Emergency Department Directors Academy Phase II Spring Course name: Measuring Success: Performance Dashboards and Key Metrics/Analytics

Transcription

1 Emergency Department Directors Academy Phase II Spring 2018 Course name: Measuring Success: Performance Dashboards and Key Metrics/Analytics 5/2/2018, 9:45:00 AM - 10:30:00 AM, WE-23 DESCRIPTION: In the last 15 years, we have experienced a dramatic acceleration of the use of data to measure healthcare performance and outcomes. In fact, many key performance measures of our EDs and hospitals are now publicly reported, driving government and private payer reimbursement. Dr. Crane will present the key sources of ED performance metrics and benchmarking and when possible, present generally accepted standards of performance. The benefits and pitfalls associated with datadriven performance and public ally-reported measures will be discussed. OBJECTIVES: Outline the key ED performance measures. List the key sources of performance and benchmarking data. List the current generally accepted performance standards Discuss the risks associated with financial rewards for publicly-reported measures FACULTY: Jody Crane, IV, MD MBA BIO: Dr. Crane is considered one of the leading experts in ED Operations in the US. He has taught and led healthcare and ED improvement efforts with hundreds of organizations in a wide variety of settings in the US, Canada, Europe, South America, and the Middle East, including courses or sessions at The University of Tennessee, The University of Kansas, George Mason University, Harvard University, and Cambridge University. Dr. Crane received his MBA from the University of Tennessee, where he currently serves as a faculty member in the Physician Executive MBA Program (PEMBA), teaching healthcare operations and leadership. Dr. Crane is also an Emergency Medicine faculty member of The Institute for Healthcare Improvement and serves as an advisor for the National Institute for Health Research s Collaboration for Leadership in Applied Health Research and Care in Northwest London. He currently works as Chief Clinical Operations Officer for Sheridan Healthcare EM. DISCLOSURE: (+)No significant financial relationships to disclose.

2 Using Data for Improvement Jody Crane, MD, MBA, FACEP Chief Clinical Officer, TeamHealth EM EDDA, 2018

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4 You can t fatten a pig by weighing it

5 Outline The Power Metrics and Tracking Data over Time Benchmarks Use Cases for Data

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11 The Power Metrics 1. Door to Doc 2. LWOBS 3. Discharged LOS 4. Admitted LOS 5. Boarding 6. Provider Productivity 7. Patient Satisfaction Target (US) 30 minutes <2% <150 minutes <240 minutes Zero patients per hour >90 %tile

12 Start Small Build as You Need/Can

13 AHS Dashboard

14 Mean vs Median Mean Average. Represents the entirety of the data. The presence of outliers, however, can skew the perception of the most likely experience Median Middle number. Often used to represent the more accurate reflection of acute experience when a data set has a skewed distribution (ie tail) Which should you use? It depends on what you are trying to communicate! Operations calculations/modeling/simulation use averages Dashboards and public reporting medians more accurately represent the likely experience, BUT can blind you to the tail.

15 Distribution of Actual ED Triage Times. Distribution of Observed Triage Times (n=777) Count Average = 5.06 Std.Dev. = Minutes Mean 5 Median 3 Mode 2

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17 Opened New Hospital

18 Creating Patient Value as Indicated by Press Ganey Scores Jan 2004-Jun Press Ganey Absolute Score Jan-04 Apr-04 Jul-04 Oct-04 Jan-05 Apr-05 Jul-05 Oct-05 Jan-06 Apr-06 Jul-06 Oct-06 Jan-07 Apr-07 Jul-07 Oct-07 Jan-08 Apr-08 Month

19 The Results:

20 Peds ED LWOBS vs Door to Doc

21 Outline The Power Metrics and Tracking Data over Time Benchmarks Use Cases for Data

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24 CMS EM Timely and Effective Care National Measure Avg Door to Doc 23 min LWOBS 2% Door to EKG 7 min Door to Pain Meds Fx 49 min CT for CVA, ICH < 45min 72% Discharged LOS 148 min Admitted LOS 277 min Dispo to Depart Admitted 102 min

25 This is the only Absolute

26 Star Groups Weighting

27 Key Milestones in the ED Visit Pre-Arrival to Door Recognized Need Care Choice Door to Doc Transport Method Departure Diagnostics Arrival Arrival Triage Start Triage End Bed Placement 1 st Nurse Eval 1 st Doc Eval Doc to Dispo 1 st Doc Eval 1 st Order Nurse Execute Rad TAT Lab TAT Dispo to Depart DispoT&R Depart T&R Last Result Dispo Dispo T&A Clean Bed Assign Ready to Move Depart T&A

28 Key Milestones in the ED Visit ED Nursing Dependent Pre-Arrival to Door Recognized Need Care Choice Door to Doc Transport Method Departure Diagnostics Arrival Arrival Triage Start Triage End Bed Placement 1 st Nurse Eval 1 st Doc Eval Doc to Dispo 1 st Doc Eval 1 st Order Nurse Execute Rad TAT Lab TAT Dispo to Depart DispoT&R Depart T&R Last Result Dispo Dispo T&A Clean Bed Assign Ready to Move Depart T&A

29 Key Milestones in the ED Visit ED Physician Dependent Pre-Arrival to Door Recognized Need Care Choice Door to Doc Transport Method Departure Diagnostics Arrival Arrival Triage Start Triage End Bed Placement 1 st Nurse Eval 1 st Doc Eval Doc to Dispo 1 st Doc Eval 1 st Order Nurse Execute Rad TAT Lab TAT Dispo to Depart DispoT&R Depart T&R Last Result Dispo Dispo T&A Clean Bed Assign Ready to Move Depart T&A

30 Key Milestones in the ED Visit Hospital Dependent Pre-Arrival to Door Recognized Need Care Choice Door to Doc Transport Method Departure Diagnostics Arrival Arrival Triage Start Triage End Bed Placement 1 st Nurse Eval 1 st Doc Eval Doc to Dispo 1 st Doc Eval 1 st Order Nurse Execute Rad TAT Lab TAT Dispo to Depart DispoT&R Depart T&R Last Result Dispo Dispo T&A Clean Bed Assign Ready to Move Depart T&A

31 Benchmarks are Scarce Nursing No source for ideal productivity Most recommendations are from nurse advocate organizations Growing evidence that lower nurse staffing results in increased morbidity, mortality, and cost Physician No source for ideal productivity ACEP, SAEM, AAEM all have position statements Other studies are largely inaccurate, outdated Recommended Benchmarking Sources: ACEP; Premier; EDBA; VHA

32 Using Data to Measure Provider Performance Nursing Intervals Dispo to departure for T&R most common, but Order to execute shortest, bed to nurse ok Physician Intervals Bed to doc shortest, but Last result to disposition is best, but

33 EDBA Adjusted PPH The average is 1.96 provider PPH 80% of values fall between 1.3 and 2.6 provider PPH 70% of values fall between 1.4 and 2.4 provider PPH N = 760 Based on 2013 data

34 EDBA Actual PPH The average is 1.73 provider PPH 80% of values fall between 1.2 and 2.3 provider PPH 70% of values fall between 1.3 and 2.2 provider PPH N = 762 Based on 2013 data

35 Frequency EDBA Nurse Productivity Nurse PPH, All More Bin % % 80.00% 60.00% 40.00% 20.00% 0.00% Frequency Cumulative % The average is 0.6 RN PPH The range is 0.93 PPH with a low of 0.2 to a high of 1.2 RN PPH 90% of values fall between 0.4and 0.85 RN PPH 70% of values fall between 0.45 and 0.8 RN PPH 60% of values fall between 0.5 and 0.7 PPH

36 EDBA WHPPV All Sites The average is 2.48 WHPPV 90% of values fall between 1.6 and 3.8 WHPPV 80% of values fall between 1.8 and 3.3 WHPPV 60% of values fall between 2.0 and 3.0 WHPPV *This data set does not include admin FTE

37 Main ED Docs Target Pts/hr Waiting 10 pts/hr 4 docs? Target Service Rate = ( 10pts/hr / 4) = 2.5pts/hr 2.5 pts/hr / 80% (desired util) = 3.12pts/hr 60min / 3.12 = 19.2 min This is the amount of time you can spend on each patient

38 Doc to Dispo Interval - Goals Caution!

39 Doc to Dispo Interval - Goals The RIGHT answer depends on your arrival rate and the number of treatment spaces in your ED! 10 pts/hr Waiting 25 Beds? LOS 25 beds / 10 pts/hr = 2.5 hours 2.5 hours *.80 = 2 hours

40 Suggested Ancillary TAT

41 POC Testing? I-Stat - 3 min Clinitech - 2 min (H/H, Chem 8, CKMB,Trop I, BNP, PT/INR, ABG, Lactate) U/A, UPT Piccolo 12 min Biosite 10 min BMP, CMP, Caution! Myoglobin, Ck- Electrolytes MB, Trop I, BNP, D-dimer Chempaq POC CBC with diff! Rapid strep, mono, influenza

42 Benchmarks

43 Boarding Hours Calculations 1. Obtain your monthly boarding hours 2. Determine your staffing of holds (ie 2:1, 3:1, 4:1) I usually assume this is 4:1 3. Divide monthly by 4 to get weekly, divide this by your patient to nurse ratio (usually 4 again) 4. This is your number of nursing hours per week staffing boarders. a. Divide this by 12 to get number of shifts weekly b. Divide this by 40 to get number of FTEs 5. Next, get your budget of nurses (How many total FTEs do I have?) 6. Divide 4(b) by this number to get % of your nurse staffing dedicated to boarders 7. Extra credit break this out by ICU (1.5:1) and Non- ICU (4:1) 1,000 4:1 1,000/4 = /4 = /12 = /40 = /625 = 10%

44 Real Time Demand Capacity Matching

45 Outline The Power Metrics and Tracking Data over Time Benchmarks Use Cases for Data

46 Pick the Right Project

47 Establish a Sense of Urgency

48 Study/Check in PDSA Cycles

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50 SH ED CT Abd/Pelvis TAT Avg 142min Avg 99min

51 SH ED CT Abd/Pelvis TAT

52 If You re Not Changing, Don t Meet

53 Accountability

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56 Once You Have Achieved Success Diffuse praise to the lowest level possible, giving from the highest level possible Look for the next target

57 In Summary, Use Data To Select the right target Establish a sense of urgency Inspire change Hold people accountable Celebrate!

58 Problems cannot be solved by the same level of thinking that created them -Einstein

59 What are You Thinking About?