1. From Ideas to Action: Practical Tips for Making Improvements Dr Donald Campbell Clinical Epidemiology & Health Service EvaluationUnit

2. Improvements n the will to make the change n the ideas to make the change n the execution of the ideas Commitment to measurement and reporting

3. Topics n Aims, Measures, Changes n The Model for Improvement and the PDSA Cycle n Collecting and Displaying Data

4. The Breakthrough Collaborative n Brings together multiple sites with common aims n Working to spread and adapt existing knowledge è not developing new knowledge

5. Fundamental Questions for Improvement n What is the aim? n What will be measured to know the aim has been achieved? n What are the changes?

6. Aims focused on delays n Patient Satisfaction n Clinical n Operational

7. Measures n The key measures should operationalize the aim –LOS for admitted, discharge, and fast track –Clinical improvements –Patient satisfaction scores n Collect data on sub-components of the system judiciously - ie, only if it is necessary

8. Changes n Based on your aims, identify the key changes in need of development/improvement in your system n Solicit input from others when you return to your organization

9. Median Time to Antibiotics Administration Anne Arundel Medical Center

10. Time To Analgesia Royal Melbourne Hospital Excessive workload

11. ED Median Total Length of Stay St Elsewhere’s Medical Center Week

12. Median Time From Bed Requested to Patient Upstairs District General Hospital

13. Percent Left Without Seeing Doctor (1999) Royal King Arthur Hospital

14. Some Things to Consider When Making Improvements n Multiple PDSA Cycles (and time) are usually needed to adapt a change n Pay attention to detail n Measurement - useful not perfect n Promote the project n Overcoming barriers to achieving success n Hold the gains

15. Model for Improvement ActPlan StudyDo What is the aim? What will be measured to know the aim has been achieved? What are the changes?

16. Model for Improvement ActPlan StudyDo What are we trying to accomplish? How will we know that a change is improvement? What change can we make that will result in improvement?

17. Use of Data Theories Ideas Changes That Result in Improvement AP SD A P S D AP SD D S P A DATA 1a 1b 1c 1d 1 2 3 Median LOS for Admitted Patients Week 1. “quick-look” x-rays 3. Bed ahead 2. Work-up done on floor

18. Useful Measurement n Data directly related to aims n Data collected in cycles to determine the effect of a particular change n Qualitative data to assist in refining a change n narrow bandwidth & stay on the money

19. Collecting Data n Use purposive sampling to conserve resources - Sample data daily for Fast Track, Main ED, Admitted - Summarize data weekly using the median to lessen the effect of outliers - To calculate Total LOS, use a weighted average of the medians n Integrate measurement into the daily routine

20. Collecting Data n Use sampling to conserve resources - Sample data daily for Fast Track, Main ED, Admitted - Summarize data weekly using the median to lessen the effect of outliers - To calculate Total LOS, use a weighted average of the medians n Integrate measurement into the daily routine

21. Operationalising Data Collection - some examples n Time to analgesia –pen/paper stuck on narcotics safe –pain scale at triage n Fast track –identify on computer (or manually on assigned cubicle) n Ottawa ankle rules –aide memoire at triage and/or in cubicles

22. Length of Stay for Main ED Discharged Patients n =1 per week Avg=180, SD=50 Avg=135, SD=35

23. Median Length of Stay for Main ED Discharged Patients n=14 per week

24. Median Length of Stay for Main ED Discharged Patients n=28 per week

25. Median Length of Stay for Main ED Discharged Patients n=300 per week

26. Example of a Data Collection Form Weekly Medians: Total LOS_________ ED LOS__________ Adm LOS_________ Fast Track_________

27. From the Wisconsin State Journal Half Still Under Median Despite the increase, union officials said about half the league’s players still earned less than the league-wide median of $75,000.

28. Understanding Demand Emergency Department Demand by Day Average Number of Patients per Hour Day

29. Understanding Demand Enhancing the understanding Average Number of Patients per Hour n What about recording pts/hour by hour of the day? n What about pts/hour by day of the week?

30. Emergency Department Demand by Hour Average Number of Patients per Hour Hour of the Day

31. Good Visual Display of Data? Attending MDS Do Work-up Outside ED

32. n Goal for pneumonia: –administer antibiotics to 95 % of patients w/in 60 mins of arrival to ED n Impact of early antibiotic administration: –decreased mortality/decreased length of stay/reduced costs Pneumonia March-June 1998

33. Some Tips for Designing Good Graphics n Eliminate ink that does not add information n Show the data n Make good use of space - Scale the graph so the data eventually encompasses most of the graphing area - Include information about multiple characteristics on the same graph or use multiple graphs on the same page n Integrate words with the data

34. Improving LOS for Admitted Patients from the ED Bed ahead Individual responsible for bed control Quick-look x-rays 2/16/98 3/16 4/13 5/11 6/8 7/6 Week

35. The Key: Holding the Gains n Document processes and adhere to standards n Pay attention to orientation and training n Assign ownership n Use measurement and audits The test: if you aren’t measuring you aren’t really trying!

36. Bibliography Berwick D. A primer on leading the improvement of systems. BMJ 1996; 312: 619-622. Berwick D, Nolan T. Physicians as leaders in improving health care: a new series in Annals of Internal Medicine. Ann Intern Med. 1998; 128:289-292. Brock W, Nolan K, Nolan T. Pragmatic science: accelerating the improvement of critical care. New Horizons 1998; 6: 61-68. Cook T, Campbell D. Quasi-Experimentation. (Boston: Houghton Mifflin 1979) Langley J, Nolan K, Nolan T, Provost L.. The Improvement Guide. (San Francisco: Jossey-Bass 1996) Lundberg G, Wennberg J. Editorial: a new proposal adn a call to action. JAMA 1997; 278: 1615-1616. Rodgers E. Diffusion of Innovations. (New York: The Free Press 1995. Tufte, E., The Visual Display of Quantitative Information, (Cheshire, CT:Graphics Press,1983)