Chapter 2. Relationships to Existing Patient Safety Efforts and Tools
Introduction
After the publication of the Institute of Medicine (IOM)
report, To Err is Human,1 patient safety deficits moved to
the forefront of public attention. The goal of the report
was a challenging one: to reduce medical errors by half in
5 years. Those 5 years have passed, and substantial effort
has been invested in reducing errors in health care. This
chapter focuses on how many of these efforts relate to
mistake-proofing and how new tools can contribute to
improved patient safety.
Mistake-proofing has been used effectively in other
industries and has been adopted in medicine as an artifact
of common sense applied to processes. More can be done.
In many cases, mistake-proofing will fit into a variety of
existing efforts to improve patient safety. In other cases, it
provides an effective alternative direction to seek
improvement in the face of ineffective actions.
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Relationships to Existing Patient Safety Efforts
The relationship of mistake-proofing to current patient
safety efforts is shown in Table 2.1. Many of the efforts to
improve patient safety are important enablers of mistake-proofing.
They create a foundation for, or aid in, mistake-proofing
implementation. Others are areas of opportunity
in which existing patient safety efforts create resources for
identifying likely mistake-proofing projects. Some efforts
address the same problems as mistake-proofing. While
these techniques are listed as competing there is no
requirement for mutual exclusivity. Multiple approaches
are not only possible, they are recommended. In cases in
which some competing approaches are onerous or
ineffective, mistake-proofing can reduce the scope and
burden of these efforts so that they may be used only
where they are needed most.
Table 2.1 includes some
overlapping concepts; both "creating a just culture" and
"enhancing attentiveness," for example, can be seen as
subsets of safety culture. Each of the relationships in Table 2.1 is also discussed in the next several pages.
Mistake-proofing has been used effectively in other
industries and has been adopted in medicine as an
artifact of common sense as applied to processes.
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Safety Culture
Safety culture is a set of attitudes, values, perceptions,
norms, and behaviors that tend to reduce the likelihood of
unsafe acts, and which encourage thorough disclosure of,
and learning from, adverse events.3 Safety culture also
includes norms of high reliability organizations, as
described by Weick and Sutcliffe:4
- Preoccupation with failure.
- Reluctance to simplify interpretations.
- Sensitivity to operations.
- Commitment to resilience.
- Deference to expertise.
Just Culturea
Just culture refers to a working environment that is
conducive to "blame-free" reporting but also one in which
accountability is not lost.5 Blame-free reporting ensures
that those who make mistakes are encouraged to reveal
them without fear of retribution or punishment. A policy
of not blaming individuals is very important to enable and
facilitate event reporting which in turn, enables mistake-proofing.
The concern with completely blame-free
reporting is that egregious acts, in which punishment
would be appropriate, would go unpunished. Just culture
divides behavior into three types: normal, risk-taking, and
reckless. Of these, only reckless behavior is punished.
a. For more information on Just Culture, see Patient Safety and the
just culture: A primer for health care executives by David Marx, J.D. (2001), on the Web at http://www.mers-tm.net/support/Marx_Primer.pdf.
Event Reporting
Event reporting refers to actions undertaken to obtain
information about medical events and near-misses. The
reporting reveals the type and severity of events and the
frequency with which they occur. Event reports provide
insight into the relative priority of events and errors,
thereby enabling the mistake-proofing of processes.
Consequently, events are prioritized and acted upon more
quickly according to the seriousness of their consequences.
Root Cause Analysis
Root cause analysis (RCA) is a set of methodologies for
determining at least one cause of an event that can be
controlled or altered so that the event will not recur in the
same situation. These methodologies reveal the cause-and-effect
relationships that exist in a system. RCA is an
important enabler of mistake-proofing, since mistake-proofing
cannot be accomplished without a clear
knowledge of the cause-and-effect relationships in the
process.
Care should be taken when RCA is used to
formulate corrective actions, since it may only consider
one instance or circumstance of failure. Other
circumstances could also have led to the failure. Other
failure analysis tools, such as fault tree analysis, consider all
known causes and not just a single instance. Anticipatory
failure determination6 (AFD™) facilitates inventing new
circumstances that would lead to failure given existing
resources.
Corrective Action Systems
Corrective action systems are formal systems of policies
and procedures to ensure that adverse events are analyzed
and that preventive measures are implemented to prevent
their recurrence. Normally, the occurrence of an event
triggers a requirement to respond with counter-measures
within a certain period of time. Mistake-proofing is an
effective form of counter-measure. It is often inexpensive
and can be implemented rapidly.
It is also important to look at all possible outcomes and
counter-measures, not just those observed. Sometimes,
mistake-proofing by taking corrective action is only part of
the solution. For example, removing metal butter knives
from the dinner trays of those flying in first class
effectively eliminates knives from aircraft, but does not
remove any of the other resources available for fashioning
weapons out of materials available on commercial
airplanes.7 This is mistake-proofing but not a fully
effective counter-measure.
Corrective action systems can also serve as a resource to
identify likely mistake-proofing projects. Extensive
discussion and consultation in a variety of industries,
including health care, reveal that corrective actions are
often variations on the following themes:
- An admonition to workers to "be more careful" or "pay attention."
- A refresher course to "retrain" experienced workers.
- A change in the instructions, standard operating procedures, or other documentation.
All of these
are essentially attempts to change "knowledge in the
head."8
Mistake-proofing is an effective form of counter-measure.
It is often inexpensive and can be implemented rapidly.
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Chappell9 states that "You're not going to become world
class through just training, you have to improve the system
so that the easy way to do a job is also the safe, right way.
The potential for human error can be dramatically
reduced."
Mistake-proofing is an attempt to do what Norman8
recommends, put "knowledge in the world."
Consequently, corrective actions that involve changing
"knowledge in the head" can also be seen as opportunities
to implement mistake-proofing devices. These devices
address the cause of the event by putting "knowledge in
the world."
Not all corrective actions deserve the same amount of
attention. Therefore, not all corrective actions should be
allotted the same amount of time in which to formulate a
response. Determining which corrective actions should be
allowed more time is difficult because events occur
sequentially, one at a time. Responding to outcomes that
are not serious, common, or difficult to detect should not
consume too much time. For events that are serious,
common, or difficult to detect, additional time should be
spent in a careful analysis of critical corrective actions.
Specific Foci
Substantial efforts to improve patient safety have been
focused on specific events such as falls, medication errors,
use of anesthesia, transfusions, and communication. These
specific foci provide areas of opportunity for the
implementation of mistake-proofing.
Simulation
There have been many discussions in health care circles
concerning the application of methods developed in the
aviation industry to improve patient safety. In aviation,
simulation is used to train pilots and flight crews.
Logically enough, simulators have also begun to be
employed in medicine. In addition to training, simulation
can provide insights into likely errors and serve as a
catalyst for the exploration of the psychological or causal
mechanisms of errors. After likely errors are identified and
understood, simulators can provide a venue for the
experimentation and validation of new mistake-proofing
devices.
Technology
Technological solutions to patient safety problems have
generated substantial interest. Bar coding and
computerized physician order entry (CPOE) systems, in
particular, are being widely implemented. Both of these
technologies are, in fact, forms of mistake-proofing,
despite their tendency to be more expensive and complex
than the mistake-proofing characterized in Table 1.6.
Facility Design
The study of facility design complements mistake-proofing
and sometimes is mistake-proofing (Figure 2.1).
Adjacency, proper handrails and affordances,
standardization, and the use of Failure Modes and Effects
Analysis (FMEA) as a precursor are similar to mistake-proofing.
Ensuring non-compatible connectors and pin-indexed
medical gases is mistake-proofing.
Revising Standard Operating Procedures
When adverse events occur, it is not uncommon for
standard operating procedures (SOPs) to be revised in an
effort to change the instructions that employees refer to
when providing care. This approach can either improve or
impair patient safety, depending on the nature of the
change and the length of the SOP. If SOPs become
simpler and help reduce the cognitive load on workers, it
is a very positive step. If the corrective responses to adverse
events are to lengthen the SOPs with additional process
steps, then efforts to improve patient safety may actually
result in an increase in the number of errors.
Evidence
from the nuclear industry suggests that changing SOPs
improves human performance up to a point but then
becomes counterproductive. Chiu and Frick10 studied the
human error rate at the San Onofre Nuclear Power
Generation Facility since it began operation. They found
that after a certain point, increasing procedure length or
adding procedures resulted in an increase in the number of
errors instead of reducing them as intended. Their findings
are shown in Figure 2.2. Their facility is operating on the
right side of the minimum, in the region labeled B.
Consequently, they state that they "view with a jaundiced
eye an incident investigation that calls only for more rules
(i.e., procedure changes or additions), and we seek to
simplify procedures and eliminate rules whenever possible."
While there is no comparable study in health
care, prudence suggests that increases in the complexity of
standard operating procedures should be considered
carefully to ensure that the benefits of the additional
instructions exceed the problems generated by the added
complexity. Simplifying processes and providing clever
work aids complement mistake-proofing and in some
cases may be mistake-proofing. When organizations
eliminate process steps, they also eliminate the errors that
could have resulted from those steps.
Attention Management
Substantial resources are invested in ensuring that workers,
generally, and medical personnel, particularly, are alert and
attentive as they perform their work. Attention
management programs range from motivational posters in
the halls and "time-outs" for safety, to team-building
"huddles" (Figure 2.3). Eye-scanning technology
determines if workers have had enough sleep during their
off hours to be effective during working hours.11
When
work becomes routine and is accomplished on "autopilot"
(skill-based12), mistake-proofing can often reduce the
amount of attentiveness required to accurately execute
detailed procedures. The employee performing these
procedures is then free to focus on higher level thinking.
Mistake-proofing will not eliminate the need for
attentiveness, but it does allow attentiveness to be used
more effectively to complete tasks that require deliberate
thought.
Crew Resource Management
Crew resource management (CRM) is a method of
training team members to "consistently use sound
judgment, make quality decisions, and access all required
resources, under stressful conditions in a time-constrained
environment."13 It grew out of aviation disasters where
each member of the crew was problem-solving, and no
one was actually flying the plane. This outcome has been
common enough that it has its own acronym: CFIT—Controlled Flight Into Terrain.
Mistake-proofing often takes the form of reducing
ambiguity in the work environment, making critical
information stand out against a noisy background,
reducing the need for attention to detail, and reducing
cognitive content (for details on cognitive content, go to
Chapter 4). Each of these benefits complements CRM
and frees the crew's cognitive resources to attend to more
pressing matters.
FMEA or FMECA?
FMEA and FMECA are "virtually the same,"14 except for a
few subtleties that have been more or less lost in practice
(hereafter simply referred to as FMEA). These two related
tools enable teams to analyze all of the ways a particular
component or process can fail, predict what the
consequences of that failure would be, and prioritize
remedial change actions.
FMEA and FMECA are form- or worksheet-based
approaches. Since forms are easily manipulated to meet
users' needs, rarely are two forms exactly the same.15-18
Regardless of which version of FMEA is selected, certain
aspect of the analysis will be included.
The FMEA process
is begun by creating a graphical description of the
sequence of tasks being analyzed, referred to as a process
map. Several books are devoted exclusively to process
mapping.19-23 The team lists all the failures that could
occur at each task on the FMEA form. The scope of this
step must be managed carefully to keep it from becoming
tremendously onerous. Often, only a small subset of tasks
is considered at one time. After failures have been
identified, the potential effects of each failure are specified,
and the severity of each is assessed. Potential causes are
identified. The team then assesses the likelihood of each
occurrence and the probability of detecting the cause
before harm is done. The severity, the likelihood of
occurrence, and the detectability of each cause are
combined into a priority ranking.
A common method is
to rank severity (sev), likelihood of occurrence (occ), and
detectability (det) on a 10-point scale and then multiply
them together. The product is often called the risk priority
number (RPN). An example of these RPN calculations is
shown in Figure 2.4. With FMECA, the risk priority
number of each cause is summed to create a mode
criticality number. Failure causes (or failure modes for
FMECA) are then prioritized, and preventive actions are
taken. In Figure 2.4, the cause "strip of labels with
multiple patient names mixed" is the highest priority
cause. "Order entry error" is the lowest priority. Little
indication of what actions should be taken is provided by
authors writing about FMEA. However, the logic of
FMEA implies that the RPN after the prevention effort
should be less severe, less likely to occur, or more easily
detected. A detailed discussion is included in Chapter 3.
In an FMEA analysis, rank severity, likelihood, and
detectability on a 10-point scale and multiply them to
determine the risk priority number (RPN).
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Fault Trees
FMEA is a bottom-up approach in the sense that it starts
at the component or task level to identify failures in the
system. Fault trees are a top-down approach. A fault tree
starts with an event and determines all the component (or
task) failures that could contribute to that event.
A fault tree is a graphical representation of the
relationships that directly cause or contribute to an event
or failure. Figure 2.5 shows a generic fault tree. The top of
the tree indicates the failure mode, the "top event." At the
bottom of the tree are causes, or "basic failures." These
causes can be combined as individual, independent causes
using an "OR" symbol. They can be combined using an
"AND" symbol if causes must co-exist for the event to
occur. The tree can have as many levels as needed to
describe all the known causes of the event.
These failures can be analyzed to determine sets of basic
failures that can cause the top event to occur, cut sets. A
minimal cut set is the smallest combination of basic
failures that produces the top event. A minimal cut set
leads to the top event if, and only if, all events in the set
occur. This concept will be employed in Chapter 3 to
assess the performance of mistake-proofing device designs.
These minimal cut sets are shown with dashed lines in
Figure 2.5.
Fault trees also allow one to assess the probability that the
top event will occur by first estimating the probability that
each basic failure will occur. In Figure 2.5, the
probabilities of the basic failures are combined to calculate
the probability of the top event. The probability of basic
failures 1 and 2 occurring within a fixed period of time is
20 percent each. The probability of basic failure 3
occurring within that same period is only 4 percent.
However, since both basic failures 1 and 2 must occur
before the top event results, the joint probability is also 4
percent. Basic failure 3 is far less likely to occur than
either basic failure 1 or 2. However, since it can cause the
top event by itself, the top event is equally likely to be
caused by minimal cut set 1 or 2.
Two changes can be made to the tree to reduce the
probability of the top event:
- Reduce the probability of basic failures.
- Increase redundancy in the system.
That
is, design the system so that more basic failures are
required before a top event occurs.
If one nurse makes an
error and another nurse double checks it, then two basic
failures must occur. One is not enough to cause the top
event.
FMEA and fault trees are useful in understanding the
range of possible failures and their causes.
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The ability to express the interrelationship among
contributory causes of events using AND and OR symbols
provides a more precise description than is usually found
in the "potential cause" column of an FMEA. Potential
causes of an FMEA are usually described using only the
conjunction OR. It is the fault tree's ability to link causes
with AND, in particular, that makes it more effective in
describing causes. Gano2 suggests that events usually occur
due to a combination of actions and conditions; therefore,
fault trees may prove very worthwhile. FMEA and fault
trees are not mutually exclusive. A fault tree can provide
significant insights into truly understanding potential
failure causes in FMEA.
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Knowing What Errors Occur, and Why, Is Not Enough
FMEA and fault trees are useful in understanding the
range of possible failures and their causes. The other
tools—safety culture, just culture, event reporting, and
root cause analysis—lead to a situation in which the
information needed to conduct these analyses is available.
These tools, on their own, may be enough to facilitate the
design changes needed to reduce medical errors. Only
fault tree analysis, however, comes with explicit
prescriptions about what actions to take to improve the
system.
These prescriptions, which will be discussed
further in Chapter 3, are: increase component reliability or
increase redundancy. Fault trees are also less widely known
or used than other existing tools. FMEA is far more widely
used, in part because it is a popular method of meeting the Joint Commission's
(JCAHO) requirement to perform proactive risk
assessment.
FMEA calls for action. Most versions of FMEA do not
provide explicit prescriptive information about what action
to take. Only JCAHO explicitly prescribes redesigning the
process. With the exception of the less-utilized fault tree
analysis, the tools used in patient safety improvement
efforts are currently focused on determining what events
and errors occur and what causes them. They are silent
about how to fix the problem or prevent the cause of
failure from recurring. Even JCAHO,24 which explicitly
identifies redesign as the preferred approach for increasing
patient safety, provides little direction about how to
accomplish it. JCAHO provides three questions that must
be answered at the "redesign the process" step:
- How can we change the process to prevent this failure mode from occurring?
- What design/redesign strategies and tools should we use? How do we evaluate their likely success?
- Who should be involved in the design/redesign process?
These are the crucial questions and, like Fermat's Last
Theorem,b are left as an exercise for the reader.
A recurring theme in quality improvement literature is
that we are good at identifying problems but not so good
at devising methods to solve them. Numerous tools are
available to define, measure, and analyze quality problems
and control processes. Six-sigma is a popular quality
improvement framework. It has an improvement cycle that
involves five problem-solving steps: define, measure,
analyze, improve, and control. The tools available to
actually conceive of what the improvement should be are
limited. In a 191-page quality management quick
reference guide,25 only 12 pages were devoted to tools for
actually improving the process (Figure 2.6). Worse, those
pages are devoted to managing the process of
implementing the improvement, not how to determine
what the improvement should be.
Determining what the improvement should be is an
inventive problem that will require some creativity. Tools
to facilitate the inventive solution to determining how to
design devices that will mistake-proof the process are
introduced in the next section and presented in detail in
Chapter 3.
b. Pierre de Fermat (1601-1665) was a French lawyer and number
theorist known for his last theorem, which was discussed for
hundreds of years until it was solved in 1995 by mathematician
Andrew John Wiles (1953-). Wiles had been working on solving
the theorem since 1963. The Last Theorem states that xn + yn =
zn has no non-zero integer solutions for x, y, and z when n > 2.
Go to http://www.groups.css.st-and.ac.uk/~history/HistTopics/Fermat's_Last_theorem.html.
Return to Contents
Using the Tools Together
Figure 2.7 shows a flowchart of how patient safety tools
can be used together with other management tools to
reduce human error and create mistake-proofing devices.
Enabling Tools
The box to the left in Figure 2.7 contains enabling tools
that provide a foundation for designing effective mistake-proofing
devices. The design tools in the center box
require detailed information about the process and a
thorough understanding of cause-and-effect relationships
as inputs to be analyzed. The enabling tools provide these
inputs.
Process mapping defines the current process. A process is
"a collection of interrelated work tasks, initiated in
response to an event, achieving a specific result for the
customer and other stakeholders of the process."16
Thinking of health care as a process and then mapping
that process is a critical step in improving the process.
Process mapping is also an early step in performing
FMEA. "Graphically describing the process" is Step 3 in
healthcare failure modes and effects analysis
(HFMEA)™.12 Flow charting, one style of process
mapping, is utilized in Steps 1 and 2 in JCAHO's
recommended FMECA process.16 A detailed
understanding of the process also provides insights into
where specific errors might be detected and how likely that
detection is to occur.
Having a just culture that is fair and open will foster event
and near-miss reporting. Reporting provides insights into
what events occur, how often they occur, and the
outcome's level of seriousness when they occur.
Information about the frequency and severity of adverse
events facilitates the prioritization of process improvement
efforts. Knowing a failure occurred should trigger an event
investigation and subsequent root cause analysis.
Root cause analysis determines what cause-and-effect
relationships lead to events in the process. There is an
implicit expectation that the cause-and-effect relationships
of a process are understood in FMEA. The potential
causes of an event must be listed for each failure mode. Fault tree analysis also assumes an understanding of cause
and effect. Fault trees go beyond FMEA by stating the
relationships among multiple causes that would lead to the
event taking place.
Visual systems create an environment where mistake-proofing
can be used more effectively (Chapter 1).
Visual cues indicating what action to take are more
obvious when distractions are removed, and
standardization provides points of reference to enable
employees to detect and prevent errors.
Design Tools
The central box in Figure 2.7 contains tools that facilitate
the design of mistake-proofing devices. The tools are listed
and employed in a sequential manner. FMEA is first. No
additional design tools are needed if, after conducting an
FMEA and brainstorming for possible solutions, an
adequate number of possible solutions is generated. The
next step is to select and implement the best solution
available.
There is no reason to think that the first solution arrived
at will be the best overall solution. Teams should
determine the optimal number of solutions to be
developed before deciding on the best one, shown as "n"
in Figure 2.7. Pella Window™ engineers26 reported that
they develop and test seven solutions before making a
decision. One step in their decisionmaking process is to
fabricate cardboard and scrap-wood prototypes of
equipment that can be tested and compared by workers
and engineers.
A similar approach was used by St. Joseph's Hospital in
West Bend, WI. The team focused on creating a patient
safety-centered design for their new building.27 To facilitate
the design process, they tore out two rooms of the existing
hospital and mocked up one new room so that staff
members could walk through it, visualize working in it,
and identify improvements. The St. Joseph's room is
shown in Figures 2.8, 2.9, and 2.10. Figure 2.10 shows a
page of comments taped to the wall. This page is
concerned only with the bathroom light fixture. Staff
members filled several sheets as they explored the mock-up
room.
St. Joseph's Hospital relied heavily on FMEA. The mock-up
room helped them to identify failure modes and think
through creative new solutions. The new facility opened in
August 2005.27
Teams can employ a similar approach on a smaller scale
for most mistake-proofing device implementation. As
mentioned in Chapter 1, Hirano28 suggests that if a device
has a greater than 50-percent chance of success, teams
should stop analyzing the situation and immediately
attempt a mock-up of the solution. Some refer to this
approach as "trystorming." Trystorming extends
brainstorming by quickly creating mock-ups that can be
rapidly and thoroughly evaluated. Given many mistake-proofing
devices' low implementation cost and simplicity,
it is logical to fabricate an early mock-up before
continuing with analysis.
A fault tree is used to model the situation further in cases
where FMEA does not yield a sufficient number of
potential solutions. Fault trees add information that may
not appear in FMEA. The use of AND and OR nodes, the concept of minimal cut sets, and the use of probabilistic
information in fault tree analysis enable a more accurate
assessment of the impact of potential mistake-proofing
devices. More brainstorming is called for after the
completion of the fault tree analysis. Teams should
proceed to selection and implementation only after
generating a sufficient number of solutions.
If, after employing FMEA and fault tree analysis, teams
still do not generate enough potential solutions, the next
logical step is to employ multiple fault trees, a technique
discussed in detail in Chapter 3. Multiple fault tree
analysis aids in converting the problem from one of how
to stop failures from happening into one of how to make
failures happen. The question here is, "Which failure
would be more benign, and how can we generate that
failure?" Fault trees that were initially used to analyze
undesirable failures are used here to explore resources and
generate benign failures.
If the number of design changes resulting in benign
failures is still not sufficient, the next step is to employ
creativity, invention facilitation techniques, or software. A
variety of techniques, methodologies, and software could
be used here. One promising approach, TRIZ, has its
genesis in the work of Genrich Altschuller.29-31 He created
an inventive algorithm called the "Theory of Inventive
Problem Solving." Its Russian acronym is transliterated as TRIZ. The
TRIZ algorithm is designed for groups to find new ideas
on how to approach a problem; to formulate the specific
problem in general terms, then identify past approaches—which originate in a Russian patent database—that have
been successful. TRIZ is complex and requires extensive
reading and/or training. Learning is made somewhat easier
by the TRIZ software, which assists in the learning
process.
If teams still need more potential solutions, they might
consider designing a process that embeds cues about how
to do the work correctly.c Norman's concepts from Table 1.6—natural mappings, affordances, visibility, feedback,
and constraints—are used here.
It would be unrealistic to assume that all problems lend
themselves to a solution. If every attempt fails, teams may
have to give up, at least in the short run. Before giving up,
though, teams should consider a change in focus; explore
sub-systems or super-system changes that might provide
an alternative problem that is more easily solved. Can the
process step be moved to a more advantageous area or
combined with another step? What would need to change
in order for this task to be entirely unneeded and
eliminated?
Selecting a solution
Let us assume that a team is not forced to give up, and
that the process described above yielded a cornucopia of
possible solution approaches. There are now many
directions in which to embark in the search for
improvement, especially when employing TRIZ software.
The team is now confronted with a delightful dilemma:
how to determine which solutions are the most promising.
Godfrey et al.,32 provide an answer, the solution priority
number (SPN). The SPN concept is very similar to
FMEA's risk priority number (RPN). The SPN is the
product of a solution's effectiveness, cost, and ease of
implementation, as shown in Table 2.2. The best solutions
will have high SPN scores: 12, 18, and 27 are the highest
possible scores. (Because SPN is the product of integer
scores, no intermediate scores, such as 13, 19, or 26, are
possible). These high-scoring solutions will be very
effective, cost very little, and be exceptionally easy to
implement.
A high SPN (Table 2.3) is an indication that a solution is
promising. It does not obviate the need for careful
consideration of device design issues. Human factors like
process usability and time constraints placed on workers
still must be considered. Devices must not negatively
affect the usability of a process or slow the process
noticeably, particularly when resources such as nurse
staffing levels are constrained. Staff will find ways to
accomplish their responsibilities, even if it means disabling
devices (Chapter 4).
c. Embedded cues about how to use the process should be placed
throughout facilities, regardless of which mistake-proofing
efforts are undertaken. Mutual exclusivity of tools or approaches
is not warranted or advisable. Cues are often less effective in
stopping errors. They can still be quite effective, however, in
avoiding them.
Table 2.3. Possible SPN scores and combinations
Possible SPN scores | Number of combinations resulting in that score |
1 |
1 |
2 |
3 |
3 |
3 |
4 |
3 |
6 |
6 |
8 |
1 |
9 |
3 |
12 |
3 |
18 |
3 |
27 |
1 |
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Conclusion
Mistake-proofing does not obviate the need for many of
the tools currently in use in patient safety environments; it
uses the insights these tools generate to aid in the design
of safer systems and processes.
Regrettably, even with these tools at teams' disposal,
determining what design change to make is not as well defined
as Figure 2.7 would suggest. Creativity, at its core,
is not a linear process. The tools contribute to our ability
to make sense of a situation, determine what needs to be
done, and decide how to do it. The actual solutions could
yet require a leap of creativity, a flash of inspiration. The
intent of Figure 2.7 and the tools it contains is to reduce
the size of the leap.
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References
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