measuring quality improvement in healthcare - spc
DESCRIPTION
Measuring Quality Improvement In Healthcare - SPCTRANSCRIPT
Measuring Quality Improvement in
Healthcare
Rosemary Ellis, MSNDirector of Quality
(Turning Data into Information)
Being responsible for a performance improvement project or analysis of a performance indicator can be a daunting task if you are not familiar with Statistical Process Control (SPC)
What is SPC
Statistical Process Control (SPC) Definition:
A data driven method for decision making based on the understanding of process variation.
Understanding SPC
Whether you are looking at medication delivery processes, or promptness in delivering food trays, the first thing you want to do is understand your process as it currently exists. In order to do this you must collect
some data.
Understanding SPCImportant things to consider when
considering data collection: Select only 1 or 2 key indicators that will
tell you how the process is performing. Develop a data collection plan that includes
reasons for collecting data, how the data will be used, an operational definition of the measurement, who and how the data will be collected.
Understanding SPC
QUESTIONS TO CONSIDER:What do you want to measure?Why are you measuring the data?How will you collect the data?Who will monitor the data?What will you do with the reports of
the analysis of the data?
Understanding SPC
How Much Data is Required? JCAHO PI .3.1.1 requires 5% or 30
whichever is greater. Control and run charts require a
minimum of 15 data points to be accurate (25 or more is best).
Measuring a process over time captures the best illustration of how the process is functioning.
Understanding SPC
Turning data into information After collecting the data you have to
analyze the data. Control and run charts will only tell you
about the predictability and capability of your process
In order to determine predictability you have to know something about variation in a process.
Understanding SPC
What is Variation in a process and why is it important? Every process has variation in its outputs and
inputs. This means that no two products- be they
components, reports, services - will ever be the same.
If your job is to fill quart bottles, there will always be some inconsistencies; there will always be a trace more or less than a quart no matter how well you do your job.
Understanding SPC
What is Variation in a process and why is it important? One of the main culprits working to make processes
unreliable or erratic is variation. A process whose capability and performance are
consistent and well understood generally produce a consistent product.
For example, computerized physician order entry results in a process with fewer handoffs, with fewer opportunities for variation, therefore leading to a more predictable time of order fill and time to patient.
Understanding SPC
VariationThere are two types of variation in a
process: Common Cause and Special Cause Common Cause Variation Variance inherent in the process which
is a result of how the process is performed
Understanding SPC
The next slide depicts common cause variation (with the exception of the first two data points)
Common Cause Variation is typically due to a large number of small sources
of variation. it is the sum of small sources of variation that
determines the inherent variation of the process it determines the process limits and its capability
as it is currently operated
Education about your role in safe care: Inpatient
UCL=85.5
CL=78.0
LCL=70.4
50
55
60
65
70
75
80
85
90
95
100
Oct-01 Nov-01 Dec-01 Jan-02 Feb-02 Mar-02 Apr-02 May-02 Jun-02 Jul-02 Aug-02 Sep-02 Oct-02 Nov-02 Dec-02 Jan-03 Feb-03
Month/Year
Mea
n
Data Points
UCL
A
B
Average
B
A
LCL
Goal is 90%
Understanding SPC
The previous slide would be considered “in control” (with the exception of the first two data points) this means unless with a change to the process
occurs the goal of 90% is not obtainable. this process is capable of achieving only
between 70 and 85 as it currently functions. additional information gathering is required to
determine what change would result in an improvement.
Understanding SPC
Special Cause Variation is depicted in the following slide (circled data is area of special cause)
Variance that can be attributed to a particular sourceEquipment problemAbnormal fluctuation in volumeSeasonal VariationFailure to follow procedure which could lead
to and increase in errors
Seclusion and Restraint
CL=0.04
0
0.01
0.02
0.03
0.04
0.05
0.06
0.07
0.08
Nov-00 Dec-00 Jan-01 Feb-01 Mar-01 Apr-01 May-01 Jun-01 Jul-01 Aug-01 Sep-01
November 00 through September 01
rate
per
pat
ient
day U
UCL
A
B
Average
B
A
LCL
Understanding SPC
The following are additional tools to help you turn data into information.
Understanding SPC
Basic Graphs - KEEP IT SIMPLEPie Chart-proportionalPareto Diagram-longest to shortestHistogram-frequency of distributionRun Chart-process over time
Basic graphs are easily compiled in Microsoft Excel
1999 Events Reported by Unit
Pie Chart
Top 5 Risk Management Issues (1999)
Fall found on floor Other IV Infiltrated Med-Other Med-Potential
Co
un
t
Pareto Analysis
Length of Stay
0
2
4
6
8
10
12
14
1 2 3 4 5 6 7
Length of Stay
Fre
qu
en
cyHistogram
Medication Errors Mar 96 to Dec 98
0
20
40
60
80
100
120
Month
Nu
mb
er
of
err
ors
re
po
rte
dRun Chart
Inpatient Fall per Month
Jan-00
Feb-00
Mar-00
Apr-00
May-00
Jun-00
Jul-00
Aug-00
Sep-00
Oct-00
Nov-00
Dec-00
Jan-01
Feb-01
Mar-01
Apr-01
May-01
Jun-01
Jul-01
Aug-01
Sep-01
Oct-01
Nov-01
Fa
lls
Re
po
rte
d
Falls
Mean
UCL
LCL
Control Chart
Understanding SPC
Additional components of graphs Name of creator Date created Source of information-you want your
data to be credible
Know the type of variation in the process before you make changes
The consequences of of not knowing the type of variation are: seeing trends where there are no trends blaming individuals for things they have no
control over. giving credit to others for things they have no
control over. “tampering” or making changes to a process
(without knowing the type of variation) can actually make it worse.
Making Changes in a processIf you have a process that demonstrates
only Common Cause: variation then you are faced with several decisions: if you you satisfied with the performance
then continue to monitor. you may determine that the process
performs so poorly you design a new process.
you may need to gather additional information before making any changes.
Making Changes in a processIf you have a process that
demonstrates Special Cause: you must eliminate the special cause
first (if you are able) the harder job begins because
eliminating common causes requires in-depth knowledge of the subject matter.
you may need to gather additional information before making any changes
All data used in this presentation is for the purpose of example only
END