quality tools and techniques- 7 tools of quality

7 Tools of Quality

Dr. Lallu JosephQuality Manager, CMC Vellore

&Mr. Rabindranath

Audit Facilitation Officer, CMC Vellore

QUALITY TOOLS AND TECHNIQUES

Recap

• Mean - It is a point of reference and also the central point for measuring variability. The only disadvantage of the arithmetic mean is that it is greatly affected by extreme values.

• Median - It is the middle value in a series of numbers arranged in an increasing order.– Series odd number - (n+1)/2

– Series even- arithmetic mean of the two middle values

QUALITY TOOLS AND TECHNIQUES7 tools of quality

Recap

• Mode - Most frequently occurring value

• Variance

σ2 = 1/n [∑xi2 - (∑ xi)

2 /n]

The Standard Deviation, is a simple square root of the variance.

In a frequency distribution, variance is calculated by

σ2 = 1/n [∑ fi xi2 - (∑ fi xi)

2 /n]


Example

Daily control measurements of Potassium were made for 25 days during a particular month5.7 5.9 5.7 5.7 5.85.7 5.8 5.7 5.9 5.85.6 5.8 5.8 5.7 5.65.8 5.8 5.5 5.6 5.85.9 5.7 5.8 5.8 5.8

Average x = ∑ xi /25 = 143.7/25 = 5.748 = 5.75Variance = 1/25 [∑ xi

2 - (∑ xi)2 /25]

= 1/25 [826.23 – (143.7)2/25]= 6.06/625 = 0.0097

Standard Deviation = Sq rt of 00.0097 = 0.0985


Basic tools of Quality for Process Improvement

“The old seven”

“The first seven”

“The basic seven”

– Quality pros have many names for these tools, first emphasized by Kaoru Ishikawa the father of “quality circles.”

– These are diagnostic tools to analyze a process and data from that process

– They make up the fundamental continuous improvement toolkit


7 Basic Tools of Quality

• Histograms

• Pareto Charts

• Cause and Effect Diagrams

• Scatter Diagrams

• Control Charts

• Flow Charts

• Check sheet


HISTOGRAM

• It is for illustrating the frequency and the extent for two variables.

• Histogram is a chart with columns which represents the distribution by mean.

• If the distribution is normal, the graph is in the shape of a bell curve.

• If not normal, it may take different shapes based on condition of the distribution.

• Histogram can be used to measure one variable against another. There should be two variables.

• Data should be numerical


When is it used?

• It is used to communicate the distribution of data quickly and easily to others.

• Help in decision making

• Graphically summarize large data

• Compare performance to expectations or specifications


Reasons for dissatisfaction at OPD# Reasons Number of patients

1 No mike or display board to know the token number 15

2 Problem mixing with ‘follow-up’ patients 25

3 Insufficient doctors 100

4 Insufficient counter Staff 93

5 Staff not following the Queue 12

6 Too many patients at the same time 21

7 Registration time too long 111

8 No name boards of the doctors 13

9 Others 10

10 Total 400


Histogram

1525

10093

1221

111

13 10

0

20

40

60

80

100

120

No mike ordisplay

board toknow the

tokennumber

Problem mixing with ‘follow-up’

patients

InsufficientDoctors

InsufficientCounter

Staff

Staff notfollowing

the Queue

Too manypatients atthe same

time

Registrationtime is too

long

No nameboards of

the doctors

Others

Reasons for dissatisfaction of patients N =400


Pareto Charts

– Pareto charts are used to identify and prioritize problems to be solved.

– Vilfredo Pareto, 1800, Italian economist noted “80% of wealth was held by 20% of population”

– Juran applied the Pareto Principle, stating that 80% variation in process is by 20% of the variables

– “Vital few” as opposed to “Trivial many”

– 80/20 rule

– Need not be 80/20, could be 75/25 or 70/30 or even 65/35 also and even disproportionate like 75/35.

– The concept is to priorities and address the issue.


When is it used?

• Looking at data on the frequency of problems or causes.

• When there are too many problems or causes and you want to focus on the significant ones.

• When you want to analyze broad causes by looking at their specific components.

• To effectively communicate to others about the problem/ data.


# Reasons

Number of

patients



3 Insufficient Doctors 100

4 Insufficient Counter Staff 93



7 Registration Time too long 111


9 Others 10

10 Total 400


# Reasons Number of patients

7 Registration Time too long 111

3 Insufficient Doctors 100

4 Insufficient Counter Staff 93






9 Others 10

10 Total 400

Des

cen

din

g o

rde

r


# Reasons Number of patientsIn %

(N=400)

7 Registration Time too long 111 28 %

3 Insufficient Doctors 100 25 %

4 Insufficient Counter Staff 93 23 %

2 Problem mixing with ‘follow-up’ patients 25 6 %

6 Too many patients at the same time 21 5 %

1No mike or display board to know the token

number15 4 %

8 No name boards of the doctors 13 3 %

5 Staff not following the Queue 12 3 %

9 Others 10 3 %

10 Total 400


# ReasonsNumber of

patients

In %

(N=400)

Cumulative

frequency

7 Registration Time too long 111 28 % 28%

3 Insufficient Doctors 100 25 % 53%

4 Insufficient Counter Staff 93 23 % 76%

2 Problem mixing with ‘follow-up’ patients 25 6 % 82%

6 Too many patients at the same time 21 5 % 87%

1No mike or display board to know the

token number15 4 % 91%

8 No name boards of the doctors 13 3 % 94%

5 Staff not following the Queue 12 3 % 97%

9 Others 10 3 % 100%

10 Total 400


28%

53%

76%

82%87%

91%94% 97% 100%

0%

20%

40%

60%

80%

100%

0

20

40

60

80

100

120

RegistrationTime too

long

InsufficientDoctors

InsufficientCounter

Staff


patients


time

No mike ordisplay

board toknow the

tokennumber

No nameboards of

the doctors

Staff notfollowing

the Queue

Others

Number of patients Cumulative frequency


28%

53%

76%

82%87%

91%94% 97% 100%

0%

20%

40%

60%

80%

100%

0

20

40

60

80

100

120

RegistrationTime too

long

InsufficientDoctors

InsufficientCounter

Staff


patients


time

No mike ordisplay

board toknow the

tokennumber

No nameboards of

the doctors

Staff notfollowing

the Queue

Others

Number of patients Cumulative frequency

Addressing these 3 issues out of 9, will solve 76% of the problems


Cause and Effect Diagrams

• Dr. Kaoru Ishikawa• Cause & Effect Diagram (Fishbone or Ishikawa diagram)• It is a schematic way of relating the causes of variation

in a process• A drawing to organize the contributing causes to a

problem in order to prioritize, select, and improve the source of the problem

• Problem (Effect) on the right side and the possible causes on the left side

• Causes are broadly classified into 5M’s and E

Man (People)

Methods (Policies and Procedures)

Materials (Supplies)

Machine (Equipment)

Money

Environment


When is it used?

• When identifying possible causes for a problem.

• Identifies areas for collecting data

• Good process knowledge from multiple stake holders

• Useful for teams: focusing a discussion and organizing large amounts of information coming from a brainstorming session.

• Especially when a team’s thinking tends to fall apart and concentration is lacking


Schematic

Effect

People /Man

Plant / MachineProcedures / Methods

PoliciesMaterial


Cause and Effect Diagram

Registration time too

long

People /Man

Plant / MachineProcedures / Methods

PoliciesMaterial

Staff can cut the queue

Registration at any time Irrespective of appointment time

Manual registration- No computers

Inadequate signage / instruction

FIFO not followed

Unnecessary information being collected at the reg.

counter

New staff

Aggrieved StaffInadequate stationeries

Separate line for men and women


Scatter Plots

• Scatter diagram shows co-relation between two variables

• If correlated – does not necessarily mean a direct cause and effect

• If one variable can be predicted based on the value of the other, then correlated


Scatter Plots- correlation

• 2 Dimensional X/Y plots (with dots)

• To check if there is correlation b/w two variables

– Used to show relationship between independent(x) and dependent(y) variables

Positive correlation Negative correlation No correlation


When is it used?

• Trying to determine if the two variables are related, such as…

– to identify potential root causes of problems.

– After brainstorming session and identifying causes and effects using a fishbone diagram, to determine whether a particular cause and effect are related.

– To determine whether two effects that appear to be related both occur with the same cause.


Time spent by doctor and patient satisfaction

Patient hosp number

Time Spent by doctor (In minutes)

Satisfaction Score

1 24 5

2 8 1

3 9 1

4 22 4

5 10 3

6 19 4

7 10 2

8 16 4

9 13 4

10 15 3

11 23 4

Patient hosp number

Time Spent by doctor (In minutes)

Satisfaction Score

12 12 3

13 12 2

14 14 3

15 11 2

16 16 3

17 20 4

18 18 3

19 14 2

20 14 4

21 17 3

22 17 4

23 13 3


Scatter plot

0

1

2

3

4

5

0 5 10 15 20 25 30

Sati

sfac

tio

n s

core

-5

be

ing

the

hig

he

st

Time spent by doctors (In minutes)

Satisfaction Score


Scatter plot

• A Scatter plot cannot prove that one variable causes another, but it does show how a pair of variables is related and the strength of that relationship.

• Statistical tests quantify the degree of correlation between the variables.


Control charts• Influence of special causes on process and out of

control situation

• Monitor processes to show how the process is performing over time

• Following needs to be calculated.

– Mean variable

– Upper control limit (UCL)

– Lower Control limit (LCL)

• UCL and LCL can be calculated based on • data from scientific literature

• Historical data

• Statistical data like Standard deviation


Time between glucose measurements(in Hours)

Day Hours

1/1/2017 5

1/2/2017 5.5

1/3/2017 5.5

1/4/2017 5

1/5/2017 7

1/6/2017 5

1/7/2017 5

1/8/2017 6

1/9/2017 6

1/10/2017 10

1/11/2017 11

Day Hours

1/12/2017 5

1/13/2017 6

1/14/2017 6

1/15/2017 5

1/16/2017 4.5

1/17/2017 5

1/18/2017 6

1/19/2017 5.5

1/20/2017 6

1/21/2017 5

1/22/2017 5

1/23/2017 5



Day Hours

1/1/2017 5

1/2/2017 5.5

1/3/2017 5.5

1/4/2017 5

1/5/2017 7

1/6/2017 5

1/7/2017 5

1/8/2017 6

1/9/2017 6

1/10/2017 10

1/11/2017 11

Day Hours

1/12/2017 5

1/13/2017 6

1/14/2017 6

1/15/2017 5

1/16/2017 4.5

1/17/2017 5

1/18/2017 6

1/19/2017 5.5

1/20/2017 6

1/21/2017 5

1/22/2017 5

1/23/2017 5

Calculate Mean and Standard deviation

Mean= 5.869565 SD = 1.575



Day Hours

1/1/2017 5

1/2/2017 5.5

1/3/2017 5.5

1/4/2017 5

1/5/2017 7

1/6/2017 5

1/7/2017 5

1/8/2017 6

1/9/2017 6

1/10/2017 10

1/11/2017 11

Day Hours

1/12/2017 5

1/13/2017 6

1/14/2017 6

1/15/2017 5

1/16/2017 4.5

1/17/2017 5

1/18/2017 6

1/19/2017 5.5

1/20/2017 6

1/21/2017 5

1/22/2017 5

1/23/2017 5

Calculate UCL (upper control limit) and LCL (Lower control limit)

Mean= 5.869565

UCL = Mean + 3 *(Standard Deviation) = 10.59

LCL = Mean -3 *(Standard Deviation) = 1.14



Day Hours Mean UCL LCL

1/1/2017 5 5.869565 10.59 1.14

1/2/2017 5.5 5.869565 10.59 1.14

1/3/2017 5.5 5.869565 10.59 1.14

1/4/2017 5 5.869565 10.59 1.14

1/5/2017 7 5.869565 10.59 1.14

1/6/2017 5 5.869565 10.59 1.14

1/7/2017 5 5.869565 10.59 1.14

1/8/2017 6 5.869565 10.59 1.14

1/9/2017 6 5.869565 10.59 1.14

1/10/2017 10 5.869565 10.59 1.14

1/11/2017 11 5.869565 10.59 1.14

Day Hours Mean UCL LCL

1/12/2017 5 5.869565 10.59 1.14

1/13/2017 6 5.869565 10.59 1.14

1/14/2017 6 5.869565 10.59 1.14

1/15/2017 5 5.869565 10.59 1.14

1/16/2017 4.5 5.869565 10.59 1.14

1/17/2017 5 5.869565 10.59 1.14

1/18/2017 6 5.869565 10.59 1.14

1/19/2017 5.5 5.869565 10.59 1.14

1/20/2017 6 5.869565 10.59 1.14

1/21/2017 5 5.869565 10.59 1.14

1/22/2017 5 5.869565 10.59 1.14

1/23/2017 5 5.869565 10.59 1.14


Control Chart

0

2

4

6

8

10

12

1-J

an-1

7

2-J

an-1

7

3-J

an-1

7

4-J

an-1

7

5-J

an-1

7

6-J

an-1

7

7-J

an-1

7

8-J

an-1

7

9-J

an-1

7

10

-Jan

-17

11

-Jan

-17

12

-Jan

-17

13

-Jan

-17

14

-Jan

-17

15

-Jan

-17

16

-Jan

-17

17

-Jan

-17

18

-Jan

-17

19

-Jan

-17

20

-Jan

-17

21

-Jan

-17

22

-Jan

-17

23

-Jan

-17

Tim

e b

etw

een

glu

cose

mea

sure

me

nts

(in

Ho

urs

)

Date

Hours Mean UCL LCL

In this case, the variation was detected on January 11 because the corresponding data point was above the upper control limit. Root cause for the variations needs to be investigated.


Control Chart

• Control charts are made with the existing data. Suggestions, if necessary, are implemented based on the chart.

• Post Implementation, the mean and the control limits of the control charts will vary depending on the effectiveness of the implementation

• They are helpful for analyzing a process before and after an improvement as well

• Helps to see how process mean and variability change as a result of the improvement.


Tim

e ta

ken

fo

r ad

mit

tin

g th

e p

atie

nt

(in

Min

ute

s)

Days

Tim

e ta

ken

fo

r ad

mit

tin

g th

e p

atie

nt

(in

Min

ute

s)

Days

Time taken for ICU admission

Time taken for ICU admission


160

180

200

220

240

260

280

300

320

2/9 3/9 4/6 5/4 6/1 6/29

Week

ED

Sta

y (

min

ute

s)

Reducing Delays for Patients Admitted to the Emergency Department

Goal


Work

Days

ACA

Initiative

begun

Optimize

the Team

0

10

20

30

40

50

60

70

80

90

100'O

ct

01

'Jan

02

'Ap

r 02

'Ju

l 02

'Oct

02

'Jan

03

'Ap

r 03

'Ju

l 03

'Oct

03

'Jan

04

'Ap

r 04

'Ju

l 04

'Oct

04

'Jan

05

'Ap

r05

'Ju

ly05

'Oct

05

'Jan

06

'Ap

ril0

6

'Ju

ly06

SI

Initiative Optimize

the Team

Imaging – MRI Backlog

7 tools of quality

Flow Chart• Process flow chart of flow diagram• A powerful improvement tool to define, describe, and

communicate clinical, administrative and operational processes.

• A flowchart represents an algorithm or process with the help of pictorial symbols.

• They trace the steps the “object” of the process goes through from start to finish. (a lab test, a clinic visit, a specialty visit, an imaging study, etc. )

• Boxes of pictorial symbols connecting with arrows to represent sequence of activities.

• Flowcharts help in identifying points or bottle necks where problems might occur.


• Develop understanding of how a process is done.

• Study a process for improvement.

• Communicate to others how a process is done.

• When better communication is needed between people involved with the same process.

• In order to document a process.

• While planning a project.

When is it used?


Flow chart- Symbols

One step in the process

Direction of flow

Link to another page or

flowchart

Input or output Document Start and end points

Decision based on a question

Delay or wait

7 tools of quality

The Process Flow Diagram (Flow Chart)

Used to understand the current process and identify opportunities for improvement. It shows the work flow through the process including all activities, decisions, delays, and measurement points.

DELAY

DELAY

ACTIVITY

ACTIVITYDECISION

ACTIVITY

DECISION

ACTIVITY

BEGIN

END

YES

ACTIVITYNO

NO

YES


Flow chart


Check Sheet

• Defect concentration diagram

• A check sheet is a structured, prepared form for collecting and analyzing data. This is a generic tool that can be adapted for a wide variety of purposes

• A simple document used for collecting data in real time and at the location where the data is generated.


When is it used?

• When data can be observed and collected repeatedly by the same person or at the same location.

• When collecting data on the frequency or patterns of events, problems, defects, defect location, defect causes, etc.

• When collecting data from a production process.


Check sheet

Wrong admission

Wrong diet

Late Discharges

Staff not punctual for duty

Missing CSSD item

Problems identified in the Wards

7 tools of quality

7 tools of quality

quality tools and techniques- 7 tools of quality

Healthcare