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Understanding Variation in Patient Satisfaction. All Rights Reserved, Juran Institute, Inc. Understanding Variation in Patient Satisfaction 2.PPT Variation.

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Presentation on theme: "Understanding Variation in Patient Satisfaction. All Rights Reserved, Juran Institute, Inc. Understanding Variation in Patient Satisfaction 2.PPT Variation."— Presentation transcript:

1 Understanding Variation in Patient Satisfaction

2 All Rights Reserved, Juran Institute, Inc. Understanding Variation in Patient Satisfaction 2.PPT Variation in Patient Satisfaction Associated With Nursing Purpose: To use appropriate graphical and statistical techniques to identify and quantify the critical factors associated with the variation in overall patient satisfaction. Y = f(X) Patient Satisfaction associated with Nursing =f(??????) Step 1 - Define the Practical Problem Step 2 - Translate to a Statistical Problem Step 3 - Solve the Statistical Problem Step 4 - Translate back to the Practical Problem

3 All Rights Reserved, Juran Institute, Inc. Understanding Variation in Patient Satisfaction 3.PPT Step 1: Define the Practical Problem The hospital has made significant improvements in patient satisfaction over the past few years, but achieving the system goal of 85% excellent ratings has been difficult to achieve and maintain. Anecdotal evidence abounds concerning reasons for variation in scores, but will these anecdotes be supported by the data ?

4 All Rights Reserved, Juran Institute, Inc. Understanding Variation in Patient Satisfaction 4.PPT Step 2: Translate to a Statistical Problem Y – Overall Patient Satisfaction with Nursing Is a function of: X1 – Agency Usage X2 – Overtime Usage X3 – Nursing Management Changes X4 – RN Turnover Rate X5 – Staffing Hours Variance X6 – Skill Mix Percentage X7 – Associate Satisfaction RN

5 All Rights Reserved, Juran Institute, Inc. Understanding Variation in Patient Satisfaction 5.PPT Step 3: Solve the Statistical Problem First, look at aggregate data for 2004: Patient Satisfaction with Nursing 0.650.690.730.770.810.85 95% Confidence Interval for Mu 0.7680.7780.7880.7980.8080.818 95% Confidence Interval for Median Variable: Pt Sat A-Squared: P-Value: Mean StDev Variance Skewness Kurtosis N Minimum 1st Quartile Median 3rd Quartile Maximum 0.770418 0.043367 0.773366 0.512 0.185 0.786605 0.052595 2.77E-03 -7.7E-01 0.383749 43 0.645000 0.759000 0.787000 0.827000 0.870000 0.802791 0.066849 0.813317 Anderson-Darling Normality Test 95% Confidence Interval for Mu 95% Confidence Interval for Sigma 95% Confidence Interval for Median Descriptive Statistics

6 All Rights Reserved, Juran Institute, Inc. Understanding Variation in Patient Satisfaction 6.PPT Step 3: Solve the Statistical Problem (continued) Overall Satisfaction Scores are in statistical control—however, this is not surprising since aggregated data is being used—it hides the true amount of variation.

7 All Rights Reserved, Juran Institute, Inc. Understanding Variation in Patient Satisfaction 7.PPT Step 3: Solve the Statistical Problem (continued) 2004 Overall Agency Usage % by Nursing Unit 0.160.120.080.040.00 95% Confidence Interval for Mu 0.060.050.040.030.02 95% Confidence Interval for Median Variable: Agency 0.021683 0.035100 0.031318 Maximum 3rd Quartile Median 1st Quartile Minimum N Kurtosis Skewness Variance StDev Mean P-Value: A-Squared: 0.054634 0.054106 0.057520 0.159000 0.069000 0.035000 0.005000 0.000000 43 0.384133 0.971670 1.81E-03 4.26E-02 4.44E-02 0.002 1.279 95% Confidence Interval for Median 95% Confidence Interval for Sigma 95% Confidence Interval for Mu Anderson-Darling Normality Test Descriptive Statistics

8 All Rights Reserved, Juran Institute, Inc. Understanding Variation in Patient Satisfaction 8.PPT Step 3: Solve the Statistical Problem (continued) Overall Agency Usage has one unit (7B at University) which falls outside the Upper Control Limit—however, 1 out of 43 units being out of control is no cause for alarm.

9 All Rights Reserved, Juran Institute, Inc. Understanding Variation in Patient Satisfaction 9.PPT Step 3: Solve the Statistical Problem (continued) Correlation between Satisfaction Scores (Y) and Agency Usage (X1) P value =0.011 therefore it can be concluded with > 95% confidence that a statistically significant correlation exists. In fact, 14.6% of the variation in Pt. Sat. is explained by variation in Agency Usage. 0.150.100.050.00 0.85 0.75 0.65 Agency P t S a t S = 0.0491794 R-Sq = 14.6 % R-Sq(adj) = 12.6 % Pt Sat = 0.807609 - 0.472877 Agency 95% CI Regression Regression Plot

10 All Rights Reserved, Juran Institute, Inc. Understanding Variation in Patient Satisfaction 10.PPT Step 3: Solve the Statistical Problem (continued) The following variables did not have a statistically significant correlation to Patient Satisfaction scores using 2004 aggregate data: X 2 – Overtime p-value = 0.121 X 6 – Skill mix p-value = 0.216 X 7 – AFS RN p-value = 0.879

11 All Rights Reserved, Juran Institute, Inc. Understanding Variation in Patient Satisfaction 11.PPT Step 3: Solve the Statistical Problem (continued) 2004 Monthly Satisfaction Scores by Nursing Unit 1 1 T h o m a s 1 3 T h o m a s 2 & 4 J 2 T h o m a s 2 E 2 n d 3 r d 3 S 4 t h 4 W A 5 A 5 B 5 S 5 t h 5 W 6 T h o m a s 6 A 6 B 6 C 6 W 7 A 7 B 7 C 7 W 8 T h o m a s 8 A 8 B 9 A 9 B C V S D E D F B U F - E D L B - G T M E C H O B S C U S N F T C U 0.4 0.5 0.6 0.7 0.8 0.9 1.0 C2 S e r v i c e E x c e l l e n c e Boxplots of Service by C 2 (means are indicated by solid circles)

12 All Rights Reserved, Juran Institute, Inc. Understanding Variation in Patient Satisfaction 12.PPT Step 3: Solve the Statistical Problem (continued) Histogram of Monthly Variation in Satisfaction Scores Conclusion: 72% of the time nursing units fail to meet the 85% satisfaction goal Process Capability for Service Excellence

13 All Rights Reserved, Juran Institute, Inc. Understanding Variation in Patient Satisfaction 13.PPT One-way ANOVA: Service Excellence versus Agency Usage < 5% Analysis of Variance for Service Source DF SS MS F P Agency U 1 0.17457 0.17457 21.88 0.000 Error 481 3.83771 0.00798 Total 482 4.01227 Individual 95% CIs For Mean Based on Pooled StDev Level N Mean StDev ------+---------+---------+--- ------+ n 164 0.76183 0.09767 (------*------) y 319 0.80197 0.08472 (----*----) ------+---------+---------+---------+ Pooled StDev = 0.08932 0.760 0.780 0.800 0.820 Step 3: Solve the Statistical Problem (continued) Conclusion: Nursing Units that use 5% Agency or less have a statistically significantly higher average satisfaction score than units that use greater than 5% agency.

14 All Rights Reserved, Juran Institute, Inc. Understanding Variation in Patient Satisfaction 14.PPT Step 3: Solve the Statistical Problem (continued) Result of Correlation/Regression using monthly data for 2004 X1 – Agency Usage p value = 0.000 X2 – Overtime Usage p value = 0.000 X3 – Nursing Management Changes X4 – RN Turnover Rate p value = 0.545 X5 – Staffing Hours Variance p value = 0.117 X6 – Skill Mix Percentage p value = 0.006 Conclusion: P values less than 0.05 are statistically significant to a > than 95% Confidence Level. However, while statistically significant these variable explain only a small fraction of the variation in Patient Satisfaction.

15 All Rights Reserved, Juran Institute, Inc. Understanding Variation in Patient Satisfaction 15.PPT The regression equation is Service Excellence = 0.801 - 0.241 Agency - 0.583 OT + 0.0380 Skill Mix + 0.145 Depart Rate RN_1 - 0.00210 HPPD Predictor Coef SE Coef T P Constant 0.80123 0.01828 43.84 0.000 Agency -0.24136 0.08420 -2.87 0.004 OT -0.5833 0.1638 -3.56 0.000 Skill Mi 0.03800 0.02600 1.46 0.145 Depart R 0.14461 0.08675 1.67 0.096 HPPD -0.002103 0.001086 -1.94 0.053 S = 0.08831 R-Sq = 7.3% R-Sq(adj) = 6.3% Best Subsets Regression: Service Excellence versus Agency, OT,... S D H k e P A i p P g l a D e l r n t V c O M a Vars R-Sq R-Sq(adj) y T i R r 1 3.8 3.6 X 1 3.1 2.9 X 2 5.6 5.2 X X 2 4.3 3.9 X X 3 6.3 5.7 X X X 3 6.1 5.5 X X X 4 6.9 6.1 X X X X 4 6.7 6.0 X X X X 5 7.3 6.3 X X X X X Conclusion: Putting all the Factors (X’s) into the model only explains 7.3% of the total variation in satisfaction Step 3: Solve the Statistical Problem (continued)

16 All Rights Reserved, Juran Institute, Inc. Understanding Variation in Patient Satisfaction 16.PPT Step 4: Translate Back to the Practical Problem What actions, if any, do you take knowing this information?


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