1991 – 2001 27% decline in post-operative mortality 45% drop in post-operative morbidity median post-operative length of stay fell from 9 to 4 days patient satisfaction improved NSQIP Example: Albumin % complications 80 70 60 50 40 30 20 10 0 <2 (n=22) 2-2.4 (n=25) 2.5-2.9 (n=28) 3-3.4 (n=78) 3.5-4 (n=161) >4 (n=125) % complications NSQIP Example: Albumin Nutrition Screening Tool Unintended Weight Loss >20lb BMI <20 Factor are present than limit oral nutrition intake: Prolonged nausea or vomiting Chronic diarrhea Anorexia Dysphasia Organ dysfunction ASA III or IV Albumin ≤3 Prealbumin ≤10 Process Measures On-time antibiotic prophylaxis Hand washing VTE prophylaxis How can we get these done? IT Electronic Orders Medication checks Standardized Protocols Checklists Checklist Checklist Checklist SCOAP Surgical Care and Outcomes Assessment Program WA State – 25 Hospitals Record compliance with Process Measures and Outcomes Report to hospitals www.surgicalcoap.org Three Strategies for Improving Outcomes and Preventing Errors 1. 2. 3. Training and simulation Real-time data collection, analysis, and feedback Implementation of new technology Fundamental Changes Technology Information, Energy, Imaging, Robotics, Nanotech, Pharm Breakdown of traditional boundaries Total integration of systems Rooms, instruments, supplies become “intelligent” Individual roles expand and interact (nurse logistician) Melding of traditionally separate functions (imaging, surgery, vascular, GI) Robotics Why robotic surgery? Humans are imperfect Dexterity Tremor Reproducibility Limited to innate senses Disconnect between knowledge and skill Surgery is hard What does robotic surgery offer? Increased dexterity Increase degrees of freedom Motion Scaling Reduce tremor Robotics Big Expensive Limited use What do we want? Small Cheap Fast Better “Supranormal Performance” Faster Stronger More precise More reliable Integration of imaging, anatomy, and physiology Integration of Biosensors What do we want? Increase Reproducibility (reliability) Semi-autonomous or autonomous behavior Increase Speed Semi-autonomous or autonomous behavior What do we want? Improve on our senses Patient-specific data Identification of tissues Tissue damage sensing Integration of Biosensors Automatic tumor targeting Image-Guided Surgery Multiple individual robots Dimitry Oleynikov MD University of Nebraska Snake-like robots Howie Choset PhD Carnegie Mellon Miniaturization Miniaturization Microelectromechanical systems Untethered, Electrostatic, Globally Controllable MEMS Micro-Robot Bruce Randall Donald – Duke University 60 µm by 250 µm by 10 µm two distinct motion gaits (forward motion and turning) Miniaturization Micro-forceps Sun Yu, University of Toronto Capable of manipulating single cells $10/device Automation Potential to: Increase speed Increase precision Increase reliability Automation 2007 METI Robot of the Year Fanuc industrial robot Automation Automotive – DARPA Urban Challenge 2007 Automation Semi-autonomous performance of surgical tasks Grasping Retraction Suturing Knot-Tying “Point and Click Surgery” Automation “McSleepy” Thomas Hemmerling, McGill University Closed-loop system Calculates and automatically administers drugs Automation Biosensors Augment human abilities Compensate for loss of haptics Sense tissue type, oxygenation, damage Identify tumors Guide therapy Breakdown of Boundaries Image-guided Surgery Catheter-based intervention NOTES Marriage of endoscopy and surgery NOTES NOTES Where will we be? Operating Room Cath Lab Radiology Suite Endoscopy Suite Where will we be? Operating Room Cath Lab Radiology Suite Endoscopy Suite All of the Above If you look out into the long-term future and what you see looks like science fiction, it might be wrong. But if it doesn't look like science fiction, it's definitely wrong. Christine Peterson Foresight Nanotech Institute Contacts awright2@u.washington.edu www.isis.washington.edu