1. Practical Exercises

2. Alzheimer’s Disease Intervention Program Intended to provide evidence-based interventions to a population of patients with Alzheimer’s disease Care to be delivered by a multidisciplinary team working with the client’s PCP The PCP’s are incentivized with a P4P program Intended outcomes include an array of clinical variables as well as client and family satisfaction Program, although initially grant-funded, must be self-sustaining

3. Suggestions Start small – One clinical unit – One district – One provider’s caseload Perfect the process on small scale and spread later – Multiple iterative PDSA Cycles (Rapid-cycle CQI )

4. Evaluate the Key Processes Using the SIPOC Diagram Intake process Intervention process Evaluation of program viability

5. The SIPOC Diagram Suppliers #1 #3 Inputs Step 4 Step 1 Step 5 Step 2 #1 #2 Step 3 Outputs Customers Process #2 #3

6. Intake Process Inputs -Clients -Solicitation letters -Evaluation tools -Time availability -Staff availability -Details of P4P program Outputs -Evaluated patients ready for intervention -Engaged Physicians

7. Intervention Process Inputs -Evaluated client -Treatment plan Outputs -Clinical improvements -Satisfied client and family -Satisfied stakeholders (staff and PCP’s)

8. Measuring the Intake Process Outcome Measures - Number of clients or percentage of patients with Alzheimer’s disease enrolled in health plan who are evaluated per month -Number of physicians or percentage of closed panel PCP’s participating in P4P per month Process Measures - Percentage of solicited patients agreeing to have an evaluation -Average time between acceptance and evaluation in days, measured monthly - Percentage of time that physician agrees with treatment plan measured monthly -Average time between evaluation and team visit

9. Measuring the Intervention Process Outcome Measures - Functional performance score -Perceived health status score -Days between ED visits evaluated monthly -Days between hospital readmissions evaluated monthly -Client and family satisfaction with program Process Measures - Number or percentage of clients withdrawing from program per month before evaluation -Percent of participating clients receiving anticholinergics -Percentage of participating clients receiving all evidence-based intervention measures or -Percentage of participating clients receiving a particular individual measure (one or all) -Percentage of participants whose cases are reviewed by team per month

10. Presenting You the Data Intake Process – Outcome Measures Percentage of Potential Clients Enrolled Percentage of Physicians Enrolled in P4P – Process Measures Percentage of Clients Agreeing to Participate Days Between agreement and Participation Days Between Agreement and First team Visit Intervention Process – Outcome Measures Functional Performance Score Days Between ED Visits Client and Family Satisfaction – Process Measures Percentage of Patients Withdrawing Percentage of Participants Whose Cases are Reviewed Monthly

11. Q1 Intake Outcomes MonthValueMedian January2%0.125 February5%0.125 March10%0.125

12. Q1 Intake Outcomes MonthValueMedian January2%0.075 February5%0.075 March7%0.075

13. Q1 Intervention Outcomes MonthValueMedian January25%0.28 February28%0.28 March32%0.28

14. Q1 Intervention Outcomes MonthValueMedian January23.023 February20.023 March25.023

15. Q1 Intervention Outcomes MonthValueMedian January98%0.825 February90%0.825 March90%0.825

16. Q1-Q3 Intake Outcomes MonthValueMedian January2%0.225 February5%0.225 March10%0.225 April15%0.225 May20%0.225 June20%0.225 July25%0.225 August30%0.225 September30%0.225 Test 1-Length of Run: 9 data points and 9 useful observations; longest run=6 data points; requires 7 or more for special cause Test 2-Trend: for 9 observations; 5 consecutive rising data points; requirement for special cause ≥6 Test 3-Requires at least 15 data points

17. Q1-Q3 Intake Outcomes MonthValueMedian January2%0.1 February5%0.1 March7%0.1 April8%0.1 May10%0.1 June10%0.1 July15%0.1 August18%0.1 September18%0.1 Test 1-Length of Run: 7 useful observations; Longest run=4; requirement for is ≥7 for special cause Test 2-Trend: 9 observations; 5 consecutive rising data points; requirement for special cause ≥6 Test 3-Number of runs: Too few data points to use

18. Q1-Q3 Intake Process MonthValueMedian January1022 February1222 March1122 April2322 May22 June2522 July2422 August22 September2322 Test 1-Length of Run: 7 useful observations; Longest run=3; requirement for is ≥7 for special cause Test 2-Trend: 9 observations; 3 consecutive falling data points; requirement for special cause ≥6 Test 3-Number of runs: Too few data points to use

19. Q1-Q3 Intake Process MonthValueMedian January1013 February1213 March1513 April13 May1013 June13 July1413 August1513 September1413 Test 1-Length of Run: 7 useful observations; Longest run=3; requirement for is ≥7 for special cause Test 2-Trend: 9 observations; 4 consecutive rising data points; requirement for special cause ≥6 Test 3-Number of runs: Too few data points to use

20. Q1-Q3 Intake Process MonthValueMedian January85%0.9 February88%0.9 March82%0.9 April90%0.9 May90%0.9 June95%0.9 July93%0.9 August95%0.9 September95%0.9 Test 1-Length of Run: 7 useful observations; Longest run=4; requirement for is ≥7 for special cause Test 2-Trend: 9 observations; 2 consecutive rising or falling data points; requirement for special cause ≥6 Test 3-Number of runs: Too few data points to use

21. Q1-Q3 Intervention Outcomes MonthValueMedian January25%0.48 February28%0.48 March32%0.48 April48%0.48 May50%0.48 June50%0.48 July52%0.48 August48%0.48 September50%0.48 Test 1-Length of Run: 7 useful observations; Longest run=3; requirement for is ≥7 for special cause Test 2-Trend: 9 observations; 5 consecutive rising data points; requirement for special cause ≥6 Test 3-Number of runs: Too few data points to use

22. Q1-Q3 Intervention Outcomes MonthValueMedian January2330 February2030 March2530 April2830 May30 June3230 July3530 August3830 September3530 Test 1-Length of Run: 8 useful observations; Longest run=4; requirement for is ≥7 for special cause Test 2-Trend: 9 observations; 7 consecutive rising data points; requirement for special cause ≥6 (SPECIAL CAUSE IS PRESENT) Test 3-Number of runs: Too few data points to use

23. Q1-Q3 Intervention Outcomes MonthValueMedian January98%0.8 February90%0.8 March90%0.8 April85%0.8 May80%0.8 June80%0.8 July75%0.8 August70%0.8 September70%0.8 Test 1-Length of Run: 7 useful observations; Longest run=4; requirement for is ≥7 for special cause Test 2-Trend: 9 observations; 3 consecutive falling data points; requirement for special cause ≥6 Test 3-Number of runs: Too few data points to use

24. Q1-Q3 Intervention Process MonthValueMedian January1%0.09 February5%0.09 March6%0.09 April8%0.09 May9%0.09 June10%0.09 July9%0.09 August12%0.09 September10%0.09 Test 1-Length of Run: 7 useful observations; Longest run=4; requirement for is ≥7 for special cause Test 2-Trend: 9 observations; 6 consecutive rising data points; requirement for special cause ≥6 (SPECIAL CAUSE IS PRESENT) Test 3-Number of runs: Too few data points to use

25. Q1-Q3 Intervention Process MonthValueMedian January100%0.88 February100%0.88 March92%0.88 April95%0.88 May87%0.88 June85%0.88 July86%0.88 August88%0.88 September83%0.88 Test 1-Length of Run: 8 useful observations; Longest run=5; requirement for is ≥7 for special cause Test 2-Trend: 9 observations; 3 consecutive falling data points; requirement for special cause ≥6 Test 3-Number of runs: Too few data points to use

26. Do We Have a Problem?

27. Q1-Q8 Intake Process MonthValueMedian January10 February1210 March1510 April1310 May10 June1310 July1410 August1510 September1410 October1410 November10 December810 January710 February810 March10 April1510 May910 June810 July810 August610 September510 October610 November510 December69 Process Change Test 1-Length of Run: 20 useful observations; Longest run=9; requirement for is ≥8 for special cause (SPECIAL CAUSE IS PRESENT) Test 2-Trend: 24 observations; 4 consecutive rising or falling data points; requirement for special cause ≥7 Test 3-Number of runs: 5 runs; expected for 20 useful observations 6-15 (SPECIAL CAUSE IS PRESENT)

28. Q1-Q8 Intake Process MonthValueMedian January109 February129 March159 April139 May109 June139 July149 August159 September149 October109 November89 December99 January79 February89 March69 April79 May89 June69 July69 August59 September49 October58 November68 December58 Process Change Test 1-Length of Run: 23 useful observations; Longest run=12; requirement for is ≥8 for special cause (SPECIAL CAUSE IS PRESENT) Test 2-Trend: 24 observations; 4 consecutive falling data points; requirement for special cause ≥7 Test 3-Number of runs: 3 runs; expected for 23 useful observations 8-16 (SPECIAL CAUSE IS PRESENT)

29. Q1-Q8 Intake Outcomes MonthValueMedian January2%0.38 February5%0.38 March10%0.38 April15%0.38 May20%0.38 June20%0.38 July25%0.38 August30%0.38 September30%0.38 October35%0.38 November38%0.38 December42%0.38 January40%0.38 February43%0.38 March50%0.38 April55%0.38 May62%0.38 June64%0.38 July70%0.38 August83%0.38 September88%0.38 October92%0.4 November95%0.42 December94%0.43 Process Change Test 1-Length of Run: 23 useful observations; Longest run=13; requirement for is ≥8 for special cause (SPECIAL CAUSE IS PRESENT) Test 2-Trend: 24 observations; 11 consecutive rising data points; requirement for special cause ≥7 (SO THERE IS SPECIAL CAUSE) Test 3-Number of runs: 2 runs; expected for 23 useful observations 8-16 (SO THERE IS SPECIAL CAUSE)

30. Q1-Q8 Intake Outcomes MonthValueMedian January2%0.35 February5%0.35 March7%0.35 April8%0.35 May10%0.35 June10%0.35 July15%0.35 August18%0.35 September18%0.35 October22%0.35 November35%0.35 December41%0.35 January48%0.35 February57%0.35 March62%0.35 April68%0.35 May71%0.35 June75%0.35 July77%0.35 August79%0.35 September82%0.35 October84%0.41 November84%0.48 December85%0.57 Process Change Test 1-Length of Run: 23 useful observations; Longest run=13; requirement for is ≥8 for special cause (SO THERE IS SPECIAL CAUSE) Test 2-Trend: 24 observations; 16 consecutive rising data points; requirement for special cause ≥7 (SO THERE IS SPECIAL CAUSE) Test 3-Number of runs: 2 runs; expected for 23 useful observations 8-16 (SO THERE IS SPECIAL CAUSE)

31. Q1-Q8 Intervention Outcomes MonthValueMedian January25%0.57 February28%0.57 March32%0.57 April48%0.57 May50%0.57 June50%0.57 July52%0.57 August48%0.57 September50%0.57 October52%0.57 November57%0.57 December63%0.57 January72%0.57 February78%0.57 March82%0.57 April81%0.57 May85%0.57 June88%0.57 July86%0.57 August90%0.57 September92%0.57 October91%0.63 November93%0.72 December92%0.78 Test 1-Length of Run: 23 useful observations; Longest run=13; requirement for is ≥8 for special cause (SO THERE IS SPECIAL CAUSE) Test 2-Trend: 24 observations; 8 consecutive rising data points; requirement for special cause ≥7 (SO THERE IS SPECIAL CAUSE) Test 3-Number of runs: 2 runs; expected for 23 useful observations 8-16 (SO THERE IS SPECIAL CAUSE) Process Change

32. Q1-Q8 Intervention Outcomes MonthValueMedian January2342 February2042 March2542 April2842 May3042 June3242 July3542 August3842 September3542 October42 November4542 December42 January5342 February5742 March6342 April6242 May7542 June7842 July8242 August8342 September9342 October9745 November9553 Test 1-Length of Run: 22 useful observations; Longest run=11; requirement for is ≥8 for special cause (SO THERE IS SPECIAL CAUSE) Test 2-Trend: 24 observations; 7 consecutive rising data points; requirement for special cause ≥7 (SO THERE IS SPECIAL CAUSE Test 3-Number of runs: 3 runs; expected for 21 useful observations 7-15 (SO THERE IS SPECIAL CAUSE) Process Change

33. Q1-Q8 Intervention Outcomes MonthValueMedian January98%0.84 February90%0.84 March90%0.84 April85%0.84 May80%0.84 June80%0.84 July75%0.84 August70%0.84 September70%0.84 October74%0.84 November75%0.84 December77%0.84 January80%0.84 February82%0.84 March84%0.84 April87%0.84 May89%0.84 June88%0.84 July90%0.84 August93%0.84 September91%0.84 October92%0.84 November93%0.84 December95%0.84 Test 1-Length of Run: 23 useful observations; Longest run=10; requirement for is ≥8 for special cause (SO THERE IS SPECIAL CAUSE) Test 2-Trend: 24 observations; 9 consecutive rising data points; requirement for special cause ≥7 (SO THERE IS SPECIAL CAUSE Test 3-Number of runs: 3 runs; expected for 21 useful observations 7-15 (SO THERE IS SPECIAL CAUSE) Process Change

34. Some Final Comments Since the program and the processes were new, there were no historical data with which to compare Once the program is running, further interventions should be undertaken (only) after the process under evaluation is in control In the course of the process improvement, there is a role for descriptive statistics to help you understand your data

35. Using Descriptive Statistics 0.98 0.9 0.85 0.8 0.75 0.7 Mean0.82 Standard Error0.0320156 Median0.8 Mode0.9 Standard Deviation0.0960469 Sample Variance0.009225 Kurtosis-0.86634 Skewness0.2416068 Range0.28 Minimum0.7 Maximum0.98 Sum7.38 Count9 PointColumn1RankPercent 90.981100.00% 70.9275.00% 80.9275.00% 60.85462.50% 40.8537.50% 50.8537.50% 30.75725.00% 10.780.00% 20.780.00% 0.75 0.60.650.70.80.850.90.951 Box and Whisker Diagram Client Satisfaction

36. Using Descriptive Statistics r=0.859776

37. Modifications Following Practice Change Fellows Meeting

38. New Disease Management Program for CHF Our CHF outcomes are poor – Risk-adjusted mortality 22% – ALOS 8 days – 30 day readmits to our facility 10% There are new innovations in treatment to be introduced to our patients We are going to design a program to upgrade care and improve outcomes

39. The SIPOC Diagram Suppliers #1 #3 Inputs Step 4 Step 1 Step 5 Step 2 #1 #2 Step 3 Outputs Customers Process #2 #3

40. The Process From 30,000 Feet Patient Referred Patient Evaluated Intervention Begun Periodic Reevaluation Modify Intervention Supplier -Referring Physician Inputs -Patient -Records Outputs Clinical outcomes Improved health- related QOL Customers Patient and family Process