This is part two of the Quality Improvement tools lecture

1. M t d lit t lManagement and quality tools
Ola H. Elgaddar
MBChB MS MD CPHQ LSSGBMBChB, MSc, MD, CPHQ, LSSGB
Lecturer of Chemical Pathology
Medical Research Institute
Alexandria UniversityAlexandria University
Ola.elgaddar@alexu.edu.eg

2. Performance ImprovementPerformance Improvement
ToolsTools
(II)( )

3. According to the Healthcare Quality
Certification Board (HQCB):Certification Board (HQCB):
I) T l f l iI) Tools for planning:
Hoshin Planningg
Force field analysis
Gantt chartGantt chart

4. A di t th H lthAccording to the Healthcare
Quality Certification Boardy
(HQCB):
II) Tools for team:
B i t iBrainstorming
Affinity diagramy g
Selection grid

5. According to the Healthcare Quality
Certification Board (HQCB):Certification Board (HQCB):
III) Tools for data collection:
IndicatorsIndicators
Check sheets

6. A di t th H lth Q litAccording to the Healthcare Quality
Certification Board (HQCB):
IV) Tools for data analysis:IV) Tools for data analysis:
Run / Control charts
HistogramHistogram
Scatter diagram

7. According to the Healthcare Quality
Certification Board (HQCB):( Q )
IV) T l f t l i (RCA)IV) Tools for root cause analysis (RCA):
Flow chart
Cause - Effect diagram
Pareto chartPareto chart

8. Indicators
Indicators are quantitative measures of
a specific part of a process or of ana specific part of a process or of an
outcome, and comparing it to a target.p g g
By themselves, they don’t directly
lit th th h lmeasure quality, rather, they help
provide data that when analyzed, givep y , g
information about quality

9. Indicators
1) Rate based:1) Rate based:
No of patients with a specified outcome
from a disease management program /from a disease management program /
total No of patients participating in the
programprogram
2) Sentinel event:2) Sentinel event:
100 % analysis and 0 % acceptability
All patients on which wrong side surgry
was performed

10. Indicators
Define:
- The intent
-Numerator and denominator-Numerator and denominator
(Operational definition)( p )
- Reliability
- Validity

12. Indicators
Data triggers:
- Sentinel event
Expected performance rate- Expected performance rate
- Trend (Specified rate change over time)Trend (Specified rate change over time)
- Pattern (Specified diff between groups)

15. Check list
A structured, prepared form for collecting
and analyzing data.and analyzing data.
When to Use a Check Sheet?When to Use a Check Sheet?
When data can be observed and collected
repeatedly by the same person or at therepeatedly by the same person or at the
same location.
When collecting data on the frequency ofWhen collecting data on the frequency of
events, problems, defects, etc.
When collecting data from a productionWhen collecting data from a production
process.

17. Control charts (SPC)Control charts (SPC)
The control chart is a graph used to studyThe control chart is a graph used to study
how a process changes over time.
It has a central line for the average, ang ,
upper line for the upper control limit and a
lower line for the lower control limitlower line for the lower control limit.
These lines are determined from historical
data.data.

18. Control charts (SPC)Control charts (SPC)
By comparing current data to theseBy comparing current data to these
lines, you can draw conclusions abouty
whether the process variation is
consistent (in control) or isconsistent (in control) or is
unpredictable (out of control, affected
by special causes of variation)

19. Control charts (SPC)Control charts (SPC)
Common cause variation:Common cause variation:
Variations are inherent in the process
and remain till the system changes
Special cause variation:Special cause variation:
The variations are considered to be the
effect of many, individually small,
unobserved influencesunobserved influences.

22. Histogram
It shows how often each different value inIt shows how often each different value in
a set of data occurs.
It is the most commonly used graph to
show frequency distributions and to viewshow frequency distributions and to view
how the distribution of the data centers itself
around the mean or main specificationaround the mean, or main specification.
Histograms show the center of the data,
the spread of the data and any data
skewness or outliers.

25. Scatter diagram
The Scatter Diagram is a Quality ToolThe Scatter Diagram is a Quality Tool
that can be used to show the
relationship between "paired data“, i.e:
shows correlationshows correlation.
Strong “r” = Higher correlation, in
ith ideither sides

29. Flow chartFlow chart