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

Understanding Variation in Patient Satisfaction

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


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?


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


Step 3: Solve the Statistical Problem

First, look at aggregate data for 2004: Patient Satisfaction with Nursing

0.65 0.69 0.73 0.77 0.81 0.85

95% Confidence Interval for Mu

0.768 0.778 0.788 0.798 0.808 0.818

95% Confidence Interval for Median

Variable: Pt Sat

A-Squared:P-Value:

MeanStDevVarianceSkewnessKurtosisN

Minimum1st QuartileMedian3rd QuartileMaximum

0.770418

0.043367

0.773366

0.5120.185

0.7866050.0525952.77E-03-7.7E-01

0.38374943

0.6450000.7590000.7870000.8270000.870000

0.802791

0.066849

0.813317

Anderson-Darling Normality Test


95% Confidence Interval for Sigma


Descriptive Statistics


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.

403020100

0.95

0.90

0.85

0.80

0.75

0.70

0.65

0.60

Observation Number

Indi

vidu

al V

alue

I Chart for Pt Sat

Mean=0.7866

UCL=0.9391

LCL=0.6341



2004 Overall Agency Usage % by Nursing Unit

0.160.120.080.040.00


0.060.050.040.030.02


Variable: Agency

0.021683

0.035100

0.031318

Maximum3rd QuartileMedian1st QuartileMinimum

NKurtosisSkewnessVarianceStDevMean

P-Value:A-Squared:

0.054634

0.054106

0.057520

0.1590000.0690000.0350000.0050000.000000

430.3841330.9716701.81E-034.26E-024.44E-02

0.0021.279


95% Confidence Interval for Sigma


Anderson-Darling Normality Test

Descriptive Statistics



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.

403020100

0.2

0.1

0.0

-0.1

Observation Number

Indi

vidu

al V

alue

I Chart for Agency

1

Mean=0.04442

UCL=0.1571

LCL=-0.06830



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

Pt S

at

S = 0.0491794 R-Sq = 14.6 % R-Sq(adj) = 12.6 %

Pt Sat = 0.807609 - 0.472877 Agency

95% CI

Regression

Regression Plot



The following variables did not have a statistically significant correlation to Patient Satisfaction scores using 2004 aggregate data:

X2 – Overtime p-value = 0.121

X6 – Skill mix p-value = 0.216

X7 – AFS RN p-value = 0.879



2004 Monthly Satisfaction Scores by Nursing Unit

11 T

hom

as

13 T

hom

as

2 &

4 J

2 T

hom

as

2E

2nd

3rd 3S

4th

4W

A5

A5

B5

S5t

h5

W6

Tho

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s6

A6

B6 C 6W 7A

7B

7 C 7W

8 T

hom

as

8A

8B

9A

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CV

SD

ED

FB

UF-

ED

LB

-GT

ME

CH

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SC

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TC

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0.4

0.5

0.6

0.7

0.8

0.9

1.0

C2

Ser

vice

Exc

elle

nce

Boxplots of Service by C2(means are indicated by solid circles)



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


One-way ANOVA: Service Excellence versus Agency Usage < 5%

Analysis of Variance for Service Source DF SS MS F PAgency U 1 0.17457 0.17457 21.88 0.000Error 481 3.83771 0.00798Total 482 4.01227 Individual 95% CIs For Mean Based on Pooled StDevLevel 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


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.



Result of Correlation/Regression

using monthly data for 2004X1 – 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.


The regression equation isService 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 PConstant 0.80123 0.01828 43.84 0.000Agency -0.24136 0.08420 -2.87 0.004OT -0.5833 0.1638 -3.56 0.000Skill Mi 0.03800 0.02600 1.46 0.145Depart R 0.14461 0.08675 1.67 0.096HPPD -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 4: Translate Back to the Practical Problem

What actions, if any, do you take knowing this information?

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

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