Shared Decision Making
Design and Testing of Tools for Shared Decision Making
Daniel D. Matlock, MD, MPH; Erica S. Spatz, MD, MHS
S
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participants’ decisional needs (eg, knowledge, values, support)
will affect the decisional quality (informed, values concordant
decisions), which ultimately impacts subsequent outcomes
such as emotions (regret, blame), behavior, and appropriate
use of health services. Recently, some developers have argued
that development should include a more active and iterative
process using end-users in all phases of the development.16
These developers have used a participatory action research
framework in which both patients and clinicians participate in
tool development during real-world clinical encounters with
embedded researchers, making modifications based on observations of how the tool is ultimately used.
Regardless of the approach, developers of PtDAs should
aim for 3 main attributes: (1) correct and accurate content,
(2) readability and usability, and (3) acceptability and lack of
bias. Table 1 outlines a typical PtDA development process.
The fourth attribute is ensuring that the PtDA is effective in
improving the quality of decisions. Effectiveness of PtDAs is
the topic of a separate article in this series. Throughout the
development process, developers should draw on the expertise of a multidisciplinary team. The team might consist of
(but is not limited to) patients, clinicians, and experts in evidence synthesis, information technology, health literacy, and
graphic design.
hared decision making (SDM) is grounded in a compelling theoretical framework that ideally helps patients make
decisions that are informed and concordant with their goals
and values.1,2 Yet operationalizing SDM within routine clinical
care remains an important challenge. Several approaches have
been studied to improve SDM; such strategies include educating clinicians on communication techniques, using a multidisciplinary medical team, incorporating trained decision
coaches, and using tools to support patients in their decision
making. These tools, commonly referred to as patient decision
aids (PtDAs), have garnered the most interest in operationalizing SDM.3 Accordingly, this article will focus specifically
on the development and testing of PtDAs highlighting some
important key points (see Box).
Extensive work has been undertaken by the International
Patient Decision Aid Standards (IPDAS) collaboration to provide guidance in this arena. Founded in 2003, IPDAS aims
to “enhance the quality and effectiveness of PtDAs by establishing an evidence-informed framework for improving their
content, development, implementation, and evaluation.”4,5
This article will draw on the extensive work of the IPDAS collaboration to describe a 4-step development process for those
interested in developing PtDAs, which includes, step 1: understanding the decision; step 2: drafting the first version of the
decision aid; step 3: iteratively modifying the tools; and step
4: testing the decision aid in a real-world setting. Additionally,
we will discuss potential opportunities to expand the work of
the IPDAS collaboration to improve uptake of the PtDA in the
clinical setting.
Step 1: Understand the Decision - What Do the
Data Suggest About the Risks and Benefits of
the Decision Options; What Is the Context of the
Decision for Which the PtDA Is Being Developed?
Step one is to gather information about the decision for which
the PtDA is being developed. Because PtDAs aim to present
information to patients who are actively making decisions, a
deceptively complex question then is what data belong in a
decision aid? Too little information or the wrong information
will not help the decision maker, and too much information may
be overwhelming.17 Before embarking on a full-scale development process, one should check to determine whether a PtDA
has already been developed. A useful resource is the University
of Ottawa A–Z inventory of patient decision aids (http://decisionaid.ohri.ca/AZinvent.php) where developers can register
their decision aids and have them evaluated using IPDAS scoring criteria.18 To determine the relevant content, PtDA developers should review the literature regarding the risks and benefits
Development and Design of Decision Aids
Several theoretical frameworks have been used in the development of PtDAs.6,7 Common theories used by developers
include the behavioral decision framework,8 expected utility
theory,9 prospect theory,10 decision conflict theory,11 differentiation and consolidation,12 fuzzy trace theory,13 and image
theory.14 Although a complete discussion of decision-making
theory is beyond the scope of this article, an excellent summary of major decision theories and their implications on
decision aid design were recently summarized by the IPDAS
collaboration.7 One commonly used PtDA development framework that is based on several of these theories is the Ottawa
Decision Support Framework.6,15 This framework states that
Received October 5, 2013; accepted March 4, 2014.
From the University of Colorado School of Medicine, Aurora, CO (D.D.M.); The Colorado Cardiovascular Outcomes Research Consortium, Denver,
CO (D.D.M.); and Section of Cardiovascular Medicine, Center for Outcomes Research and Evaluation, Yale-New Haven Hospital/Yale University School
of Medicine, New Haven, CT (E.S.S.).
Correspondence to Daniel D. Matlock, MD, MPH, Division of General Internal Medicine; University of Colorado School of Medicine, Academic Office
1, 12631 E, 17th Ave, Campus Box B-180, Aurora, CO 80045. E-mail [email protected]
(Circ Cardiovasc Qual Outcomes. 2014;7:00-00.)
© 2014 American Heart Association, Inc.
Circ Cardiovasc Qual Outcomes is available at http://circoutcomes.ahajournals.org
1
DOI: 10.1161/CIRCOUTCOMES.113.000289
2 Circ Cardiovasc Qual Outcomes May 2014
Key Points of the Article on
Decision Tool Development
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• PtDAs should be used in conjunction with a conversation with a clinician.
• Helping patients consider and clarify their values
around a decision is what makes a PtDA different
from an information pamphlet.
• Development is iterative, and the key tasks are to
make sure the information is understandable, accurate, and unbiased and that the tool fits the needs and
workflow of the end-users.
• Trials designed to test the effectiveness of a decision
aid need to consider both the patient’s and the clinician’s experience with the tool.
• Decision aids should be living documents that will
require updating when new information arises.
of all possible choices, and this information should be summarized in a background evidence document or in a systematic
review.18 This background evidence document becomes important when users begin reviewing the decision aid, as the data
presented are often a source of contention. Also, the medical
literature frequently contains articles with divergent results, and
developers will need to decide what data to present in the PtDA.
In the case of implantable cardioverter-defibrillators, there are
many conflicting studies about the risks, some of which are
related to the different definitions of risk and different time
frames for follow-up.19 Furthermore, some data originate from
randomized, controlled trials (RCTs), and other data originate
from observational studies. In general, the benefit of a therapy
is most easily derived from an RCT, whereas one can argue that
real-world risks may be more accurately derived from an observational study.20 However, these decisions are complicated, and
stakeholders often disagree on what data should be presented in
a PtDA. Regardless of the source of information, the PtDA will
need to be routinely reviewed and updated to ensure that it is
consistent with current evidence.
In addition to a comprehensive literature review, PtDA
developers should gain a deeper understanding of the decisionmaking needs and experiences of the participants involved.
This can be accomplished through strategies ranging from surveys to in-depth interviews to observed encounters. This process is essential and will allow the developer to gain a deeper
understanding of the context in which the PtDA will ultimately
be implemented. In the case of implantable cardioverter-defibrillators, many issues were learned from the qualitative needs
assessment that would never have been understood through a
literature review alone (eg, the importance of guidelines, the
influence of device recalls, the lack of understanding about
deactivation, and the importance of discussing inappropriate
shocks and driving a car).21
Step 2: Developing a First Draft of the PtDA
At some point in the information-gathering process, the developer will need to draft the first version of the PtDA. The initial
approach needs to consider 2 key questions in tandem, as 1
will inform the other: (1) what type of tool to develop, and (2)
when to introduce the PtDA in the clinical pathway. Current
PtDAs come in many forms, including article, videos, websites, and even scripted telenovelas.3,22 Each of these forms has
been shown to be helpful in supporting decision making, and
there is little guidance on precisely which format is best.3 The
type of tool should be informed by the needs assessment, the
target population, the context of the decision, and the resources
available for development as videos and websites are markedly more expensive to develop. Developers additionally need
to consider when in the d­ ecision-making process to introduce
a PtDA, that is, before, during, or after the clinical encounter. Implementation of the PtDA may be based on feasibility
and cost and ultimately guide the type of tool developed. For
example, if the intention is for a PtDA to be viewed before
a clinical encounter, then a web-based tool may be more or
less ideal depending on the target populations’ access to and
comfort with computers. Table 2 lists the advantages of several
common types of tools that have been developed.
The next question faced by a decision aid developer is
what to put in the PtDA? The IPDAS collaboration provides
guidance. Although each decision is different and the actual
content of the PtDA should ultimately be determined by the
literature review, needs assessment, and iterative participant
testing, the IPDAS checklist serves as a useful guideline for
drafting the initial PtDA.4 The IPDAS includes the following
4 main domains: (1) What is the decision? (2) What are the
risks/benefits? (3) What are the important values to consider
Table 1. Steps of Decision Aid Development
Step 1 – Understand the decision
- Literature review: Aggregate the appropriate data (effectiveness and risks)
surrounding a given intervention and summarize in a formal document.
- Needs assessment: Determine what patients and clinicians think are
important attributes of the decision. This process is often done through
qualitative interviews or written surveys.
Step 2 – Develop the initial draft of the decision aid based on user input in step 1
- Determine the type of tool that would be useful and feasible for the given
decision situation (video, article, web-based, etc)
- Consider when to introduce the PtDA in the clinical encounter (before,
during, or after) because this may influence the type of tool developed
- Use the IPDAS criteria as a guide for what to include in a decision aid. At a
minimum, the tool should:
a. Identify a decision that needs to be made
b. Describe the risks and benefits of all options
c. Assist people in clarifying their values, either explicitly or implicitly
d. Empower the person regarding the next steps in the decision-making
process
Step 3 – Iteratively modify the tools with end-users
- Test the tool with all end-users, including patients, clinicians, and any
other potential participants (eg, caregivers) who have a relevant role in the
decision making as determined by the needs assessment
- Modify the tool with the goal of improving accuracy, understandability, and
balance
Step 4 – Pilot test and/or implement the tool in a real-world setting
- Researchers can choose from several study designs, including randomized,
controlled trial of patients, clustered randomized trial of clinicians or clinician
groups, and before and after study comparisons
- Each study design has advantages and disadvantages
IPDAS indicates International Patient Decision Aid Standards; and PtDA,
Patient Decision Aid.
Matlock and Spatz Tools for Shared Decision Making 3
Table 2. Advantages and Disadvantages of Different Patient
Decision Aid Formats
Format
Advantages
Disadvantages
Short, article decision
- Short article decision - These tools tend to not be
aids
aids may have
comprehensive and are
Examples: Option grids
more success in
thus unable to meet all of
(www.optiongrid.org)33;
implementation
the IPDAS criteria.
Statin choice article
within a clinical
However, whether all
decision aid – Mayo
encounter.
the IPDAS criteria are
clinic34
- Easy to modify and
necessary to achieve
update
decision quality is a topic
- Inexpensive to
of debate.5
develop
- Often require higher
literacy levels.
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Longer article decision
aids
Examples: AHRQ
booklets35; Ottawa
decision aids.36
- Easy to modify and
update.
- Inexpensive to
develop.
- Comprehensive.
Table 3. Strengths and Weaknesses of Different Study
Designs to Test Patient Decision Aid Formats
- Difficult to implement
during a clinical
encounter. Ideally, these
tools would
be delivered to a
patient before or after
a discussion with a
clinician.
- Often require higher
literacy levels.
Video decision aids
Examples: Health
Dialog Tools37; ACP
Decisions.38
- May be more useful
to populations
with lower health
literacy.39
- Can include patient
vignettes.
- Costly to develop.
- Visual images may
influence decisions in
ways not intended by the
developer.40
Web-based decision
aids
Examples: Healthwise
tools,41 Bresdex.com42
- Can be interactive.
- Can be linked to
electronic medical
records and
tailored to patient
characteristics.
- Can record data as
the participant uses
the decision aid.
- Development and
modification require
technical expertise which
can be costly.
- Patients must have
access to the Internet.
ACP indicates Advance Care Planning; AHRQ, Agency for Healthcare Research
and Quality; and IPDAS, International Patient Decision Aid Standards.
in making the decision? (4) What are the next steps?4 The
Cochrane review of decision aids recently demonstrated that
more detailed decision aids improved knowledge by an additional 5% compared with simpler PtDAs.3
Step 3: Iteratively Modify the Tools With
Potential Participants
After the initial prototype is developed, the tool should be
tested and modified iteratively with end-users including
patients, clinicians, and any other potential participants (eg,
caregivers) who have a relevant role in the decision making as
determined by the needs assessment. Throughout the testing,
the tool should be modified based on the input from the participants to ensure that the tool is accurate, understandable, and
as balanced as possible.4 Achieving balance can be difficult,
particularly as opinions vary between patients and clinicians.
Step 4: Testing the Tool in a Real-World Setting
Once the tool is developed, consideration must be given to the
study design, setting, and implementation of the PtDA. Table 3
Strengths
Weaknesses
RCT at patient level
Minimization of bias and
confounding
Spillover, regardless
of randomization at
patient or clinician level;
disruptive to workflow
Clustered randomized
trial
Contemporaneous
control group; ease with
workflow; minimizes
spillover
Costly, requires
collaborations and
oversight, confounding
by differences in study
groups (unmeasured
variables)
Quasiexperimental
(pre/post)
Stable population
and setting, minimal
confounding, less costly,
ease with workflow
Secular trends (eg,
new data or changes in
attitude influence PtDA
and outcomes), priming
PtDA indicates Patient Decision Aid; and RCT, randomized, controlled trial.
outlines some potential study designs and their strengths and
weakness as applied to decision aids. Randomized, controlled
trials are traditionally perceived as the most rigorous study
design to minimize bias and potential confounders. However,
the dyadic or multidisciplinary nature of shared decision making creates some inherent limitations to randomized trials. If
randomization occurs at the patient level, the same clinicians
will be engaging with patients in both the decision aid and
the usual care arms, increasing the probability for spillover. In
spillover, clinicians may adopt language or processes from the
decision aid into their routine practice, thereby diluting differences between the intervention and usual care groups.23,24 The
majority of trials in the Cochrane review of decision aids were
patient-level randomized trials.3
Clustered randomized trials are particularly important
for decision aids that are designed to be used within a clinical encounter.25 A clustered randomized trial design offers an
attractive alternative to avoid the effects of spillover seen in
patient-level trials. In clustered randomized trials, clinicians or
an entire clinician group are randomized to either use of the
decision aid or to the control with the idea that all patients seen
by a clinician or a clinician group will receive the same care.
Randomizing at the clinician level may not completely avoid
spillover because clinician styles are often influenced by colleagues and cultural norms, which may evolve as the intervention is implemented.26,27 For this reason, it may be preferable to
cluster by clinician group for trials of decision aids and not clinician. The downsides of clustered randomized trials primarily
relate to resources and logistics. Outcomes are assessed at the
level of the group; hence, the sample size is considerably lower
than had randomization occurred at the level of the patient,
which may reduce statistical power from which to draw conclusions. An alternative approach is to assess outcomes at the
patient level; however, patients with similar characteristics
tend to cluster around clinicians and clinician groups, which
may overestimate differences between groups.
Because of the limitations and challenges involved in performing randomized, controlled trials, several researchers
have used quasiexperimental, pre/poststudy designs, whereby
a historical control period is followed and compared with a
4 Circ Cardiovasc Qual Outcomes May 2014
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period of PtDA implementation and evaluation. This design is
efficient and less costly, and the characteristics of the patient
population tend to be stable. One limitation of a pre/poststudy
design is not having a concurrent control group, and thus being
vulnerable to secular trends, for example, changes in attitude
toward the intervention or new data, which may influence outcomes. Additionally, priming may occur, whereby responses
to survey items are influenced by experience with the topic
and question. For example, assessment of clinician behavior
during the control or usual care study period may show that
clinicians perceive themselves as always including patients in
the decision-making process. However, after the implementation of the PtDA, clinicians may newly recognize and report
that they do not regularly engage patients in this type of shared
decision-making process, despite adoption of the PtDA in
their practice. A recent example of this is the before and after
evaluation of the Patient Refined Expectations for Deciding
Invasive Cardiac Treatments (PREDICT) tool for patients
considering percutaneous coronary intervention options.28
Researchers must also decide on the appropriate setting in
which to introduce a decision aid. Presumably, there is a sweet
spot, the period between the patient being presented with a
choice and the point at which a decision needs to be made.29
This is the ideal time for a decision aid. Because PtDAs require
patients to contemplate their values, consider alternatives,
and often make complex decisions, it is important to identify
clinical milestones/windows or opportunities where decision
making can most easily occur.30 The ideal clinical milestone is
not always obvious. If the PtDA is introduced during an acute
change in health status (eg, during an acute myocardial infarction or heart failure exacerbation), the patient may not be prepared to engage in a decision-making process. On the contrary,
the decision needs to be timely and relevant to the patient to
carry import. Consider, for example, a PtDA on left ventricular
assist device (LVAD) implantation for patients with advanced
heart failure. If the PtDA is introduced at the time of hospitalization for an acute exacerbation, when the decision to implant
an LVAD is the difference between life or death, patients may
be too sick to engage in a shared d­ ecision-making process or
may experience decisional regret if they allowed their emotional state, as opposed to their values, to influence their decision.31 The outpatient setting, when patients are stable yet have
end-stage heart failure, may be more ideal. This is the kind
of balance that must be learned early while the investigator is
performing the needs assessment.
Related to setting, researchers must determine (ideally
through the needs assessment) who is the most appropriate clinician to introduce the PtDA. Should it be a practitioner who
has a longstanding relationship with the patient or the surgeon
performing the surgery? For example, it is not clear whether
the interventionalist or the referring clinician is in the best
position to help patients considering a bare metal stent versus
a drug eluting stent for percutaneous coronary intervention.
For the purposes of research, it may be impractical to disseminate PtDAs to all referring providers. Moreover, it is not clear
that interventionalists would accept and carry out decisions
with which they were not involved. On the contrary, referring
clinicians who have a rapport with the patient may be better
able to assess their patients’ values and reflect preferences but
may not be as prepared to discuss the risks and benefits of a
bare metal stent versus a drug eluting stent.
Unique Challenges and Future Directions
Shared decision making in general and PtDAs in particular
are an emerging science. As such, there are many unanswered
questions and a significant need for future research. Below, we
highlight a selection of challenges and controversies among
the development community.
Should Information in a PtDA Be Tailored to the
Individual Patient?
The type and magnitude of risks and benefits associated with
each decisional option may vary based on the characteristics
of the patient. For example, an older patient with more competing morbidities will likely have a smaller benefit and larger
risks for many of the aforementioned therapies. Some argue
that patients should be presented with tailored statistics that
more accurately reflect their clinical situation.28 This is cumbersome in that it often requires a mathematical model or a
host of assumptions to determine which tailored statistics to
provide to any given patient. Whether individual patient decisions are sensitive to this tailoring is unknown.
Can Emotion and Affect Be Addressed in a PtDA?
Much of the work on decision aid development has focused on
the cognitive transfer of information. However, many major
decisions are largely driven by emotion, particularly decisions
involving tradeoffs around quality versus quantity. This affect
heuristic has been shown to influence many cognitive aspects
of decision making.32 For example, we found that many
patients who were hospitalized in an intensive care unit dying
of heart failure were unable to cognitively weigh the risks and
benefits of an LVAD because of their overwhelming fear of
dying.31 Should PtDAs in this setting be designed to address
emotions like fear, and, if so, does this help patients to make
more cognitive decisions?
Are PtDAs Useful for Chronic Disease
Models, in Which Patients Make Multiple
Decisions Over Time?
Traditionally, PtDAs have been conceived and developed to
assist discrete decisions. However, the vast majority of medical decisions are made by patients with chronic illness who
often have to make multiple, repeating decisions during a
long period of time. For example, patients with heart failure
may frequently need to recalibrate decisions about activity,
salt intake, and medications. Can PtDAs be developed to help
patients with recurring decisions such as these? Should PtDAs
be used periodically in patients with chronic illness as a means
of reassessing goals of care and ongoing management? At
present, the majority of PtDAs focus on discrete decisions
rather than the multiple decisions that are made over time, and
this area is ripe for research and innovation.
Conclusion
The aim of this discussion was to provide a framework
for potential developers to consider in developing PtDAs.
Matlock and Spatz Tools for Shared Decision Making 5
However, this field is ripe for innovation, particularly in
the areas where decisions are more difficult. At present,
PtDAs are stymied in the research setting. Whether their
lack of adoption into routine clinical practice stems from
poor development, reluctance on the part of clinicians to
use them, prohibitive workflow, maligned incentives, or
inaccessibility at the time they are needed is not clear. Certainly 1 essential step toward a solution to this problem
is to invite all potential stakeholders (patients, clinicians,
clinical staff, administrators, etc) into all aspects of development. With increasing interest among healthcare leaders,
policymakers, and funders to bring PtDAs into the fold,
there may be more opportunities to study the development,
uptake, and impact of PtDAs. Such investigation is critical
to informing best practices for developing PtDAs and policies to support their use.
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Sources of Funding
Dr Matlock was supported by a career development award from the
National Institute on Aging (1K23AG040696).
Disclosures
None.
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Design and Testing of Tools for Shared Decision Making
Daniel D. Matlock and Erica S. Spatz
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