WHA Improvement Forum For July    “Data Driven Improvement”   Presented by Stephanie Sobczak Courtesy Reminders: Please place your phones on MUTE unless you are speaking (or use *6 on your keypad) Please do not take calls and place the phone on HOLD during the presentation.

2 Today’s Webinar Agenda  Data Driven Decision Making  Data Mining Your Processes  From Data to Information  “Real Time” Improvement

Why measure? The main reason for conducting an improvement project is to achieve results, no matter the issue or topic. And how do we know we have achieve a desired result that can be proven to others?  We must demonstrate change from a baseline, or initial measurement, and assess the degree of change after an intervention. 3

Linking Measures to Small Tests of Change AIM: Improve M/S Unit HCAHPS Score for “Patients Always received requested help” by 10 points by Nov Small Test of Change: Anyone within 6 feet of a room will answer that patient’s need. Possible Process Measures: Track how many call lights occur between the hours of 10am -11am and 1pm - 2pm Hallway observation of day shift staff response to call light by a volunteer for 1 hour on 3 different days each week How will we prove this change is effective?

Measurement Best Practices 5  Measures are the proof of improvement  Measures guide improvement by informing the decisions about which changes to test  Outcome and Process Data should be plotted over time on annotated graphs.  Process measurement should be integrated into the team’s daily routine, and shared with staff in ‘real time’.  Really important skill set for staff to understand

6 Graph Your Data Over Time

Time Series Charts 7 Like the EKG of a process!

Data on the Surface 8 No Improvement over time… WHY?

Taking a Deeper Dive – Looking for Drivers What are your Drivers for your Outcomes? Do you have data for these processes? 9 What does the evidence say? If not, can you collect some? If yes, what does it tell you?

Connecting Outcome & Process Measure Data 10 Key: Up is Better

Data Mining Your Processes 11

6 months, no improvement 12 WHY? We do follow-up calls!

Follow- up Calls – quarterly data 13 Need to work on improving the number of calls made

Dive deeper into each STOC results How soon do you see relationships between outcome – process – small test of change? Ex: Follow-up Calls – Was the plan executed well? – Was it the wrong plan? – Were the results not sustained over time? – Is more effort required? 14

How to segment data Start with theories on ‘why’? Dive deeper to demographics such as days/night, age, Dx, unit, etc. Spilt graph into multiple graphs to see driving forces Example: Pts. discharged with appointments 15

16 Evidence  INTERACT adoption in LTC and/or Care Transitions Coaches

Some positive trend - is it related? 17 Adopt INTERACT Toolkit in LTC?

Improvement Plan AIM: Reduce Readmissions by 50% for those over 65 through implementing Care Transitions Coaches Process Measure: Patients receiving coaching Plan: Implement in March, gather monthly data 18

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Decisions Purpose 20 Improve follow-up call process Prevent Readmissions INTERACT Toolkit Adoption Decrease Transfers to ED Care Transitions Coaching Model Assistance for older adults to prevent readmissions

21 New F/u Call Process INTERACT Initiative in LTC Start Care Transitions Coaching

“Mining” your data Other analysis: Does our performance go down with a higher census? Is performance the same on every shift? Are there variations in the practices of individuals? Disclaimer information here…22

Common Mistakes Only one person looks at the process measures Staff aren’t aware of the process measures and how they are directly linked to improvement Processes are only measured for a short period of time Processes aren’t measured at all 23

Turn Your Data to Information 24 Visual displays of data can provide greater insights into the systemic knowledge that lives in the data Turn “data” into “information” Data: raw facts Information: data that has been processed and analyzed so that it is directly useful Visual displays of data highlight variation in the system Systems thinking and understanding of variation is essential for Improvement

Telling a Strong Story 25

The Importance of Data Display If data is not displayed or interpreted correctly, incorrect assumptions can be made leading to poor decisions Aggregated or data presented in tabular formats or with summary statistics, will not help you measure the impact of process improvement/redesign efforts. Aggregated data can only lead to judgment, not to improvement. ©Copyright 2012 IHI/R. Lloyd26

Robut Data Displays Tell a Better Story 27 Identical Improvement

Using Data to Develop an Improvement Plan 1. Which process do you want to improve or redesign? 2. Does the process contain non-random patterns or special causes? 3. How do you plan on actually making improvements? What strategies do you plan to follow to make things better? 4. What effect (if any) did your plan have on the process performance? 28 Run & Control Charts will help you answer questions 2 & 4. YOU need to figure out the answers to questions 1 & 3.

Annotate Your Run Charts 29

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Tells WHY something is changing Helps show your Improvements work Improves support/ ‘buy-in’ Documents what you have learned when revisited in the future. 31 Why Annotate?

Keep visuals simple – and visible! 32

Provide Users will Real Time Feedback Don’t save the reports until meetings Staff will better understand improvement work Enables faster improvement Empowers staff to make their own improvements Better shows where the opportunities for improvements live 33

Summary Look further than Outcome Measures – Measure what you DO / what you TEST Create data displays that are simple but informative – Measure over time Provide real time feedback – Easy to access, Meaningful measurement 34

Next Month: 35 Establishing an Accountable Culture August 22 Noon  The “Two Jobs” of Work  Who’s job is “accountability?”  Strategies to build engagement

Thank You! Questions Please complete 3 question survey when closing webinar window. 36