How to Use Data to Improve Patient Safety: A Two-Part Discussion
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The document discusses the use of data and analytics to improve patient safety, highlighting the increase in preventable medical injuries and calling attention to the disconnect between safety and quality metrics. It outlines historical context, roadblocks to improvement, and presents various organizational poll results regarding the effectiveness of patient safety programs. The discussion emphasizes the need for real-time safety analytics and proactive capabilities to prevent harm in healthcare settings.
How to Use Data to Improve Patient Safety: A Two-Part Discussion
- 1. Stanley L Pestotnik, MS, RPh Valere Lemon, MBA, RN How to Use Data to Improve Patient Safety: A Two-Part Discussion
- 2. © 2016 Health Catalyst Proprietary and Confidential Agenda 2 History and myths about patient safety and quality. Roadblock to patient safety. How data and analytics can help.
- 3. © 2016 Health Catalyst Proprietary and Confidential3 The prevention of harm caused by errors of commission and omission. Patient Safety Defined: Adverse event defined: An event that results in unintended harm (injury) to the patient by an act of commission or omission rather than the underlying disease or condition of the patient. Source: Institute of Medicine, Patient Safety: achieving a new standard for care, The National Academies Press, 2004
- 5. © 2016 Health Catalyst Proprietary and Confidential Patient Safety 5 The human faces
- 6. © 2016 Health Catalyst Proprietary and Confidential Pioneers in Patient Safety 6
- 7. © 2016 Health Catalyst Proprietary and Confidential 0 2 4 6 8 10 12 14 16 18 1841 1842 1843 1844 1845 1846 1847 1848 1849 1850 MaternalMortality First Second Intervention Semmelweis IP, 1861 May 15, 1847 Maternal Mortality Rates First and second obstetric clinics General Hospital of Vienna, 1841-1850 7
- 8. © 2016 Health Catalyst Proprietary and Confidential Poll Question #1 Within the United States, since the 1999 IOM report on patient safety, preventable harm in the US has: 79 respondents a. Decreased 10 fold – 7% b. Decreased by half – 20% c. Stayed the same – 28% d. Increased by half – 28% e. Increased 10 fold – 16% 8
- 9. © 2016 Health Catalyst Proprietary and Confidential Please rate your organization’s use of data to drive patient safety and quality improvement. 76 Respondents a. Extremely effective – 5% b. Very effective – 19% c. Effective – 41% d. Not very effective – 27% e. Ineffective – 8% Poll Question #2 9
- 10. © 2016 Health Catalyst Proprietary and Confidential When using data to improve patient safety and quality, the data in my organization is: (check all that apply) 75 Respondents a. Timely – 34% b. Automated – 42% c. Actionable – 45% d. Using predictive analytics – 23% e. None of the above – 29% Poll Question #3 10
- 11. © 2016 Health Catalyst Proprietary and Confidential Preventable medical injuries are actually on the rise. Ten times more preventable harm since 1999. • 400,000 lives per year. • >$100B annually. Patient harm is the 3rd leading cause of death. Dispelling Myths about Patient Safety 11 Based on our estimate, medical error is the 3rd most common cause of death in the US. However, we’re not even counting this – medical error is not recorded on US death certificates. Causes of death—U.S., 2013 Heart disease 611k Cancer 585k Medical error 251k COPD 149k All causes 2,597 k Suicide 41k Firearms 34k Motor vehicles 34k
- 12. © 2016 Health Catalyst Proprietary and Confidential 12 Information management in EHRs Unrecognized patient deterioration Implementation and use of clinical decision support Test result reporting and follow-up Antimicrobial stewardship Patient identification Opioid administration and monitoring in acute care Behavioral Health issues in non- Behavioral-Health settings Management of new oral anticoagulants Inadequate systems or processes to improve safety and quality 2017201620152014 Health IT configurations and organizational workflow that do not support each other Patient identification errors Inadequate management of behavioral health issues in non- Behavioral-Health settings Inadequate cleaning and disinfection of flexible endoscopes Inadequate test result reporting and follow up Inadequate monitoring for respiratory depression in patients prescribed opioids Medication errors related to pounds and kilograms Unintentionally retained objects despite correct count Inadequate antimicrobial stewardship Failure to embrace a culture of safety Alarm hazards: inadequate alarm configuration policies and practices Data integrity: incorrect or missing data in EHRs and other health IT systems Managing patient violence Mix-up of IV lines leading to misadministration of drugs and solutions Care coordination events related to medication reconciliation Failure to conduct independent double checks independently Opioid-related events Inadequate reprocessing of endoscopes and surgical instruments Inadequate patient handoffs related to patient transport Medication errors related to pounds and kilograms Data integrity failures with health information technology systems Poor care coordination with patient’s next level of care Test results reporting errors Drug shortages Failure to adequately manage behavioral health patients in acute care settings Mislabeled specimens Retained devices and retrieved fragments Patient falls while toileting Inadequate monitoring for respiratory depression in patients taking opioids Inadequate reprocessing of endoscopes and surgical instruments
- 13. © 2016 Health Catalyst Proprietary and Confidential Poll Question #4 13 How effective are your organization’s patient safety improvement programs? 76 Respondents a) Not at all effective – 3% b) Somewhat effective – 31% c) Moderately effective – 40% d) Very effective – 13% e) Unsure or not applicable – 14%
- 14. © 2016 Health Catalyst Proprietary and Confidential Berwick’s Roadblocks to Improving Patient Safety 14 Displacement by other concerns. Thinking incentives will improve quality. Metrics Glut. Illusion of completeness. Separation of safety from quality. System literacy.
- 15. © 2016 Health Catalyst Proprietary and Confidential Creating a System of Learning and Safety 15
- 16. © 2016 Health Catalyst Proprietary and Confidential16 Socio- Economic Financial Admin Clinical (EHR/Device) Patient Reported Active Surveillance Data Operating System Normalize Standardize Optimize Algorithms Thoughtflow Text analytics Machine learning 1. Triggers 2. Clinical Confirmation 3. RCA with Attribution Insight & Learning Dashboards Reports Exports Prediction and Prevention Actionable Interventions & Sustained outcomes Patient Safety Surveillance Value Chain:
- 17. © 2016 Health Catalyst Proprietary and Confidential How Data and Analytics Can Improve Patient Safety 17 Reactive capabilities Automated triggers identify potential harm. Proactive capabilities Predictive analytics identifies interventions to reduce or prevent harm. Full integration capability Safety tool integrated across workflow tools across the health system.
- 18. © 2016 Health Catalyst Proprietary and Confidential Using Data and Analytics to Improve Patient Safety 18 Analytic efficiencies – automation and integration. New insights for performance improvement. 35% decrease in HACs. 50% decrease in CAUTI rate. 75% decrease in manual chart reviews. 5.3% percentage point reduction (a 21.7% relative reduction) in incidence of bleeding after PCI and $1.8M cost reduction. 7% relative improvement in percentage of patients therapeutic within 24 hours of heparin therapy; decreased incidence of major bleeds.
- 19. © 2016 Health Catalyst Proprietary and Confidential Using Data and Analytics to Improve Patient Safety 19
- 20. © 2016 Health Catalyst Proprietary and Confidential20
- 21. © 2016 Health Catalyst Proprietary and Confidential21
- 22. © 2016 Health Catalyst Proprietary and Confidential22
- 23. © 2016 Health Catalyst Proprietary and Confidential23 Pain Management Trigger Morphine Milligram Equivalents per day > 50 Population Analytic
- 24. © 2016 Health Catalyst Proprietary and Confidential Pain Management Trigger Morphine Milligram Equivalents per day > 50 Patient Analytic 24
- 25. © 2016 Health Catalyst Proprietary and Confidential25 The Future of Safety A Sociotechnical Solution Retrospective safety information • Detect fraction of all events. • Labor intensive and unwieldy. Frontline drenched with alerts • More burn-out. • More cynicism. • More risk. Poor clinical learning systems • Hard to use to change patterns. Other issues • Safety isolated from hospital business. • Safety data black-hole. Health Catalyst Approach Existing Systems Real-time safety analytics • Measure, trend, and learn from all defects. • Predict harm in specific patients and populations. Intelligent & clinically appropriate • Targeted intervention. • System of trust. • Controlled risk. Data-driven learning systems • Integration of culture and analytics. • Learning boards (organizational, unit and patient). • Focus on integrated value. • Transparency (sharing safety data with patients).
- 26. © 2016 Health Catalyst Proprietary and Confidential Date: June 28th Time: 1:00-2:00 PM EST Attendees will learn how to: • Get upstream of patient safety events to avoid harm and downstream costs. • Identify key sources of patient safety data. • Integrate patient safety data into existing quality improvement projects. • Improve patient safety using real-time safety analytics. Join for the Second Part of this Discussion 26
- 27. © 2016 Health Catalyst Proprietary and Confidential Healthcare Analytics Summit 17 ERIC J. TOPOL Author, The Patient Will See You Now and The Creative Destruction of Medicine. Director, Scripps Translational Science Institute DAVID B. NASH, MD. MBA Dean, Jefferson School of Population Health JOHN MOORE Founder and Managing Partner, Chilmark Research ROBERT A. DEMICHIEI Executive Vice President and Chief Financial Officer, University of Pittsburgh Medical Center THOMAS D. BURTON Co-Founder, Chief Improvement Officer, and Chief Fun Officer, Health Catalyst DALE SANDERS Executive Vice President, Product Development, Health Catalyst THOMAS DAVENPORT Author , Consultant Competing on Analytics*, , Analyitcs at Work, Big Data at Work, Only Humans Need Apply:Winners and Losers in the Age of Smart Machines. *Recognized by Harvard Business Review editors as one the most important management ideas of the past decade, one of HBR’s ten must-read articles in that magazine’s 90-year history. Summit highlights Industry Leading Keynote Speakers We’ll hear from well-known healthcare visionaries. We’ll also hear from two C-level executives leading large healthcare organizations. CME Accreditation For Clinicians HAS 17 will again qualify as a continuing medical education (CME) activity. 30 Educational, Case Study, and Technical Sessions We have the most comprehensive set of breakout sessions of any analytics summit. Our primary breakout session focus is giving you detailed, practical “how to” learning examples combined with question and opportunities. The Analytics Walkabout Back by popular demand, the Analytics Walkabout will feature 24 new projects highlighting a variety of additional clinical, financial, operational, and workflow analytics and outcomes improvement successes. Analytics-driven, Hands-on Engagement for Teams and Individuals Analytics will continue to flow through the three-day summit touching every aspect of the agenda. Networking and Fun We’ll provide some new innovative analytics-driven opportunities to network while keeping our popular fun run and walk opportunities and dinner on the down. Sept. 12-14, 2017 Grand America Hotel Salt Lake City, UT