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#HASummit14 Session #20 How to Drive Clinical Improvement That Get Results Tom Burton And the Catalyst Academy Education Team.

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Presentation on theme: "#HASummit14 Session #20 How to Drive Clinical Improvement That Get Results Tom Burton And the Catalyst Academy Education Team."— Presentation transcript:

1 #HASummit14 Session #20 How to Drive Clinical Improvement That Get Results Tom Burton And the Catalyst Academy Education Team

2 #HASummit14 2 What is a 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 #HASummit14 3 Organizational AGILE Teams = Subject Matter Expert = Data Capture = Data Provisioning & Visualization = Data Analysis Women & Children’s Clinical Program Guidance Team Pregnancy MD Lead RN SME Knowledge Manager Data Architect Application Administrator RN, Clin Ops Director Guidance Team MD lead Normal Newborn MD Lead RN SME Gynecology MD Lead RN SME Permanent teams that meet weekly Integrated clinical and technical members Supports multiple care process families

4 #HASummit14 4 Incorporating the most 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

5 #HASummit14 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 #HASummit14 6 Choose the right initiative

7 #HASummit14 7 Deal or No Deal Exercise

8 #HASummit14 8 DEAL or NO DEAL

9 #HASummit14 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 9

10 #HASummit14 10 Pareto Example: Resources Consumed Cumulative % % of Total Resources Consumed for each clinical work process Key Findings: 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) 80% of all in-patient resources are represented by 21 Care Process Families 21 CPFs 80% Analytic System

11 #HASummit14 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 #HASummit14 12 Excellent OutcomesPoor Outcomes # of Cases Excellent Outcomes # of Cases Poor Outcomes 1 2 3 4 Variability High Low Resource Consumption LowHigh Improvement Approach - Prioritization 12

13 #HASummit14 13 Excellent OutcomesPoor Outcomes # of Cases Excellent Outcomes # of Cases Poor Outcomes 1 2 3 4 Variability High Low Resource Consumption LowHigh Improvement Approach - Prioritization 13

14 #HASummit14 14 Internal Variation versus Resource Consumption Y- Axis = Internal Variation in Resources Consumed Bubble Size = Resources Consumed Bubble Color = Clinical Domain X Axis = Resources Consumed 1 2 3 4

15 #HASummit14 15 DEAL or BETTER DEAL

16 #HASummit14 16 Understand Variation

17 #HASummit14 17 The Popsicle Bomb Exercise 1M59585756555453525150494847464544434241403938373635343332313029282726252423222120191817161514131211109876543210 Timer When you’re finished note your time and enter it in the HAS app – Poll Question 1

18 #HASummit14 18 Variation in Results Corp Analytics – shows results 18

19 #HASummit14 19 Less Effective Approach 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 Excellent OutcomesPoor Outcomes Excellent Outcomes Poor Outcomes 1 box = 100 cases in a year

20 #HASummit14 20 Effective Approach to improvement: Focus on “Better Care” Excellent OutcomesPoor 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 #HASummit14 21 Round 2 21 1M59585756555453525150494847464544434241403938373635343332313029282726252423222120191817161514131211109876543210 Timer When you’re finished note your time and enter it in the HAS app – Poll Question 2

22 #HASummit14 22 Reduced Variation in Results Corp Analytics – shows results 22

23 #HASummit14 23 Improve Data Quality

24 #HASummit14 24 The Water Stopper Exercise

25 #HASummit14 25 Information Management 25 DATA CAPTURE Acquire key data elements Assure data quality Integrate data capture into operational 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) = Subject Matter Expert = Data Capture = Data Provisioning = Data Analysis Fix it Here Not Here

26 #HASummit14 26 Data Capture Quality 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 26

27 #HASummit14 27 Challenges with Data “Scrubbing” 27 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 #HASummit14 28 Choose the right influencers

29 #HASummit14 29 Paul Revere's ride Exercise

30 #HASummit14 30 Revere vs. Dawes 30 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 #HASummit14 31 Innovators early adopters early majority laggards (never adopters) * Adapted from Rogers, E. Diffusion of Innovations. New York, NY: 1995. late majority Innovators. Recruit innovators to re- design care delivery 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 #HASummit14 32 = Subject Matter Expert = Data Capture = Data Provisioning & Visualization = Data Analysis

33 #HASummit14 33 Organizational AGILE Teams = Subject Matter Expert = Data Capture = Data Provisioning & Visualization = Data Analysis Women & Children’s Clinical Program Guidance Team Pregnancy MD Lead RN SME Knowledge Manager Data Architect Application Administrator RN, Clin Ops Director Guidance Team MD lead Normal Newborn MD Lead RN SME Gynecology MD Lead RN SME Permanent teams Integrated clinical and technical members Supports multiple care process families Choose innovators and early adopters to lead Innovators Early Adopters

34 #HASummit14 34 How to identify 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 34

35 #HASummit14 35 Conclusion – TEACH OTHERS

36 #HASummit14 36 Teach Others Exercise  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 1M59585756555453525150494847464544434241403938373635343332313029282726252423222120191817161514131211109876543210 Timer 1M59585756555453525150494847464544434241403938373635343332313029282726252423222120191817161514131211109876543210

37 #HASummit14 37 Exercise Effectiveness Q1 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 37

38 #HASummit14 38 Exercise Effectiveness Q2 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 38

39 #HASummit14 39 Exercise Effectiveness Q3 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 39

40 #HASummit14 40 Exercise Effectiveness Q4 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 40

41 #HASummit14 41 Exercise Effectiveness Q5 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 41

42 #HASummit14 42 Exercise Effectiveness Q6 Are you interested in running these same exercises in your organizations? a) Yes b) No 42

43 #HASummit14 Analytic Insights A Questions & Answers

44 #HASummit14 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 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 2.What feedback or suggestions do you have?

45 Healthcare Analytics Summit 14 Script/Description of Exercise (Hidden) Many of you may have seen the popular game show on TV: Deal or No Deal – where contestants get to randomly choose from numbered briefcases held by models which contain anywhere from 1 cent to 1 million dollars. The contestants negotiate with the banker to decide whether to take the deal offered or continue randomly picking briefcases. We are going to play a similar version today but our briefcases are contain potential $ savings from implementing clinical programs for continuous improvement. As we invite our Catalyst Analytical Nerds, sorry no models, to bring the briefcases out we need a volunteer from the audience, this starts the learning by doing active participation ;-) (Choose someone from the audience while the 26 briefcases are brought out by Catalyst Team Members dressed in tan pants, white catalyst shirts and nerd glasses with tape on them. Thank you for volunteering, what’s your name? (Jane Doe) Great Jane thanks for playing Deal or No Deal today. Just so you know there is a total of $XXX in cost reduction opportunity that you can win for your organization today. Because we have a limited amount of time and because your organization has a limited # of trained improvement resources I’m going to ask you right of the bat to just pick 6 briefcases we encourage you to ask the audience for help in choosing – (she chooses three briefcases as she pick, the team members come forward in a row off their riser location) Ok let see what savings you have achieved? (Open the 6 briefcases and we quickly calculate the total amount for the 6 brief cases she has chosen and display it on the screen as well as how much opportunity she just gave up by not working on the other 20 process. $XXX (it’s a big number) The Banker Calls. (Wa Wa Wa) I just been authorized to offer you a DEAL. Here’s the DEAL: You can say DEAL; and take this improvement savings for these 6 processes and we will give you this nice parting gift of a Health Catalyst ball cap; However if you say NO DEAL, we will put these 6 briefcases back in the mix and shuffle them into a data driven layout and you’ll have the opportunity to pick again, but this time only pick three brief cases from all 26 briefcases; (Hopefully she chooses NO DEAL) 45

46 Healthcare Analytics Summit 14 Script/Description of Exercise (Hidden) Ok the catalyst nerds are being organized into a very interesting layout know as Key Process Analysis. This will take both size of the care process family and variation into account. First we will have the Catalyst Analytic Nerds line up in order of variable cost size. (Nerds move into order) Large process on this side down to small processes on this side. We’ve also labeled the name of the care process family and the variable cost associated with each care process family Now we will have them move up or down the risers based on how much variation exists in their process. We’ll separate the briefcases into 4 quadrants with this caution tape. The idea here is that processes that are inconsistent and large most likely will have the most improvement opportunity (Three processes are in the top right of the graph – most briefcases are in the top left - smaller processes with a lot of variability) Ok which 3 Care Process Families do you want to choose this time (hopefully she picks the top three in the top right quadrant.) Now lets see what your total opportunity would be for the three process you have selected. (This will represent like 30% of the opportunity – a big number) Banker RINGS: (Wa Wa Wa) Ok here’s what the Banker is willing to do: You can say DEAL and take this Catalyst T-shirt and call it a day or you can say NO DEAL and you will force Catalyst to give you an iPad mini plus run a free Key Process Analysis with your data for your health system organization (a 50K dollar value) (She says no Deal, gets the free iPad mini plus a free KPA) 46

47 Healthcare Analytics Summit 14 Script/Description of Exercise (Hidden) Banker RINGS: (Wa Wa Wa) Ok here’s what the Banker is willing to do: You can say DEAL and take this Catalyst T-shirt and hat and call it a day or you can say NO DEAL and you require Catalyst to give you an iPad mini plus run a free Key Process Analysis with your data for your health system (She says no Deal, gets the free iPad mini plus a free KPA) 47

48 Healthcare Analytics Summit 14 Script/Description of Exercise (Hidden) The demonstrator show a finished example to the entire crowd. He tells them they cannot tell anyone else if they know how to do it. Everyone has to start out individually (no collaboration). People can easily see the point that this is a square with two sticks crossed, but they don’t get a closeup look at how the sticks are positioned, which ones are in front and which are in back. Just the final results Then we start the timer. Everyone at each table starts as an individual to do it. They can’t show each other how to do it. However, once the first person at any table figure is out, then they can help the rest. The table raises their hand when they get X people (3) that have finished it. You as the facilitator know the fastest way. But you go over to the table that finishes first and see how they did it. Mentally you are deciding whether they can easily teach the rest of the teams the trick or whether you should be the one to teach. Then we continue for X minutes to see how many tables can get it done. The timer goes off and if a table hasn’t finished, they just get the maximum time. Catalyst team members are timing each table. 48

49 Healthcare Analytics Summit 14 Script/Description of Exercise (Hidden) We start the timer in the second found with everyone knowing the best way The tables again raise their hand when X (3) people have finished.. We show the variation visualization and the improved time 49

50 Healthcare Analytics Summit 14 Script/Description of Exercise (Hidden) For this next exercise we need two teams of four people each. Can we get some volunteers. This exercise is all about stopping poor quality data from getting out into the organization. We have here a very large bucket of water. The water represents data quality problems. We have here two data quality teams that have a number of different sized rubber stoppers that match the number and size of the holes in the second bucket and can prevent bad data from getting to the rest of the organization. The first team to stop the water from flowing to the bottom bucket with these stoppers will be our winner. Will see which group will work most effectively as a team to stop the flow of poor quality data. Alright are you ready, get set, GO! (The teams now frantically try to match the holes to the stoppers – if one team figures it out and uses the largest stopper to plug the hole in the top bucket they win; if both teams fail to realize that you can plug it at the source we let them play it out until one team wins and then we show them on the third contraption) We have our winners!!! How did your team win? (bla bla bla) (If they figured it out we say well done and go into the explanation on the next slide) (if they don’t figure it out, we say the following) So it was a valiant effort by both teams, but no one realized that this largest stopper could be used to stop the water at the source (demonstrate on the third contraption) 50

51 Healthcare Analytics Summit 14 Script/Description of Exercise (Hidden) Ok for our final exercise we are going to re-enact the famous ride of Paul Revere. We actually will need two volunteers for this. What some of you may not realize is that Paul Revere was not the only rider on that important night. William Dawes, another patriot, also rode that night. (Catalyst team members start distributing different colored envelops to each person still sitting at the tables) Thank you so much for volunteering, ok what are your names. Great – John you will be Paul Revere and Matt you will be William Dawes. We would like to introduce you to your horses (out come two catalyst team members with coconuts, Monti Python style) Here are your trusty steeds. This half of the room will represent the route of Paul Revere and this half of the room represent the course of William Dawes. Each table represents a small town or village they will pass through on their ride. (Paul Revere’s horse secretly reveals to him that he should only pick red envelopes) We are going to give you thirty seconds to gallop thru these towns and warn one person at each table, by tapping them on the shoulder. If you are tapped, open your envelope and distribute the contents to other members of your table.Ok for effect, you can yell “the British are coming, the British are coming. Ok. are you ready? On your mark, get set, go!! (they gallop thru the audience, with their Catalyst steeds, clapping the coconuts together – as they pick people the person who is picked opens their envelope and distributes, red card stock cut in the shape of a coat in quantities of 1, 2 or 10 – the red envelopes have 10, all other envelopes only have 1 or 2) Very well done – if you received a red card, you were notified that the red coat are coming – will you hold up your cards please. (On the Paul Revere side of the room everyone was notified, only sparsely on the Dawes side) 51


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