Posts (10)

Sep 6, 2019 · Purposeful SDM: Our new model of shared decision making

There are many situations in which patients and clinicians need to and are making decisions together, arguably these are all instances of Shared Decision Making (SDM). The ways that patients and clinicians make decisions should change according to the problem that is the reason why decisions are being made. For example, how patients and clinicians choose whether or not to take statins to potentially reduce 10-year risk of heart attack may be different from how management decisions are made for a patient living with multiple chronic conditions who is experiencing multiple detrimental life changes. In the first instance patient and clinician might use a weighing approach to weigh the pros and cons of known alternatives (to take or not statins), while in the second they might use a problem-solving approach to uncover possible solutions and judge how they would work in the patient’s life.

In a paper published in the current issue of Patient Education and Counseling, we present the Purposeful SDM model. Purposeful SDM distinguishes different kinds of situations where patients and clinicians need to work out what to do, and different SDM methods for addressing these problems. The model suggests that there is no one way to do SDM, rather we can think of SDM as a range of methods that vary according the problem that the patient is experiencing. I.e. SDM changes according to its purpose.

Kinds of situations that require patients/family and their clinicians to make decisions together and pertinent methods of SDM.

Purposeful SDM extends the
predominant focus in SDM research, practice, training, and promotion on the
need to involve patients in decision making. The model draws attention to the
problem that is the reason why patients and clinicians are involved in making
decisions in the first place and the appropriate method of addressing these
problems together. The Purposeful SDM model may help explain why many
clinicians don’t see current models of SDM as being relevant to the problems
that they are dealing with in their practice.

We believe that Purposeful
SDM has important implications for what SDM interventions, such as decision
aids, should be designed to do and what should be measured when evaluating SDM.
Current measures are mostly intended for situations where SDM is used to choose
between alternatives. This is only one of the situations and methods that
Purposeful SDM describes.

Purposeful SDM: A problem-based approach to caring for patients with shared decision making is available through open access until October 15, 2019.

Authors: Ian G. Hargraves, Victor M. Montori, Juan P. Brito, Marleen Kunneman, Kevin Shaw, Christina LaVecchia, Michael Wilson, Laura Walker, Bjorg Thorsteinsdottir

Download the Purposeful SDM poster presented at ISDM 2019.

Aug 30, 2019 · Reflecting on and making sense of shared decision making

Measuring shared decision making (SDM) is challenging. Previous research showed discrepancies between observer-based and self-reported scores. Patient-reported SDM scores are usually higher and tend to have ceiling effects (high scores without much variance), possibly due to halo effects (difficulty to disentangle SDM from overall experience of care).

We wanted to test whether introducing a pause (“stop-and-think”) before filling in SDM scores would slow patients down and encourage them to reflect above and beyond their assessment of general satisfaction with the clinician or the visit. Also, we wanted to assess how much intellectual, emotional, or practical sense the care plan made to patients.

In two studies, we asked a diverse group of patients to reflect on their care before completing the 3-item CollaboRATE SDM measure. In the first study, adding the reflection questions lowered the CollaboRATE score (“less” SDM) and reduced the proportion of patients giving the maximum scores. The differences, while tantalizing in magnitude and direction, were not significant. In the second study, the reflection questions did not change the distribution of CollaboRATE scores or top scores.

In general, patients indicated high scores on the sense of their care plan. However, this ‘sense’ was only weakly correlated with the total CollaboRATE scores. One of every two patients indicated their care plan made less than ideal sense, yet they still gave maximum scores on the CollaboRATE.

Our studies showed limited and somewhat inconsistent evidence that reflection-before-quantification interventions may improve the performance of patient-reported SDM measures. Also, we showed that it is conceivable that scoring high on the “technical steps of SDM” as assessed by SDM measures, may not necessarily lead to a decision that makes sense and vice versa.

The full paper was published in Health Expectations and can be found here.

This study was part of the Fostering Fit by Recognizing Opportunity STudy (FROST) program, and has been made possible by a Mapping the Landscape, Journeying Together grant from the Arnold P. Gold Foundation Research Institute.

Submitted by: Marleen Kunneman, Christina LaVecchia, Naykky Singh Ospina, Abd Moain Abu Dabrh, Emma Behnken, Patrick Wilson, Megan Branda, Ian Hargraves, Kathleen Yost, Richard Frankel, Victor M. Montori

Jul 2, 2019 · Decision aids that facilitate elements of shared decision making in chronic illnesses

Submitted by Thomas Wieringa

Shared decision making
(SDM) is a patient-centered approach in which clinicians and patients work
together to find and choose the best course of action for each patient’s
particular situation [1]. This approach is pertinent to the care of
patients with chronic conditions [2]. Six key elements of shared decision making
can be identified [1-4]:

  1. situation diagnosis (understanding the patient’s situation and establishing the aspects require action)
  2. choice awareness (indicating that multiple options are available and highlighting the
  3. importance of the patient’s preferences in deciding on the course of action)
  4. option clarification (explaining the available options)
  5. discussion of harms and benefits (explaining the harms and benefits of each option)
  6. deliberation of patient preferences (discussing the preferences of the patient)
  7. making the decision (clinician and patient making together the decision)

Decision aids
SDM can be facilitated
by decision aids that have been developed for use by clinicians and patients,
either during or in preparation of the clinical encounter [5-7]. Decision aids can help patients choose an option that is congruent
with their values, reduce the proportion of patients remaining undecided and/or
who play a passive role in the decision-making process, and improve patient
knowledge, decisional conflict, and patient-clinician communication [7-11].

The International
Patient Decision Aid Standards (IPDAS) Collaboration developed a minimal set of
standards for qualifying a tool as a decision aid, which require that a
decision aid support all key elements but making the decision [12].

Systematic review
We conducted a
systematic review to assess the extent to which decision aids
support the six key SDM elements and how this relates to their impact.

We found 24 articles reporting on 23 RCTs of 20 DAs
(10 DAs for cardiovascular disease, two DAs for respiratory diseases, and eight
DAs for diabetes). With the exception of one, all studies
have an unclear or high risk of bias for all outcomes assessed in this review. The option clarification element
(included in 20 of 20 DAs; 100%) and the harms and benefits discussion
(included in 18 of 20 DAs; 90%; unclear in two DAs) are the elements most
commonly clearly included in the DAs. The other elements are less common and more
uncertainty is present whether these elements are included, especially with
regard to choice awareness (uncertain in 14 out of 20 DAs; 70%). All elements
were clearly supported in four DAs (20%). We found no association between the presence of
these elements and SDM outcomes.

Thus, despite
the IPDAS minimal set of qualifying criteria, our systematic review showed that
decision aids for cardiovascular diseases, chronic respiratory diseases, and
diabetes mostly support the option clarification and the discussion of harms
and benefits elements of SDM, while the other SDM elements are less often

Future research
Possibly, some SDM
elements may be left out of decision aids by design. This choice may depend on
what features were thought most important by the developers (e.g., patient
education, risk communication, preference elicitation, or patient empowerment).
The importance of incorporation of SDM elements in decision aids may be
situation-dependent, but the way this works is unclear. Therefore, future
research should clarify this situation-dependence and eventually inform
possible reconsideration of the IPDAS minimum standards for decision aid
qualification. The relationship between the extent to which decision aids
support SDM elements and outcomes is yet unknown and should be studied in
future research as well.

The full paper was
published in Systematic Reviews and can be found here:

Thomas Wieringa is
a post-doc researcher at the department of Epidemiology at the University
Medical Center Groningen (UMCG), the Netherlands. He did his PhD, focused on
shared decision making and patient-reported outcomes in type 2 diabetes, at the
VU University Medical Center. He visited and collaborated with the Knowledge
and Evaluation Research (KER) Unit of the Mayo Clinic in the context of his


  1. Hargraves I, LeBlanc A, Shah ND, Montori VM. Shared decision making: The need for patient-clinician conversation, not just information. Health Affairs. 2016;35(4):627-9.
  2. Montori VM, Gafni A, Charles C. A shared treatment decision-making approach between patients with chronic conditions and their clinicians: The case of diabetes. Health Expectations. 2006;9(1):25-36.
  3. Kunneman M, Engelhardt EG, Ten Hove FL, Marijnen CA, Portielje JE, Smets EM, et al. Deciding about (neo-) adjuvant rectal and breast cancer treatment: Missed opportunities for shared decision making. Acta Oncologica. 2016;55(2):134-9.
  4. Stiggelbout AM, Pieterse AH, De Haes JCJM. Shared decision making: Concepts, evidence, and practice. Patient Education and Counseling. 2015;98(10):1172-9.
  5. IPDAS Collaboration. What are patient decision aids? (2017). Accessed 30 Oct 2018.
  6. Montori VM, Kunneman M, Brito JP. Shared decision making and improving health care: The answer is not in. JAMA: Journal of the American Medical Association. 2017;318(7):617-8.
  7. Stacey D, Légaré F, Lewis K, Barry MJ, Bennett CL, Eden KB, et al. Decision aids for people facing health treatment or screening decisions. Cochrane Database of Systematic Reviews. 2017;(4):CD001431.
  8. Durand MA, Carpenter L, Dolan H, Bravo P, Mann M, Bunn F, et al. Do interventions designed to support shared decision-making reduce health inequalities? A systematic review and meta-analysis. PloS One. 2014;9(4):e94670.
  9. Légaré F, Turcotte S, Stacey D, Ratté S, Kryworuchko J, Graham ID. Patients’ perceptions of sharing in decisions. The Patient – Patient-Centered Outcomes Research. 2012;5(1):1-19.
  10. Dwamena F, Holmes-Rovner M, Gaulden CM, Jorgenson S, Sadigh G, Sikorskii A, et al. Interventions for providers to promote a patient-centred approach in clinical consultations. The Cochrane Library. 2012;(12):CD003267.
  11. Joosten EA, DeFuentes-Merillas L, De Weert GH, Sensky T, Van Der Staak CPF, de Jong CA. Systematic review of the effects of shared decision-making on patient satisfaction, treatment adherence and health status. Psychotherapy and Psychosomatics. 2008;77(4):219-26.
  12. 12.           Joseph-Williams N, Newcombe R, Politi M, Durand M-A, Sivell S, Stacey D, et al. Toward minimum standards for certifying patient decision aids: A modified Delphi consensus process. Medical Decision Making. 2014;34(6):699-710.

Jun 10, 2019 · Shared Decision Making with patients who have Limited English Proficiency

Submitted by Amelia Barwise

importance of shared decision making (SDM) is widely recognized and its
practice is encouraged. However, some people face major challenges as they are
invited to participate in SDM, and may not recognize or understand the concept of
SDM within healthcare. There is a limited amount of literature about SDM in patients
who have limited English proficiency (LEP) – defined as “not speaking English as a primary
language and potentially having a limited ability to read, speak, write, or
understand English.” We do know, however, that older age, poor health literacy,
and language barriers are obstacles
to using SDM. LEP often occurs together with low health literacy and cultural
obstacles; this triad is aptly referred to as the “triple threat.”

The basic tenets of SDM – sharing of information and
preferences, consensus building and reaching agreement – may be foreign to
many. Here, we examine the steps involved in SDM, and clarify the potential
issues that may arise in the context of people with LEP.

Process of information sharing

Those with LEP may have a different worldview with cultural
norms that diverge substantially from Western norms. Some people with LEP believe,
either for faith-based or cultural reasons, in non-disclosure and deliberately
hide a poor diagnosis, poor prognosis, and alternative treatment options from
their loved ones who are patients. This is not done with ill-intent but to protect their loved
ones from experiencing potential hopelessness and depression from learning of
impending death or a non-curative condition. LEP patients may also be more
to use alternative therapies and be reluctant to share this
information as they sense that clinicians may not approve. Those with LEP are
more likely to experience bias or perceive they have experienced
discrimination, and therefore have less trust in their clinicians
inhibiting information sharing. Clinicians in turn may
share less information
with those who have LEP due to a variety of factors including lack
of time, interpreter availability, and concerns about comprehension.

Deliberation and Decision making

The importance of family in decision making among those with
LEP is also key, with large groups of relatives often involved in decisions
that for most US families would involve a patient acting alone or with a surrogate
or with very close family members only. The collectivist approach to making
decisions is at risk of impeding deliberation and shared decision making as the
needs, preferences, and understanding of what is best for the patient as voiced
by the patient may get crowded out by the many voices wanting to be heard.

Decision making models

The US promotes patient autonomy (with designated surrogates
as needed) as vital in all decision making and a driver of shared decision
making, while other cultures support a paternalistic model with the clinicians
considered expert and driving the decision making process.

Decision aids developed for specific populations may help
bridge the gap between inadequate communication and improved decision making.
Decision aids adapted from English to other languages require more than
translation to ensure their usability and effectiveness; an enormous challenge.
Interpreters will need to be involved in the process of developing and
implementing tools as they will be central to their uptake and effectiveness in
practice. There remain huge challenges to supporting and measuring SDM even
with isolated language barriers unrelated to other health literacy and cultural

The purpose of this commentary is not to stereotype groups
into those “capable” of SDM and those that are not. The purpose of this commentary
is to draw attention to a wider range of cultural approaches to decision making
in healthcare. The healthcare team should assess each patient’s interest in
being part of a SDM process. For some with LEP, SDM will appeal and help them
make informed and meaningful decisions about their healthcare. For others it
will be a baffling and potentially distressing encounter. We must not coerce
patients into “complying” with Western decision-making approaches when seeking care.
In respecting patients, we need to consider flexible and culturally adept decision-making
processes that acknowledge the fundamental role family and other factors play in
clinical decision making.

Clinicians should be mindful of the other more pressing barriers
to decision making that exist for those with LEP and accept other potentially
unfamiliar approaches to providing compassionate and culturally sensitive care.
It may help to exercise some cultural humility, accepting decisions that clash
with usual expectations and being skeptical of SDM as the preferred way to
reach decisions with patients. For some with LEP there are limits to the
practical use of SDM and requiring them to conform to SDM is unrealistic and
may be counter-productive and uncaring.

Amelia Barwise is an assistant Professor of Medicine within the Division of Pulmonary and Critical Care Medicine at Mayo Clinic. She is currently working on her PhD focused on end of life care among patients with limited English proficiency.

May 16, 2019 · Supporting Implementation of Shared Decision Making for Statin Therapy Initiation in Primary Care

Submitted by Aaron Leppin

Decisions on whether to initiate statin therapy for
cardiovascular risk reduction should be based on individual patient risk and
occur in the context of a shared decision making (SDM) conversation. The Statin
Choice Conversation Aid is a web-based tool that incorporates patient variables
to calculate and present an individual-level risk. It has been shown in
multiple randomized trials to facilitate SDM when used in the clinical

Despite being freely available and well accepted by patients
and clinicians, the Statin Choice tool had not been institutionally adopted and
integrated into the clinical work flow at any site prior to 2014. This lack of
implementation was and is representative of many SDM interventions which, in
routine settings, are often not prioritized. The reasons for this are complex
but, at least at some level, result from the competing priorities healthcare
systems must address and the often-fixed resources they have to do this work.
In this context, it stands to reason that health systems and other settings
will be more likely to undertake the work of implementing SDM when it is
understood clearly to be low.  Unfortunately,
in most cases, the work of implementing any individual SDM intervention is
poorly understood at the outset. The most effective and efficient strategies
for facilitating implementation are often even more ambiguous.

In this study, we sought to address these foundational
problems by both characterizing the work of implementing the Statin Choice tool
and identifying the most useful strategies for doing this work. Specifically,
we recruited 3 health systems in the Mayo Clinic Care Network and carefully
observed and tracked their efforts to integrate the tool into their EHR and
into routine use across all of primary care over an 18-month period.

We used Normalization Process Theory, an implementation
theory that organizes the types of work required to embed new practices, to
describe the implementation process at each site. We collected multiple types
of data from many sources to track the success (or outcomes) of implementation
as well. By carefully examining the things teams did (e.g. the strategies they
used) to do the work of implementation and the results of this effort (e.g. the
outcomes the work achieved), we were able to identify the most useful
strategies for making SDM implementation happen. We were also able to gain a
clear understanding of the types and amount of work that would be required.

With this knowledge, we were able to develop a
multi-component toolkit that could be provided to other settings to support
implementation of the tool. As part of this toolkit, we were also able to
provide a brief organizational readiness and context assessment. More clearly,
because we had observed the implementation process, we were able to provide an
assessment that would guide clinical stakeholders in thinking about the
specific things they would need to be able to do (e.g. integrate into the
record, train clinicians), the ways in which these things can be done (e.g.
workflow examples, training methods), and whether the provided toolkit
resources (e.g. EHR code language, implementation team manuals, educational
templates) was sufficient support to justify going forward.

Importantly, our study identified several strategies that
were judged to be of low value in facilitating implementation. This knowledge
was critical to the development of the toolkit and to stakeholders as it
allowed us to avoid inclusion of things that will only cause more work for
clinical teams with little to no benefit.

The conceptual advancements of our research to the field of
implementation science include (1) a theoretical connection between the work
that stakeholders do to implement SDM and the outcomes this achieves and (2) an
appreciation of the need to develop useful toolkits that can support clinical
settings in understanding and doing the work of implementation.

It is not our impression, however, that the toolkit we
developed will be necessarily appropriate for other SDM interventions. Rather,
we believe our research should be used as a template that can be replicated by
other teams in other settings and for other interventions.

The full paper was published in BMC Health Services Research and can be found here. This study was made possible by a CTSA Grant (UL1 TR000135) from the National Center for Advancing Translational Sciences (NCATS), a component of the National Institutes of Health (NIH).

Apr 29, 2019 · Patient explicit consideration of tradeoffs: a Values Clarification Method

Submitted by
Arwen H. Pieterse

In oncology, as in other healthcare settings, shared decision making (SDM) is increasingly advocated when more than one treatment strategy is available. However, we previously found that cancer patient treatment preferences are often left undiscussed, and that patients are hardly involved in treatment decision making.  If patients are unclear about their preferences, or if these preferences are left unspoken, patients may not receive the treatment that fits them best.

Values clarification methods (VCMs) have been developed to support patients in weighing treatment benefits and harms and harms and to help them voice what matters most to them . We developed a stand-alone VCM that asks patients to make explicit trade-offs between treatment benefits and harms. This VCM is adaptive, in that it ensures that the trade-offs presented to patients are tailored to the preferences of the patient as revealed in the exercise so far.

We tested this VCM in patients newly-diagnosed with rectal cancer who were
facing the decision whether or not to undergo short-course pre-operative
radiotherapy. Radiotherapy increases the likelihood that the cancer will stay away at the
initial site (i.e., local control), however, it also increases the likelihood of fecal incontinence and of sexual
dysfunction. We hypothesized that the
VCM would aid patients to become more confident on their preferences and to
voice them more often during consultations, based on results among treated
rectal cancer patients asked to consider the decision hypothetically. We
expected that going through the VCM would lead to patients’ preferences to be
more often integrated in treatment decisions, and that patients would
experience less regret over the decision and would cope better with treatment

Values clarification method

The online VCM was offered in
advance of the first encounter of the patient with the radiation oncologist, a
visit in which the treatment decision is usually made. The VCM started with lay
explanations of the three outcomes (local control, fecal incontinence, and male
or female sexual dysfunction), and stated that survival was the same across
situations. It then asked patients to rate how important they considered
differences between best and worst probabilities of outcomes, that varied
within a clinically realistic range (see print
). Next, the VCM asked patients to indicate their preference for pairs of
outcomes, where outcome probabilities differed in each pair. The final page of
the VCM showed the patient’s relative importance for the three outcomes in percentages.
It did not show which treatment should suit the patient best, as it was meant
to support patients in considering the options and they still were to meet with
their radiation oncologist.

were initially randomized to be offered the VCM or not. Later on in the study,
we offered the VCM to all patients due to practical difficulties and low
recruitment rates. We compared the outcomes in patients who agreed to receive
the link to the VCM versus those who did not receive the link.


Of the 135 patients who had their consultation
audiotaped and completed questionnaires, 35 received and accessed the VCM-link.
Patients in the VCM-group slightly more often expressed their views on treatment
and treatment outcomes than the patients who had not, although such utterances
were still uncommon. This points to very limited discussion between patients
and clinicians on how patients consider benefit-harm trade-offs. This may
further explain why the questionnaire data showed that patients in the VCM-group did not differ in how clear their values were.

An important finding is that
patients who completed the VCM felt less regret over the treatment decision at
follow-up, and experienced less impact of faecal incontinence and sexual
dysfunction six months after treatment. As hypothesized, explicitly considering
trade-offs may have helped patients to better understand the pros and cons
involved, and supported them to live with the consequences later on. Of note,
the radiation oncologists in this study reported that almost all decisions
had been made before the
consultation, either by the referring physician or by the tumour board, without
input from the patient. Patients clearly
lacked room to contribute.


This is the first study to assess the effect of an
adaptive conjoint analysis-based VCM on actual patient-clinician communication,
and long-term decision regret and impact of treatment harms. Decisions to
undergo short-course preoperative radiotherapy in rectal cancer had in almost
all cases been made prior to the consultation, without patient input. The VCM
hardly could affect final decisions in this setting. Even so, our results
suggest a favourable effect of being explicitly invited to think about benefits
and harms of treatment on the extent to which patients endorse treatment
decisions and can live with treatment consequences.

The full paper was
published in Acta Oncologica and can
be found here (open access).

This study was made
possible by a grant from the Dutch Cancer Society (UL2009-4431).

Arwen H. Pieterse is associate professor in medical decision making at the Leiden University Medical Center, the Netherlands. She studied Cognitive Psychology and graduated (cum laude) in 1998. She obtained her PhD in 2005. She was Research fellow of the Dutch Cancer Society (2008-2011). She published well over 50 international peer-reviewed articles on patient-physician communication, patient and physician treatment preferences, patient-physician (shared) decision making, and psychometric properties of measurement instruments. Based on her research, she co-developed e-learnings to teach shared decision making skills to medical students and clinicians. She received the 2018 Jozien Bensing award from the International Association on Communication in Healthcare (EACH), granted biennially to early-career researchers.

She is
Associate editor of Patient Education and Counseling since 2017. She was the
scientific co-chair of the 2018 European meeting of the Society of Medical
Decision Making. She chairs the EACH standing committee on research since 2018
and is the co-chair of the upcoming EACH Forum, September 16-18 2019, Leiden, the Netherlands.

Mar 22, 2019 · Technical versus Humanistic Shared Decision Making revisited: Evaluating its occurrence

Submitted by Marleen Kunneman & Victor Montori

In an earlier post, we reflected on technically correct and humanistic shared decision making (SDM). In our view, it is unclear “whether having a technically correct structure of the SDM process improves the likelihood that the care decisions made will contribute to improve the patient situation.” We called to look beyond what is technically correct, to uncover humanistic SDM and caring conversations.

We recently published a systematic literature review in which we assessed the extent to which evaluations of SDM assess the extent and quality of humanistic communication, such as respect, compassion, and empathy. We looked for studies evaluating SDM in actual clinical decisions using validated SDM measures. We found 154 studies, of which only 14 (9%) made at least one statement on humanistic communication. This happened in framing the study (N=2), measuring impact (e.g., empathy, respect, interpersonal skills; N=9), as patients’ or clinicians’ accounts of SDM (N=2), in interpreting the study results (N=3), and in discussing implications of the study findings (N=3).

In addition, we looked whether the validated SDM measures used contained items on humanistic communication. The eleven SDM measures used contained a total of 192 items. Of these, only 7 (3.6%) assessed aspects of humanistic communication.

Our review shows that assessments of the quality of SDM focus narrowly on SDM technique and rarely assess humanistic aspects of the patient-clinician conversation. We conclude that considering SDM as merely a technique may reduce SDM’s patient-centeredness and undermine its contribution to patient care.

In evaluating technical SDM, we have measured with our eyes and our ears. Perhaps the fox from “The Little Prince” was on the right track when he noted: “It is only with the heart that one can see rightly; what is essential is invisible to the eye.”

The full paper was published in Patient Education and Counseling and can be found here.

This study was part of the Fostering Fit by Recognizing Opportunity STudy (FROST) program, and has been made possible by a Mapping the Landscape, Journeying Together grant from the Arnold P. Gold Foundation Research Institute.


Mar 19, 2019 · Trust and shared decision making

By Victor Montori

At the beginning of our research journey into shared decision making (SDM), we thought that fostering collaboration between patients and clinicians would promote their partnership and advance mutual trust. Yet, in this trial reported in 2008, we only measured patient trust in the clinician, and we found that disclosing uncertainty (as the intervention required) did not reduce trust in the clinician and may have even improved it despite the measure’s ceiling effect. To my knowledge, we have not measured this outcome in our trials of SDM intervention since then.

Four years earlier, when that trial was being planned, Entwistle reflected on studies that strongly suggested that trust, as a bridge between protective barriers, could favor shared decision making, and shared decision making could result in greater trust in treatment plans. This view was supported by clinicians interviewed by Charles and colleagues. That patients who trust their clinician may be comfortable taking a passive role in following treatment plans their clinician recommends, was substantiated in a report of a survey of Canadian patients that year.

Four years after our publications, in 2012, Peak and colleagues noted a bidirectional relationship between trust and SDM. In focus groups comprised of African American persons living with diabetes, participants reported how clinician efforts to engage them in shared decision making may promote trust, how their own trust in the physician may facilitate their participation in SDM, and how race (including aspects of implicit bias and cultural discordance) can affect both.

And this month, Academic Medicine publishes an important essay by Wheelock, a second year internal medicine resident in Boston, in which she poignantly asks how might we develop relationships of trust needed for shared decision making as industrial healthcare destroys any vestige of continuity of care.

As we review the videos that are produced in the course of the conduct of our clinical trials of SDM interventions, I have noticed another angle in the relationship between trust and SDM, which, as far as I know, remains largely unexplored. We have caught clinicians, using SDM tools in a manner that reveals they simply do not trust their patients to wisely consider the issues and contribute to form care that fits their life situation. Instead, they seem to use the tools as a speaker would use PowerPoint, to build the case for a particular action, to argue in an uninterrupted monologue that concludes in a strong recommendation. It is clear that these clinicians have met these diseases before, but not the people who have them. Nonetheless, the encounter will finish, and the clinicians will know little about these people or their situation, satisfied that they got consent to proceed as they thought would be appropriate, perhaps even before entering the consultation.  It is as if their professional commitment to the welfare of their patients prevents them from running the risk of trusting the patient into the decision making process. They appear afraid that these patients may enter a conversation that may finish at an impasse, at a disagreement, or at a substandard plan. The issues discussed in the last two decades that applied mostly to patient trust in the clinician, may need to be explored in the opposite direction, with an eye on the harmful effect of industrial healthcare.

SDM researchers may therefore do well in considering clinician trust in the patient as a potential modifier – barrier or facilitator – of the collaborative work necessary to form programs of care that make sense and advance the situation of patients.

Contact Us · Privacy Policy