Working with Data: A Toolkit for Health Care Professionals

1. Working with Data:A Toolkit for Health Care Professionals Developed by Cheryl A. Niespodziani, MBA The Children’s Hospital, Denver

2. “The beautiful thing about learning is that nobody can take it away from you.”--BB King US jazz musician

3. Overview • Background • Types and Uses of Tools • Examples • Questions/Answers

4. Background • Quality in health care • Related factors • Quality gurus • W. Edwards Deming • Joseph Juran • Methods of performance improvement

5. Statistics vs. Tools • Inferential analysis • Statistics (regression, correlation, etc.) • Descriptive analysis • Tools to display information

6. Tools are necessary to… • Design • Measure • Assess • Improve • Redesign Continuous quality improvement

7. Types/Uses of Quality Tools • Planning • Teams • Data Collection • Data Analysis • Understanding Root Causes of Performance

8. Tools for Planning • Hoshin Planning • Critical Paths • Gantt Chart • Force Field Analysis

9. Hoshin Planning • Comes from Japanese term hoshin kanri = policy deployment • Organization-wide process of creating a vision and taking action

10. Hoshin Planning Process • Select stakeholders • Gather information • Craft the vision • Develop the elements of the vision • Create the hoshin (strategic focus) • Operationalize the success factors • Develop breakthrough projects • Conduct frequent audits

11. Critical Paths(also called Clinical Care Pathways/Guidelines) • Comprehensive, flexible framework • Single patient-care process • Details involvement of all groups • Summarizes day-to-day activities • “Ideal” process

12. Critical Path Process • Select the process • Define the process • Form a team • Create the critical path • Make the path a working document

13. Gantt Chart

14. Driving Forces (support efforts)  Restraining Forces (conflict with efforts)  Force Field Analysis

15. Force Field Analysis Process • Identify the issue • Identify the ideal state/situation • Brainstorm to identify positive forces • Brainstorm to identify negative forces

16. Tools for Teams • Brainstorming • Affinity Diagrams • Multivoting • Selection Grids • Task Lists • Storyboards

17. Brainstorming • Create a non-threatening environment • Never criticize ideas (no bad or wrong answers) • Write down all ideas so team can view • Keep process short; enforce time limit

18. Affinity Diagrams • Organize large volumes of information • Put into meaningful groupings • Provide structure • Can give new perspective to old problems

19. Affinity Diagram Process • Choose a team • Define the issue • Brainstorm the issue • Randomly display cards/notes • Sort in silence • Create header cards • Draw the diagram

20. Consider if items are same/similar Ask team if items can be grouped Combine similar items Number items on new list Determine number of points assigned to the list Allow group time to independently assign points Indicate each member’s point allocation Tally the votes Note items with greatest number of points Choose final selection or multivote again Multivoting

21. Selection Grids(also called Prioritization Matrices) • Start with list of options • Choose criteria & scoring system • Draw the grid • Judge each option against criteria & write in scores • Use completed grid to evaluate findings • Determine whether new criteria are necessary • Select the best option

22. Task Lists • Most familiar quality tool • Written record of what has been done & what is left to do • Can be expanded into action plans

23. Tips for Using Storyboards • Make it ongoing part of process • Both formal and informal presentations • Include team member names • Keep simple and attractive • Ask for feedback and use it • Be creative and have fun

24. Tools for Data Collection • Indicators • Check Sheets • Surveys

25. Indicators • Quantitative measures • Related to one or more dimensions of performance • Help provide data that (when analyzed) give information about quality • Direct attention to potential problems

26. Types of Indicators • Sentinel-event indicators • Aggregate-data indicators • Continuous-variable indicators • Rate-based indicators

27. Points to Remember • Tailor indicators to processes that are important (e.g., high volume, high risk, problem prone) • Use other tools to help identify appropriate processes/indicators (e.g., brainstorming, flowcharts, etc.) • Review existing data sources • Make complete and objective statements; leave no room for interpretation • Consult a statistician if necessary

28. Check Sheets • Most basic tool • Shows how often an event occurs • Records data that answer objective statements

29. Surveys

30. Tools for Data Analysis • Run Charts • Control Charts (SPC) • Histograms • Scatter Diagrams

31. Run Charts • Probably most familiar/used tool • Used to identify trends/patterns in a process over time • Helps track if target level has been attained/maintained

32. Run Chart Process • Decide what the chart will measure • Draw graph’s axes • Plot the data points & connect them • Evaluate the chart to identify meaningful trends • Equal # of points will fall above/below average • A “run” of 6 or more points on 1 side of average indicates statistically unusual event/shift • A trend of 6 or more steadily increasing/decreasing points (with no reversals) indicates important chage • Cyclical trends should also be considered • Investigate the findings

33. Control Charts(sometimes called Statistical Process Control—SPC) • Run charts that include statistically determined “control” limits • Shows what type of variation exists • Measures quantitative data (e.g., time or length vs. rate) • Tracks performance over a significant time period

34. SPC Chart Process • Choose process and obtain a data set • Calculate the mean • Calculate the SD & set UCL/LCL • Create the control chart • Plot the data • Analyze the chart and investigate findings • Remember…terms “in control” and “out of control” do not signify whether a process meets the desired level of performance

35. Histograms • Bar charts that display: • Patterns of variation • The way measurement data are distributed • Snapshot in time • May be more complex to establish; consult statistics textbook if needed

36. Histogram Process • Obtain data set & count number of data points • Determine range for entire data set • Set the number of classes into which the data will be divided • Determine the class width • Establish class boundaries • Construct the histogram • Count the data points in each class and create the bars • Analyze the findings

37. Scatter Diagrams • Graphs that show statistical correlation between 2 variables • Used when group wants to: • Test a theory • Analyze raw data • Monitor an action taken

38. Scatter Diagram Process • Decide which 2 variables will be tested • Collect & record relevant data • Draw horizontal/vertical axes • Plot the variables on the graph • Interpret the completed diagram

39. Tools for Understanding Root Causes of Performance • Flowcharts • Cause & Effect Diagrams • Pareto Charts • RCA vs. FMEA

40. Flowcharts • Graphic representation of process from start to finish • Can demonstrate actual process or an “ideal” process path • Can help identify problems and plan solutions

41. Flowchart Process • Define the process • Brainstorm activities and decision points in the process • Determine the sequence of activities and decision points • Use information to create flowchart • Analyze the flowchart

42. Cause-and-Effect Diagrams(also called Ishikawa or fishbone diagrams) • Present picture of many causal relationships between outcomes and factors of outcomes • Used to identify and display large numbers of possible causes

43. Fishbone Process • Identify outcome/problem statement • Determine general categories for the causes • List major causes under general categories • List subclauses under major clauses • Evaluate the diagram

44. Pareto Charts • Pareto principle: Few causes are responsible for majority of effects • Statistical tool used to compare events, problems, or causes according to relative frequency or magnitude • Purpose: show which causes have the greatest effects • Natural follow-up to a fishbone diagram

45. Pareto Chart Process • Decide on topic of study • Select causes to be compared • Set the standard for comparison • Collect data • Make the comparison • Draw the chart’s vertical axis • List factors along horizontal axis • Draw a bar for each factor • Include additional features if desired

46. Root Cause Analysis (RCA) vs. Failure Mode Effects Analysis (FMEA) • RCA • Reactive • Asks “why” something happened • FMEA • Proactive • Asks “what could happen”

47. FMEA Rating Scales(From VA Model) • Severity Rating • Minor event • Moderate event • Major event • Catastrophic event • Probability Rating • Frequent (may happen several times in 1 year) • Occasional (may happen several times in 1-2 years) • Uncommon (may happen sometime in 2-5 years) • Remote (may happen sometime in 5-30 years) • Detectability Rating (1=not detectable; 0=detectable)

48. FMEA Hazard Scoring Matrix

49. Questions/Comments? Contact: Cheryl Niespodziani 303-861-6159 (office) E-mail: niespodziani.cheryl@tchden.org