1. 6/29/2015 Individual Task Variability: Linking Process Improvement to Patient and Hospital Outcomes Susan Meyer Goldstein & Rachna Shah Cincinnati Innovations in Healthcare Delivery 2006

2. 6/29/2015 Scenario… Treatment of ST-elevation mycardial infarction (STEMI) in Greater Minnesota

3. 6/29/2015 Medical Science Balloon angioplasty (PCI) is preferred treatment for heart attack (based on numerous global studies) Practice Less than half receive primary balloon treatment; often delayed Current Evidence

4. 6/29/2015 Pilot Study Source: Henry et al., American Heart Journal Vol 150, Issue 3, 2005

5. 6/29/2015 Community hospital MHI Standardized Protocol Every patient, every time (24/7 coverage); no exclusions. 95 minutes Source: Henry et al., American Heart Journal Vol 150, Issue 3, 2005

6. 6/29/2015 no yes no yes no Patient arrives at rural hospital with STEMI symptoms Remove patient shirt; put on gown Perform ECG within 5 min. of arrival Activate team (MD, nurse, technician) Is STEMI diagnos ed? Perform angiogram (image the blockage) A cardiologist explains procedure to patient; another cardiologist preps patient Move patient onto imaging table Security holds elevator and escorts patient to cath lab Does angiogr am confirm blockag e? Perform PCI Contact MHI Start IV and monitors, draw blood for testing (all in kit) End of process Is patient anxious ? Give 2 more doses of metoprolol during transport Load patient into ground or air ambulance Give sedation Attach defibrillation pads Start second IV Perform chest x-ray Give aspirin, clopidogrel, nitroglycerin, heparin, metoprolol (all in kit) Contact transport Complete procedure and transfer patient to recovery room Arrive at MHI Locate pre- stocked kit MHI’s Standardized Treatment Protocol for STEMI

7. 6/29/2015 Outcomes – Patient Mortality

8. 6/29/2015 Research Problem Practitioners’ questions: ·Can we further improve an already well-performing system? · Are the community hospitals doing everything they can? Researchers’ questions: · Are there systematic factors within process-level activities that can be improved? What is the impact of hospital-level task activity on the outcomes of interest? Patient-level task activity?

9. 6/29/2015 Research Propositions  Is the impact of variability in task activity on process performance (cost, quality) observable?  What is the relative importance of hospital-level versus patient-level task activity in predicting performance?  What are the impact of process handoffs?

10. 6/29/2015 Literature Base  Service process variability  Frei et al. (1999), Management Science  Tsikriktsis & Heineke (2004), Decision Sciences  Field et al. (2006), Decision Sciences  Process improvement  Zantek et al. (2002), Management Science  Rust & Metters (1996), EJOR  Process handoffs  Hammer (re-engineering)  Shingo (set-ups)

11. 6/29/2015 Sample Characteristics  27 Minnesota community hospitals  Average 81 miles from MHI (range 17-149 miles)  Data collection period: March 2003 – Feb. 2006  Total 720 patients  Exclusions: 54 false positives, 4 extreme time outliers (2 for weather delay; 1 for diagnostic dilemma; 1 for LOS), 11 intentional protocol deviations/missing partial data  Final data set for analysis: 651 patients

12. 6/29/2015 Outcomes of Interest  Patient hospital length of stay – proxy for cost  Sample mean = 3.8 days (range 0-34)  Mortality cases excluded due to truncation  Skewed distribution; 90% of patients hospitalized 6 days or fewer  Logarithmic function used in analysis  Patient in-hospital mortality – proxy for quality  Sample mean = 3.2%  21 deaths in sample

13. 6/29/2015 Data Structure MHI Community Hospital j etc. Patient i etc. i = 1, … 651 j = 1, … 27

14. 6/29/2015 Process Description 0. Pt arrives at CHosp 1. EKG started 2. Transport called 3. Transport arrives 4. Pt departs CHosp 5. Pt arrives at MHI 6. Pt arrives at Cath Lab 7. Procedure begins 8. Normal blood flow 1: arrive → EKG 2: EKG → call 3: call → arrive 4: arrive→depart 5: depart →MHI 6: MHI →Lab 7: Lab → begin 8: begin → flow Interval CHosp Transpt MHI

15. 6/29/2015 Independent Variables: Hospital- Level  From ‘Know what’ to ‘Do what’  Proportion of 4 drugs given  From ‘Know how’ to ‘Do how’  Hospital median time intervals

16. 6/29/2015 Independent Variables: Patient- Level  From ‘Know what’ to ‘Do what’  Proportion of 4 drugs given  From ‘Know how’ to ‘Do how’  Difference from hospital median time intervals Reduces multi-collinearity Keeps VIFs below 2.0 Patient Interval 1 ij Median Hospital Interval 1 j Patient Raw Minutes Interval 1 ij = -

17. 6/29/2015 Control Factors – Patient Characteristics  Systolic blood pressure  Age  Heart rate  Killip class 4  Killip class 3  Killip class 2  Hypercholesterolemia  Diabetes  Hypertension  Prior congestive heart failure  Anterior MI

18. 6/29/2015 Regression Model: Length of Stay Baseline with control factors: ln(length of stay) ij = β 0 + β 1-3 [Patient risk factors ij ] + ε ij Full model: ln(length of stay) ij = β 0 + β 1-3 [Patient risk factors ij ] + β 4-8 [Hosp median interval j ] + β 9 Hosp drug score j + β 10-17 [Pt interval ij ] + β 18 Pt drug score ij + ε ij

19. 6/29/2015 Length of Stay Results Baseline Model Full Model Sample size619 F-change43.87 (p<.001) 3.10 (p<.001) R2R2 0.180.24 Adjusted R 2 0.170.21

20. 6/29/2015 Hospital-Level Effects: LOS Hospital effects: Hosp median Interval 10.035 Hosp median Interval 2-0.012 Hosp median Interval 3-0.048 Hosp median Interval 4-0.031 Hosp median Interval 5-0.051 Hosp drug score-0.090**

21. 6/29/2015 Patient-Level Effects: LOS Patient effects: Patient Interval 10.041 Patient Interval 2-0.101*** Patient Interval 30.128** Patient Interval 40.142*** Patient Interval 50.014 Patient Interval 60.074** Patient Interval 7-0.030 Patient Interval 80.031 Patient drug score-0.048

22. 6/29/2015 Length of Stay Results 8 7 6 5 4 3 2 1 Interval CHosp Transpt MHI ? Patient ‘Do how’ Hospital ‘Do what’ Drug score EKG → call transport Transport call → arrive CHosp → transport handoff Transport → MHI handoff

23. 6/29/2015 Logistic Regression: Mortality Results Baseline Model Full Model Sample size651 Chi-square - change 63.32 (p <.001) 31.37 (p <.01) Nagelkerke R 2 0.090.14 Cox & Snell R 2 0.37 0.55

24. 6/29/2015 Hospital-Level Effects: Mortality Hospital effects: Hosp median Interval 10.554* Hosp median Interval 2-0.470** Hosp median Interval 3-0.122 Hosp median Interval 4-1.013 Hosp median Interval 5-0.064 Hosp drug score1.718

25. 6/29/2015 Patient-Level Effects: Mortality Patient effects: Patient Interval 10.004 Patient Interval 2-0.005 Patient Interval 30.001 Patient Interval 40.011 Patient Interval 5-0.110* Patient Interval 60.068** Patient Interval 70.126 Patient Interval 8-0.014 Patient drug score-3.753

26. 6/29/2015 Mortality Results 8 7 6 5 4 3 2 1 Interval CHosp Transpt MHI ? Patient ‘Do how’ Hospital ‘Do how’ ? Transport → MHI handoff EKG → call transport Arrive CHosp → EKG Depart CHosp → arrive MHI

27. 6/29/2015 Conclusions Is the impact of variability in task activity on process performance (cost, quality) observable? 8 7 6 5 4 3 2 1 8 7 6 5 4 3 2 1 Hospital ‘Do what’ Drug score Length of Stay Mortality

28. 6/29/2015 Conclusions What is the relative importance of hospital-level versus patient-level task activity in predicting performance? 8 7 6 5 4 3 2 1 8 7 6 5 4 3 2 1 Hospital ‘Do what’ Drug score Length of Stay Mortality

29. 6/29/2015 Conclusions What are the impact of process handoffs? 8 7 6 5 4 3 2 1 8 7 6 5 4 3 2 1 Hospital ‘Do what’ Drug score Length of Stay Mortality

30. 6/29/2015 Conclusions In practice… 8 7 6 5 4 3 2 1 8 7 6 5 4 3 2 1 Hospital ‘Do what’ Drug score Length of Stay Mortality