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How To Drive Clinical Improvement Programs That Get Results - HAS Session 20
The document outlines a clinical program framework aimed at driving sustained clinical improvement through organized care delivery, integrated teams, and effective learning methods. Key principles focus on selecting the right initiatives, understanding variation in outcomes, ensuring data quality, and engaging appropriate influencers to lead change. The strategies discussed emphasize data-driven decision-making and collaboration among clinical and technical teams for enhanced patient care outcomes.
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How To Drive Clinical Improvement Programs That Get Results - HAS Session 20
- 1. Session #20 Howto Drive Clinical Improvement That Get Results Tom Burton And the Catalyst Academy Education Team
- 2. 2 What isa Clinical Program? • Organized around care delivery processes • Permanent integrated team of clinical and analytics staff • Creates a iterative continuous learning environment • Focus is on sustained clinical outcome improvement (not revenue growth) • Not a Clinical Service Line (although you can Leverage Service Lines as a good start)
- 3. 3 Organizational AGILETeams • Permanent teams that meet weekly • Integrated clinical and technical members • Supports multiple care process families MD Lead RN SME = SubjectMatter Expert = Data Capture = DataProvisioning & Visualization = Data Analysis Women & Children’s Clinical Program Guidance Team Pregnancy Knowledge Manager MD Lead RN SME Data Architect Guidance Team MD lead RN, Clin Ops Director Application Administrator MD Lead RN SME Normal Newborn Gynecology
- 4. 4 Incorporating themost effective learning methods Teach Others - 90% Practice by Doing- 75% Discussion Group- 50% Demonstration- 30% Audiovisual- 20% Reading- 10% Lecture- 5% % represents average information retained through the particular learning method ‒ Duke University 0 50 100
- 5. 5 Session Objective 4 Learning Experiences Clinical Programs that Get Results Principles Choose the right initiative Understand variation Improve data quality Choose the right influencers
- 6. 6 Choose theright initiative
- 7. 7 Deal orNo Deal Exercise
- 8. 8 DEAL orNO DEAL
- 9. 9 First Principle • Picking an improvement opportunity randomly is like playing traditional DEAL or NO DEAL • You might get lucky • Choosing the loudest physician or the choosing based on non-data driven reason can dis-engages other MDs and use scarce analytical resources on projects that may not be the best investment • It takes about as much effort to work on a large process as it does on a small process
- 10. 10 Pareto Example:Resources Consumed • 80% of all in-patient resources are represented by 21 Care Process Families 10 Cumulative % % of Total Resources Consumed for each clinical work process Key Findings: Analytic System 50% • 50% of all in-patient resources are represented by 7 Care Process Families 7 CPFs Number of Care Process Families (e.g., ischemic heart disease, pregnancy, bowel disorders, spine, heart failure) 21 CPFs 80%
- 11. 11 Dr. J. 15 Cases $60,000 Avg. Cost Per Case Mean Cost per Case = $20,000 $40,000 x 15 cases = $600,000 opportunity Total Opportunity = $600,000 Total Opportunity = $1,475,000 $35,000 x 25 cases = $875,000 opportunity Total Opportunity = $2,360,000 Total Opportunity = $3,960,000 Cost Per Case, Vascular Procedures Analytic System
- 12. Improvement Approach -Prioritization 12 Poor Outcomes Excellent Outcomes # of Cases Poor Outcomes Excellent Outcomes # of Cases Excellent Outcomes # of Cases Poor Outcomes Excellent Outcomes # of Cases Poor Outcomes 1 2 3 4 High Variability Low Low Resource Consumption High 12
- 13. Improvement Approach -Prioritization 13 Poor Outcomes Excellent Outcomes # of Cases Poor Outcomes Excellent Outcomes # of Cases Excellent Outcomes # of Cases Poor Outcomes Excellent Outcomes # of Cases Poor Outcomes 1 2 3 4 High Variability Low Low Resource Consumption High 13
- 14. 14 Internal Variationversus Resource Consumption Y- Axis = Internal Variation in Resources Consumed 3 4 Bubble Size = Resources 1 2 Consumed X Axis = Resources Consumed Bubble Color = Clinical Domain
- 15. 15 DEAL orBETTER DEAL 15
- 16.
- 17. 17 The PopsicleBomb Exercise Timer 11234510123456789M101234567890123456789 When you’re finished note your time and enter it in the HAS app – Poll Question 1
- 18. 18 Variation inResults • Corp Analytics – shows results
- 19. 19 Less EffectiveApproach to improvement: “Punish the Outliers” # of Cases Current Condition • Significant Volume • Significant Variation # of Cases Option 1: “Punish the Outliers” or “Cut Off the Tail” Strategy • Set a minimum standard of quality • Focus improvement effort on those not meeting the minimum standard Mean Focus on Minimum Standard Metric Poor Outcomes Excellent Outcomes Poor Outcomes Excellent Outcomes 1 box = 100 cases in a year
- 20. 20 Effective Approachto improvement: Focus on “Better Care” Poor Outcomes Excellent Outcomes # of Cases Current Condition • Significant Volume • Significant Variation Excellent Outcomes # of Cases Option 2: Identify Best Practice “Narrow the curve and shift it to the right” Strategy • Identify evidenced based “Shared Baseline” • Focus improvement effort on reducing variation by following the “Shared Baseline” • Often those performing the best make the greatest improvements Mean Focus on Best Practice Care Process Model Poor Outcomes 1 box = 100 cases in a year
- 21. 21 Round 2 Timer 11234510123456789M101234567890123456789 When you’re finished note your time and enter it in the HAS app – Poll Question 2
- 22. 22 Reduced Variationin Results • Corp Analytics – shows results
- 23. 23 Improve DataQuality
- 24. 24 The WaterStopper Exercise
- 25. 25 Information Management DATA CAPTURE • Acquire key data elements • Assure data quality • Integrate data capture into operational = Subject Matter Expert = Data Capture = Data Provisioning = Data Analysis 25 25 workflow DATA ANALYSIS • Interpret data • Discover new information in the data (data mining) • Evaluate data quality DATA PROVISIONING • Move data from transactional systems into the Data Warehouse • Build visualizations for use by clinicians • Generate external reports (e.g., CMS) Knowledge Managers (Data quality, data stewardship and data interpretation) Application Administrators (optimization of source systems) Data Architects (Infrastructure, visualization, analysis, reporting) Fix it Here Not Here Not Here
- 26. 26 Data CaptureQuality Principles • Accuracy Does the data match reality? Example: Operating Room Time Stamps • Timeliness What is the latency of the data capture? Example: Billing data delay; end of shift catch-up • Completeness How often is critical data missing? Example: HF Ejection Fraction
- 27. 27 Challenges withData “Scrubbing” Analyst time spent on re-working scrubbing routines Root cause never identified Early binding vs. late binding – what you consider dirty data may actually be useful for others analyzing process failures. Using data to punish vs. data to learn – punish strategy promotes hiding the problem so clinicians don’t look bad
- 28. 28 Choose theright influencers
- 29. 29 Paul Revere'sride Exercise
- 30. 30 Revere vs.Dawes Paul Revere "Revere knew exactly which doors to pound on during his ride on Brown Beauty that April night. As a result, he awakened key individuals, who then rallied their neighbors to take up arms against the British.” William Dawes "In comparison, Dawes did not know the territory as well as Revere. As he rode through rural Massachusetts on the night of April 18, he simply knocked on random doors. The occupants in most cases simply turned over and went back to sleep." Diffusion of Innovations (Free Press, 2003) by Everett M. Rogers
- 31. 31 Innovators. Recruit innovators to re-design care delivery early adopters Innovators early majority laggards (never adopters) late majority * Adapted from Rogers, E. Diffusion of Innovations. New York, NY: 1995. processes (like Revere) Early adopters. Recruit early adopters to chair improvement and to lead implementation at each site. (key individuals who can rally support) The Chasm N = number of individuals in group N N = number needed to influence group (but they must be the right individuals)
- 32. 32 W&N SmallTeams (Designs Innovation) • Meet weekly in iteration planning meeting • Build DRAFT processes, metrics, interventions • Present DRAFT work to Broader Teams OB Early Adopters Innovators Guidance Team (Prioritizes Innovations) • Meet quarterly to prioritize allocation of technical staff • Approves improvement AIMs OB Newborn GYN • Reviews progress and removes road blocks W&N Innovators Innovators Broad Teams (Implements Innovation) • Broad RN and MD representation across system • Meet monthly to review, adjust and approve DRAFTs • Lead rollout of new process and measurement W&N OB W&N W&N Early Adopters Innovators Early Adopters
- 33. 33 Organizational AGILETeams • Permanent teams • Integrated clinical and technical members • Supports multiple care process families • Choose innovators and early adopters to lead MD Lead RN SME = SubjectMatterExpert = Data Capture = DataProvisioning & Visualization = Data Analysis Women & Children’s Clinical Program Guidance Team Pregnancy Knowledge Manager MD Lead RN SME Data Architect Guidance Team MD lead RN, Clin Ops Director Application Administrator MD Lead RN SME Normal Newborn Gynecology Innovators Early Adopters
- 34. 34 How toidentify innovators and early adopters • Ask Innovators (inventors) - Who are the top three MDs in our group who are likely to invent a better way to deliver care? Early Adopters (thought leaders) - When you have a tough case who are the top three MDs you trust and would go to for a consult? • Fingerprinting selection process Invite innovators to choose identify their top three MD choices from the early adopters to lead the Clinical Program
- 35. 35 Conclusion –TEACH OTHERS
- 36. 36 Teach OthersExercise Deal or No Deal - Choose the right initiative - Prioritize based on process size and variation Popsicle Bomb - Understand variation - Measure variation and standardize processes Water Stopper - Improve data quality - Fix the problem at the source Paul Revere’s Ride - Choose the right influencers - Identify Innovators and Early adopters to accelerate diffusion of innovation Take 1 minute and describe the purpose of each exercise to your neighbor, then swap and let them teach you Timer 11234510123456789M101234567890123456789 11234510123456789M101234567890123456789
- 37. 37 Exercise EffectivenessQ1 Overall, how effective were the exercises in explaining the principles? 1) Not effective 2) Somewhat effective 3) Moderately effective 4) Very effective 5) Extremely effective
- 38. 38 Exercise EffectivenessQ2 How effective was the Deal or No Deal Exercise at teaching the principle of prioritizing based on process size and variation? 1) Not effective 2) Somewhat effective 3) Moderately effective 4) Very effective 5) Extremely effective
- 39. 39 Exercise EffectivenessQ3 How effective was the Popsicle Bomb Exercise at teaching the principle of understanding variation and standardizing processes? 1) Not effective 2) Somewhat effective 3) Moderately effective 4) Very effective 5) Extremely effective
- 40. 40 Exercise EffectivenessQ4 How effective was the Water Stopper Exercise at teaching the principle of fixing data quality issues at the source? 1) Not effective 2) Somewhat effective 3) Moderately effective 4) Very effective 5) Extremely effective
- 41. 41 Exercise EffectivenessQ5 How effective was the “Paul Revere Ride” exercise at teaching the principle of choosing the right influencers based on their capabilities as innovators and early adopters? 1) Not effective 2) Somewhat effective 3) Moderately effective 4) Very effective 5) Extremely effective
- 42. 42 Exercise EffectivenessQ6 Are you interested in running these same exercises in your organizations? a) Yes b) No
- 43. Analytic Insights Questions& A Answers
- 44. Session Feedback Survey 44 1. On a scale of 1-5, how satisfied were you overall with this session? 1) Not at all satisfied 2) Somewhat satisfied 3) Moderately satisfied 4) Very satisfied 5) Extremely satisfied 2. What feedback or suggestions do you have? 3. On a scale of 1-5, what level of interest would you have for additional, continued learning on this topic (articles, webinars, collaboration, training)? 1) No interest 2) Some interest 3) Moderate interest 4) Very interested 5) Extremely interested
Editor's Notes
- #45 Follow up group participation 1Would you like to participate in a follow up group on this topic that would meet 2-3 times next year to share progress, challenges and best practices? (Yes, No)