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.
Recently, a systematic review that my colleagues and I started working on two years ago, was published in PlosONE (link to paper). Here, we will provide a summary of the methods and results and share our conclusions and recommendations. The aim of this review was to rate the psychometric quality of existing instruments measuring the process of shared decision making (SDM). Publishing this work is a great milestone for me for several reasons. Doing a systematic literature review is a time-consuming and intense process, and for months you crave for the moment that the work will finally be published and shown to the world. Also, this is my first scientific article in the field of SDM, combining my experience with performing psychometric validation studies with my current research focus, and research passion, SDM.
The main aim of this systematic review, as stated in the background, was to help researchers identify the best instrument to measure SDM in their studies. As there are so many SDM instruments available, reviewing the separate instruments provided us with the opportunity to aggregate results and identify overall strengths and limitations of the instruments and the methods applied in their development and evaluation studies. This, I think, is even of greater value to the SDM field than merely providing insight into the quality of the separate instruments. By presenting overall results on the methodological quality and the psychometric quality of SDM instruments, we aimed to point out the challenges that our field faces in the development and evaluation of the measurement instruments we use in our research and practice evaluation. I hope that our work will trigger reflection on the methods commonly applied and their limitations, and that it helps in starting and continuing discussions on future directions to help improve the quality of studies validating SDM instruments, as well as those using them.
I look forward to hearing your thoughts and views on our findings and ways forward. My co-authors and I will join a few conferences this year (e.g. SMDM-Europe 2018 in Leiden, the Netherlands and ICCH 2018 in Porto, Portugal), so for a discussion in person, please come and meet us there!
Background
As the readers of this Blog may be aware of, research on shared decision making is extensively growing. Most studies on the extent of shared decision making (SDM) seen in clinical care, on the effects of SDM training and tools for healthcare providers and patients, and on the effect of SDM on psychosocial and physical patient outcomes make use of standardized measurement instruments to assess the actual realization of SDM. The validity of their results highly depends on the psychometric quality of the instruments used. Existing instruments to measure SDM include questionnaires for patients or providers, and observer-based coding schemes to be applied to audio- or videotaped consultations. We performed a systematic literature review of instruments assessing the SDM process, in order to help researchers choose the best instrument in terms of psychometric quality.
Methods
We systematically searched seven databases. Two researchers independently evaluated all retrieved records for eligibility, using pre-defined inclusion criteria (i.e., peer-reviewed articles that describe the development or evaluation of an SDM-process instrument). For each instrument we identified in the included articles, we rated the psychometric quality for ten separate measurement properties: separately for ten measurement properties: Internal consistency, reliability (test-retest reliability for questionnaires and intra-rater and inter-rater reliability for coding schemes), measurement error, content validity, structural validity, hypotheses testing, cross-cultural validity, criterion validity, responsiveness, and Interpretability.
For this quality rating we performed two quality appraisals: we appraised 1) the quality of the methods applied in the development and/or validation study, using the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN, see www.cosmin.nl), [1-2] and 2) the psychometric quality of the measurement property per instrument, based on the results of the development and/or validation studies.[4] For each instrument, we synthesized the results of the two appraisals into a best level of evidence per measurement property. The levels of evidence were: ‘unknown’ (due to poor methods), ‘conflicting’, ‘limited’, ‘moderate’, and ‘strong’. These were scored as either positive or negative results for a measurement property evaluation. [5].
Findings
Our search resulted in 51 included articles, describing 23 different instruments measuring the SDM-process. Including all revisions and translations of these instruments, we found in total 40 different instrument versions. Most instruments were observer-based coding schemes (N=18), followed by patient (N=16) and provider questionnaires (N=4); two instruments were dyadic, i.e., they included multiple perspectives in the assessment of SDM.
Overall trends in the quality of SDM instruments and the methods applied in their validation studies
Generally, evidence is lacking regarding the measurement quality of existing SDM instruments, partly because not all measurement properties have been evaluated, and partly because the methodology applied in the evaluation studies was of poor quality.
Overall, six measurement properties have been evaluated for less than 20% of the instruments, accounting for their applicability: Test-retest reliability of questionnaires (17%), measurement error (0%), content validity (14%), cross-cultural validity (13%), responsiveness (2%), and interpretability (0%). The best-evidence synthesis indicated positive results for half of the instruments for content validity (50%) and structural validity (53%), if these had been evaluated. In contrast, negative results for about half of the instruments were found for inter-rater reliability (47%; coding schemes only) and hypotheses testing for construct validity (59%), in case these had been evaluated. Differences in the quality between instrument types were found for internal consistency and structural validity: results for questionnaires were overall more positive than for coding schemes, and for coding schemes more often unknown than for questionnaires, due to lack of validation of these measurement properties, or because of poor methodological quality of the studies.
Concerning the often poor results of hypothesis testing for construct validity evaluation, it is of note, hypotheses about relationships with instruments that were designed to measure the same construct (i.e., the SDM process), either measured from the same or from a different perspective, were often not confirmed, or did not reach the threshold we handled for positive results for correlation coefficients of ≥0.50. The weak correlations point both to a lack of consensus on how to define the process of SDM and to the question whether SDM viewed from the perspective of the patient, provider, or observer can be regarded as the same construct?
This fits the finding that developers often only provided a vague definition of the construct to be measured, or none at all. Also, only two developers explicitly mentioned which underlying measurement model they assumed: a formative model, in both instances. The choice for the measurement model–reflective, in which the latent construct determines the items (effect indicators) versus formative, in which the latent construct is a result of independent items (causal indicators)–has implications for the development and validation criteria of instruments [6]. Neglecting the differences may result in applying an inappropriate methodology. In 2011, Wollschläger called upon the SDM field to reach consensus on the most suitable underlying measurement model [7], a call that has not yet been clearly responded to.
Conclusions and recommendations
A large number of instruments are available to assess the SDM process, but, evidence is still lacking regarding their measurement quality, partly because measurement properties have not been evaluated at all, and partly because the validation studies have been of poor quality. Clearly, this does not imply that existing instruments are of poor quality, but rather, that their quality is often unknown. In practice, the choice for the most appropriate instrument for your research can therefore best be based on the content of the instrument and other characteristics of the instruments that suit best the aim of the study and the resources available for the study, such as the perspective that is assessed and the number of items. For quality improvement of existing SDM instruments, and improvement of the validation studies in the SDM field, we recommend the following:
Key recommendations:– Reach consensus on the most suitable underlying model for the construct of the SDM process.- Provide a clear definition of the construct the instrument aims to measure–in this case the SDM process.- Perform content validity analyses prior to further validation of new instruments.- Include large-enough sample sizes in validation studies; improvement of sample sizes is especially needed for inter- and intra-rater reliability testing of coding schemes.- Seek alternative ways to evaluate test-retest reliability of questionnaires for the process of SDM.- Find ways to improve inter-rater reliability of coding schemes; e.g., by providing more detailed descriptions of coding scheme items.- When formulating hypotheses to evaluate construct validity, include instruments with constructs that are as similar as possible to the construct of the instrument under investigation and, alternatively, make use of known-group differences testing.- Determine minimal important change values to inform the interpretation of change scores in intervention studies.- Above all, we recommend to further evaluate and refine existing instruments and to adhere as best as possible to the COSMIN guidelines (www.cosmin.nl) to help guarantee high-quality evaluations of psychometric properties.
For a more detailed description of the methods and results of our systematic review and for a more nuanced discussion of our findings, please take a look at our full paper in PlosOne.
For any questions about this work feel free to contact Fania Gärtner: f.r.gartner@lumc.nl
Submitted by
Fania R. Gärtner1, Hanna Bomhof-Roordink1, Ian P. Smith1, Isabelle Scholl2,3, Anne M. Stiggelbout1, Arwen H. Pieterse1
Author affiliations
1 Medical Decision Making, Department of Biomedical Data Sciences, Leiden University Medical Centre, Leiden, the Netherlands
2 Department of Medical Psychology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
3 The Dartmouth Institute for Health Policy and Clinical Practice, Lebanon, NH, Unites States
Dr. Fania Gärtner holds a Master’s degree in Social Psychology and a PhD in occupational medicine. In her work, she combines her expertise in the development and evaluation of measurement instruments, and doctor-patient communication and SDM. She has a special focus on learning needs and barriers of oncologists for applying SDM in daily practice. Next to her work as a researcher, Fania has extensive experience in training medical students and specialists in communication and SDM skills, which brings her in contact with diverse attitudes and levels of competencies, and feeds her eagerness for the research in this field.
References
Mokkink LB, Terwee CB, Patrick DL, Alonso J, Stratford PW, Knol DL, et al. The COSMIN checklist for assessing the methodological quality of studies on measurement properties of health status measurement instruments: an international Delphi study. Qual Life Res. 2010;19(4):539-49.
Mokkink LB, Terwee CB, Patrick DL, Alonso J, Stratford PW, Knol DL, et al. The COSMIN study reached international consensus on taxonomy, terminology, and definitions of measurement properties for health-related patient-reported outcomes. Journal of clinical epidemiology. 2010;63(7):737-45.
Terwee CB, Mokkink LB, Knol DL, Ostelo RW, Bouter LM, de Vet HC. Rating the methodological quality in systematic reviews of studies on measurement properties: a scoring system for the COSMIN checklist. Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation. 2012;21(4):651-7.
Terwee CB, Bot SD, de Boer MR, van der Windt DA, Knol DL, Dekker J, et al. Quality criteria were proposed for measurement properties of health status questionnaires. J Clin Epidemiol. 2007;60(1):34-42.
Terwee CB, Prinsen CA, Ricci Garotti MG, Suman A, de Vet HC, Mokkink LB. The quality of systematic reviews of health-related outcome measurement instruments. Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation. 2016;25(4):767-79.
Jarvis CB, Mackenzie SB, Podsakoff PM. A Critical Review of Construct Indicators and Measurement Model Misspecification in Marketing and Consumer Research. Journal of Consumer Research. 2003;30:199-218
Wollschlager D. Short communication: Where is SDM at home? putting theoretical constraints on the way shared decision making is measured. Zeitschrift fur Evidenz, Fortbildung und Qualitat im Gesundheitswesen. 2012;106(4):272-4.
Every year, about 10 million people worldwide develop dementia – one person in every three seconds.1 Dementia is a progressive brain-disease for which no curative treatment is available. Patients with dementia endure cognitive decline and will eventually not be able to take care of themselves anymore. In the early stages of dementia, patients may still be able to participate in shared decision-making (SDM),2 but as the disease progresses, this may become increasingly challenging. To ensure that we provide patients with the best personalized healthcare also in these final phases of life, we need to know what is most important to them. A patient representative like a close family member or a caregiver can in such cases be asked to participate in the SDM process to design a care plan that fits the patient as best as possible.
As part of my medical training, I participated in a minor ‘Patient Centred Care’3 of the Leiden University Medical Center, (the Netherlands), focussing on self-management and SDM. For this 10-week course, I delved into the topic of SDM with patients with dementia. Here, I report on the interviews I had with two patient representatives, Richard* (63 years old, works as a nurse in a nursing home for people with dementia) and Helena* (48 years old). I wanted to explore the role of the doctor, the patient, the patient’s caregivers, and Advanced Care Plans (ACP’s) in SDM about decisions at the end of life for patients with dementia who are unable to participate in such conversations. An ACP is a document made by the patient and his family, possibly also together with his clinicians, in the early stages of dementia. It contains directions for clinicians and caregivers about a patient’s preferences regarding future healthcare when the person is no longer able to express his or her own preferences anymore. Of note, the clinical value of ACP’s is still questionable for practical and ethical reasons, such as how long it is valid and how to interpret a patient’s preferences when described situations lack details.
In Richard’s views, doctors should always take the patient’s values and preferences into account when deciding about care, even though this is challenging in advanced dementia. However, even in developed stages of dementia, patients can often express preferences in some way. Richard also stated that the family and caregivers have an important role as well: their involvement is crucial in ensuring that the opinion and preferences of the patient drive making decisions about care. They know the patient better than the doctor, and therefore they should advocate for what they think would be in the patient’s best interest. Although we must always aim to care for the patient in ways compatible to the patient’s ACP, Richard believes doctors are entitled to overrule the ACP if they believe it is better for the patient.
Helena, on the contrary, would prefer the clinician to take the lead in making decisions about care for patients with advanced dementia, not necessarily engaging family members and caregivers in a SDM process. Although they could act on behalf of the patient, the clinician should always follow the ACP. In other words, the ACP is superior to everyone’s opinion, even to the doctor’s opinion. The ACP has to be carried out at all times, since it is the most direct source of the patient’s opinion, according to Helena.
The patient representatives I talked to agreed that SDM in the setting of advanced dementia is complex and requires more effort from the doctor. More than in most other care settings, clear communication with the patient’s family members and caregivers, and considering with them what would be in the patient’s best interest, requires effort. As the relation with the patient may become increasingly difficult to maintain, developing a relation with the family members and caregivers becomes ever more important for clinicians in caring for the patient.
During the half minor, I realized that patient representatives may differ in their views on the value and implementation of SDM in advanced dementia. Just as for frail older patients without dementia,4 we need to find ways to ensure that all patients receive care that fits them as best as possible, even when they are unable to voice their preferences and participate in a SDM process. As patients with dementia might forget who they truly are, we must not forget them.
* To protect their privacy, I altered the names.
Submitted by: Hannah Leegwater, medical student at Leiden University Medical Center, the Netherlands.
I would like to acknowledge Marleen Kunneman, PhD and Arwen Pieterse, PhD for reviewing and editing this blog post.
References
Prince MJ, Wimo A, Guerchet MM, Ali GC, Wu Y-T, Prina M. World Alzheimer report 2015 – the global impact of dementia: an analysis of prevalence, incidence, cost and trends. London: Alzheimer’s Disease International, 2015. 84 p.
Van der Flier WM, Kunneman M, Bouwman FH, Petersen RC, Smets EMA. Diagnostic dilemmas in Alzheimer’s disease: room for shared decision making. Alzheimers Dement (N Y). 2017 May 9;3(3):301-304. DOI: 10.1016/j/trci.2017.08.008. eCollection 2017 Sep.
Van de Pol MH, Fluit CR, Lagro J, Slaats YH, Olde Rikkert MG, Lagro-JanssenAL. Expert and patiënt consesnus on a dynamic model for shared decision-making in frail older patients. Patient Educ Couns. 2016 Jun;99(6):1069-1077. DOI: 10.1016/j.pec.2015.12.014. Epub 2015 Dec 28.
As pharmacists are now embedded in many healthcare teams with responsibilities for medication therapy management, teaching shared decision-making skills is essential in our pharmacy curriculum. In the 2nd year of a 4-year longitudinal evidence-based medicine (EBM) doctor of pharmacy school curriculum, student pharmacists are taught how to communicate evidence to patients and health care team members, and how to use a shared decision-making process with patients, using tools from the Mayo Clinic Shared Decision Making National Resource Center. The following is a reflection of their experience, as future pharmacists, with the shared decision-making activity:
In a society where patients have a plethora of information at their fingertips, curiosity and involvement in self-care have become increasingly popular. However, with readily available information, particularly on the internet, both credible and deceptive, it is crucial that patients and health care providers work together in developing effective therapeutic plans. There are certain clinical scenarios that merit the implementation of swift, solitary decision-making by healthcare professionals. However, more often, there are cases where there is no definitive correct answer – situations in which priorities and values should be taken into consideration. We believe that the shared decision-making model is an optimal system, by which patients and health care providers can work together to formulate a clear picture of an effective action plan.
As doctor of pharmacy candidates at Western University of Health Sciences, we have had the valuable opportunity of engaging in progressive, interactive workshops that mimic the shared-decision making model. During one of these workshops, we were divided into teams and given hypothetical cases, modeling clinical scenarios. The goal of this workshop was for us to role-play as patients and pharmacists in a clinical setting to practice the shared decision making model and to learn how to effectively communicate with patients to discuss their risk, health history, and preferences to unite on healthcare decisions that are mutually agreed upon. This exercise was effective in shedding light onto the experience of a patient, as well as a practicing pharmacist in shared-decision making.
For each of the two example cases, we were supplied with shared decision-making tools to assist us in formulating a decision for our patients’ therapy options. For the first case regarding diabetes management, we were exposed to the Diabetes Medication Choice decision aid cards (https://shareddecisions.mayoclinic.org/decision-aid-information/decision-aids-for-chronic-disease/diabetes-medication-management/), each of which focused on one topic and all pertinent information that may affect patients’ decisions, such as cost, lifestyle modifications, fear of needles and insulin therapy, blood sugar levels, side effect concerns, among other topics. In essence, these cards help both the patient and healthcare provider discuss aspects that the patient valued in order to choose the most appropriate treatment option. For instance, the patient in this one case study did not have any cost limitations, was most interested in minimizing alterations to her daily routine and enhancing weight loss. We began looking at her options based on these topics, and moved our way to other topics based on her priority scale. We simultaneously integrated clinical expertise and scientific evidence into the equation in order to make the best possible decision.
Another tool we used was the online interactive tool for determining fracture risk, developed by the Mayo Clinic Shared Decision Making National Resource Center for our osteoporosis patient case. This was a great resource because it allowed us to engage with our patients, as healthcare providers, by asking questions about their history, potential risk factors for developing osteoporosis, and preferences in their lifestyle or therapy. After we gathered all pertinent information, we input our patient’s specific data into the website, which then generated a user-friendly 100-face Cate’s plot, a visual aid that displays the patient’s personalized fracture risk with and without treatment, so that the patient could better understand the level of improvement offered by the potential treatment plan. Additionally, other tabs included tips on lifestyle modifications and other therapy options for patients to consider. This tool provided patients with a visual aid to better understand their risk for developing osteoporosis and the benefit of initiating osteoporosis therapy. Tools like these give healthcare providers, and patients alike, an opportunity to communicate with each other interactively and highlight the importance of EBM, especially when it comes to making important healthcare decisions. This allowed us another chance to interact with the patient and provide them with an outline of key points to focus on during the SDM session.
In essence, the shared decision-making model is the application of EBM. With the adoption of EBM in clincal practice, we believe that the SDM model will become organically integrated into most (if not all) health care practices. Participating in the SDM simulation workshop was very valuable as it fostered a patient-pharmacist interaction that remained focused on the patient’s priorities and values, while still catering to the pharmacist’s goals of achieving therapeutic efficacy. This is important because, based on our experience, it seems that patients respond best to information that is organized in a fashion they can appreciate and understand, without being clouded by hazy, complex information. This experience also allowed us to hone our clinical skills by showing us how to frame our questions and topics while effectively communicating evidence-based information to patients. We believe that due to their increased involvement in reaching a decision about the treatment plan, patients will be more likely to adhere to the designated agenda – as a proactive contributor to their healthcare plan, they will be more aware of the risks and benefits of adherence, as well as the risks of non-adherence. In situations where there is no definitive therapeutic plan, the patient and pharmacist can work together to figure out whether a treatment is necessary, and if so, which treatment option is most suitable. Ultimately, the SDM model will help us address clinical siutations that require a collaborative effort from both health care provider and patient.
Submitted by:
Doctor of Pharmacy Candidates, Western University of Health Sciences: Ani Arsenyan, BSBA, Dara Nguyen, BS, Sona Sourenian, BS EBM Curriculum Coordinator/Faculty and Professor, College of Pharmacy: Cynthia Jackevicius, BScPhm, PharmD, MSc, BCPS-AQ Cardiology, FCSHP, FAHA, FCCP, FCCS
We were very thrilled to participate at the ISDM conference in Lyon. We were honored to had been invited to contribute in the Special ISDM ZEFQ Issue regarding the state of implementation of SDM in different countries. The development of SDM in our country is challenging, as Mariela Barani, our lead researcher, has discussed with other colleagues at the Sunday Workshop on national strategies for implementing SDM.
We are currently exploring the perceptions from our health professionals and patients regarding SDM in our setting. Our activities in this conference included the presentation of our latest research on trans-cultural adaptation of SDM measuring, a co-chairing of one of the oral sessions and three poster presentations about women’s perceptions on breast cancer screening, a validation of a search filter for studies on patient’s values and preferences, and health professionals and patients perceptions regarding participation in SDM in a low health literacy community. It was a great opportunity to learn from other experiences and become enlightened with a wide variety of research studies.
We highlight the need for short validated tools in non-English speaking languages to aid the evaluation and improvement of clinical practice. We think that this conference will help us improve our initiative to locally empower patient-centered care research and implementation.
We also reflected with Victor Montori about SDM and financial incentives. It is on vogue worldwide today the use of financial incentives to boost SDM activities. But in practice, our perception is that those incentives only stimulate the simply registration of the use of a decision aid but does not guarantee that a SDM conversation has taken place between the patient and his caregiver. Victor agreed with us and also added other arguments for not incentivizing with money SDM: 1) SDM is good practice and that is enough to justify its introduction in clinical practice; 2) When you start paying for something, money will not last forever and after some time you will be in need of changing the financial incentive to other indicator or stop paying for it. And caregivers that have been payed for doing SDM until that moment will ask for money to continue doing it; 3) Once you start incentivize a SDM indicator, it will go up because doctors know that you are measuring it and they are being evaluated trough that indicator. After some time, when doctors forget about it, it will decline. This is called Hawthorne effect, also referred to as the observer effect, and is a type of reactivity in which individuals modify an aspect of their behavior in response to their awareness of being observed.
So we came to the conclusion that to incentivize SDM, we have to work on changing culture and make SDM a part of clinical practice.
Dr. Margaret Schwarze, a surgeon from the University of Wisconsin, and her colleagues published a proof of concept study “A Framework to Improve Surgeon Communication in High-Stakes Surgical Decisions—Best Case/Worst Case.”1 (https://www.ncbi.nlm.nih.gov/pubmed/28146230) This article was recently the topic of discussion during our bi-weekly Shared Decision Making working group.
Schwarze and colleagues described that hospitalized elderly adults who have urgent surgical conditions may receive unwanted burdensome surgical care at the end of life. Routine discussions between surgeons and elderly patients may not result in a care plan that authentically honors the goals, values, and preferences of patients.
To improve these discussions, they developed a “Best Case/Worst Case” framework to discuss high stakes surgical decisions (https://www.youtube.com/watch?v=FnS3K44sbu0). Surgeons were instructed to draw two lines on a paper. One line represented the option of pursuing surgical treatment and the other line represented the option of choosing supportive care. At the top of each line (or option), the surgeon would write and write and describe the “best case scenario” (or outcome) of that option. At the bottom of each line, the surgeon would write and describe the “worst case scenario” of each option. Somewhere in the middle, the surgeon would describe the “most likely scenario” of each treatment option. Surgeons were allowed to describe each best and worst case scenario as they best saw fit according to the individual patient circumstances. Thirty cardiac, vascular, and general surgeons at the University of Wisconsin completed a two hour training on the communication framework.
In this pre/post study, investigators enrolled 32 elderly hospitalized patients with urgent, but not emergent, surgical conditions with a high risk of adverse outcome (≥40% risk for serious surgical complication or ≥8% risk of death). In the pre-intervention group, usual care conversations were audiotaped. In the post-intervention group, conversations using the “best case/worst case” framework were audiotaped.
The primary outcome was the OPTION 5 score (https://www.ncbi.nlm.nih.gov/pubmed/25956069), which allows a rater to rate the decision making process on 1) presentation of multiple options, 2) establishment of a partnership with the patient, 3) description of the treatment differences in each option, 4) elicitation of patient preferences, and 5) integration of patient preferences into the plan.
Prior to the intervention, the median OPTION 5 score of audiotaped conversations was 41 (on a 0-100 scale)—and improved to 74 in the post-intervention group. Surgeons in the intervention group were more likely to involve patients and families in decision making, were more likely to present various treatment choices, and were more likely to describe outcomes rather than isolated procedural risks.
During the discussion at our SDM working group, several strengths of this approach were noted:
This method was easily adoptable by surgeons and can be used in high stakes decisions in the acute hospital setting.
Whereas many patients undergoing potentially risky surgical procedures may not be aware of potential complications, this method formally allowed for patients and surgeons to at least consider a “worst case scenario.” This has the potential to spark discussion about what a patient values most in determining a treatment plan.
This method allowed surgeons the flexibility to tailor the treatment options as well as the outcomes of those options to the individual patient. This may therefore represent a universal, non-disease and non-context specific method to improve shared decision making discussions in general.
We also noted several questions and limitations:
What constitutes a “best case” or “worst case” outcome may considerably vary between patients—as patients value different things when faced with high stakes, end of life decisions. Some people at our working group thought that the example descriptions of the “most likely” outcome actually seemed worse than the example descriptions of the “worst case” outcomes. Who determines what the best and worst case scenarios were? Was this left up to the individual surgeon? Were the descriptions standardized in any way? Were questions asked to assess if description of best and worst outcomes rang true to the individual patient? How much were patients influenced by a potentially biased presentation of one treatment option versus the other? What do we know about the patients’ perspectives and interpretations of the best case and worst case scenarios?
To our knowledge, the likelihood of the outcomes was not specifically disclosed in a salient manner. If one were to apply the best case/worst case methodology to a “lower stakes” decision, the worst case scenario may be very rare—and the most common outcome a particular decision may be that nothing changes.
Even though the OPTION 5 score was higher in the post intervention group, does this really mean that a better decision was made? While we agree that the OPTION 5 (https://www.ncbi.nlm.nih.gov/pubmed/25956069 ) and OPTION 12 (https://www.ncbi.nlm.nih.gov/pubmed/15713169) scores represent a good attempt to measure a certain quality of shared decision making, there are still various aspects of decision making that are overlooked. Tools to better measure the quality of decision making are needed.
While we congratulate the authors on having a high inter-observer agreement regarding ratings on the OPTION 5 score (.8), this is much higher than what most other groups (including our group and the group validating the instrument) (https://www.ncbi.nlm.nih.gov/pubmed/25956069) have been able to achieve (.6 to .7). In addition, both the pre-intervention and post-intervention OPTION 5 scores were quite a bit higher than what we have seen in other trials, including ours. Additional information about the process of training observers and measuring inter-observer reliability is desirable.
Overall, Dr. Schwarze and colleagues (http://www.surgery.wisc.edu/research/researchers-labs/schwarze/) showed that a framework for formally presenting the best case outcome, worst case outcome, and most likely outcome of various treatment options increased shared decision making as measured by the OPTION 5 score. We congratulate Dr. Schwarze and colleagues for developing and testing a framework to try to improve decision making for high stakes surgical decisions for hospitalized elderly adults!
Submitted by Michael Wilson, M.D. Dr. Wilson studies end-of-life decision-making in the hospital and intensive care unit (ICU). He aims to improve individualized prognostication, shared decision-making and the delivery of quality palliative care to patients and their family members in the hospital setting.
References
Taylor LJ, Nabozny MJ, Steffens NM, et al. A Framework to Improve Surgeon Communication in High-Stakes Surgical Decisions: Best Case/Worst Case. JAMA Surg 2017.
Authors: Claudia C. Dobler, Gabriela Spencer-Bonilla, Michael R. Gionfriddo, Juan Pablo Brito
Shared decision making (SDM) has been widely advocated [1] and called the pinnacle of patient-centered care [2]. Translating this ideal into reality has proven challenging [3]. Several papers have identified barriers to the translation of SDM into practice [4-6]. A number of challenges arise in the context of intercultural and inter-linguistic SDM, which may be particularly pertinent to immigrant populations. Some of the challenges of SDM in an intercultural context have been summarized in a paper by Suurmond et al. [7]. These challenges include 1) language barriers, need for interpreters, 2) differences in health beliefs and concepts of illness between the patient and clinician, 3) differences in role expectations, e.g. an apparent preference for a paternalistic approach or desire for family-centered model of decision making, 4) consultation situation (e.g. time constraint and lack of culturally adapted patient information), and 5) low health literacy. Recently, our SDM Working group at Mayo discussed this article with the lens of applying the lessons to the development of an SDM tool for immigrant patients discussing preventive tuberculosis treatment with their clinicians.
A core component of SDM is communication. When clinicians and patients have to communicate through an interpreter, the work of SDM is complicated by: incorporating a third party into a sometimes intimate conversation, disruption of typical communication flow, lengthening of the medical encounter, and the telephone effect when interpreters engage in interpretation and curation of language rather than pure translation. Interpreters, whether professional or lay, may make judgments about which information is important to convey to patients (and back to the clinician) and which information is not. Little is known about how this form of triadic communication affects the process of SDM and the extent to which interpreters’ knowledge, attitudes and beliefs affect SDM and the use of SDM tools in clinical encounters. A recently published study that analyzed three consultations with an interpreter in which an Option Grid for osteoarthritis was used, found that discussions of treatment options were mainly between clinician and interpreter [8]. Patients had only minimal participation in the discussion with an average of four words articulated when they had an opportunity to speak, indicating that patients did not have a significant role in discussing treatment options.
In addition to differences in language, patients may have illness narratives [9] and health literacy which do not align with those of their clinicians. Providing care is also complicated by the fact that immigrants, especially those newly arrived in the destination country and with limited socio-economic resources, can have pressing material needs and concerns like providing for the daily needs of their families. A holistic approach to improving health and well-being must also take into account each patient’s context in the decision making process.
A single solution will not address all of these barriers, and more research is needed to determine the effectiveness of available interventions. For conversations that require interpreters, more research is needed around the dynamics of these triadic conversations as well as strategies for facilitating SDM in this context. For example, future research in this area could evaluate the effect of academic detailing (on SDM and the use of encounter decision aids), or training of interpreters on using SDM during the clinical encounter. Testing whether this could be achieved with interpreters working over the phone has the potential for widespread implementation. Research is also required to find models of SDM that do not only facilitate collaborative deliberation between two individuals (the patient and the clinician), but facilitate the inclusion of family members and carers into the decision making process. To adapt to cultural differences, group education classes or shared visits in addition to individual encounters may help create a cohesive narrative between patients and clinicians. This strategy is currently being implemented by one of our collaborators in China. As many cultures have a family-centered model of decision making, patients’ families could be integrated into these group classes as well.
At times, SDM conversations will need to incorporate existential or practical needs that extend beyond a specific medical decision. Thus, components of the ICAN tool, which can help prompt conversation about the patient’s context and situation including goals, priorities, capacity, and burden [10], may be a useful addition to a SDM intervention in this disease context.
While ongoing refugee crises throughout the world have highlighted the limitations of current approaches to SDM, these challenges exist to varying degrees in all encounters; we all have our own microcultures and idiosyncrasies. Discovering how to communicate with one another in an effective, respectful, compassionate, and empathic manner is essential for the realization of the promises of patient-centered care.
We welcome the opportunity for continued conversations and collaborations. Please share your comments, stories and experiences in this area. Contact us at KERUNIT@mayo.edu.
References
Frosch DL, Moulton BW, Wexler RM, Holmes-Rovner M, Volk RJ, Levin CA. Shared decision making in the United States: policy and implementation activity on multiple fronts. Z Evid Fortbild Qual Gesundhwes 2011: 105(4): 305-312.
Barry MJ, Edgman-Levitan S. Shared decision making–pinnacle of patient-centered care. N Engl J Med 2012: 366(9): 780-781.
Elwyn G, Scholl I, Tietbohl C, Mann M, Edwards AG, Clay C, Legare F, van der Weijden T, Lewis CL, Wexler RM, Frosch DL. “Many miles to go …”: a systematic review of the implementation of patient decision support interventions into routine clinical practice. BMC medical informatics and decision making 2013: 13 Suppl 2: S14.
Legare F, Thompson-Leduc P. Twelve myths about shared decision making. Patient education and counseling 2014: 96(3): 281-286.
Joseph-Williams N, Elwyn G, Edwards A. Knowledge is not power for patients: a systematic review and thematic synthesis of patient-reported barriers and facilitators to shared decision making. Patient education and counseling 2014: 94(3): 291-309.
Legare F, Witteman HO. Shared decision making: examining key elements and barriers to adoption into routine clinical practice. Health Aff (Millwood) 2013: 32(2): 276-284.
Suurmond J, Seeleman C. Shared decision-making in an intercultural context. Barriers in the interaction between physicians and immigrant patients. Patient education and counseling 2006: 60(2): 253-259.
Wood F, Phillips K, Edwards A, Elwyn G. Working with interpreters: The challenges of introducing Option Grid patient decision aids. Patient education and counseling 2017: 100(3): 456-464.
Kleinman Arthur. The Illness Narratives: Suffering, Healing, And The Human Condition. Basic Books, 1988.
Boehmer KR, Hargraves IG, Allen SV, Matthews MR, Maher C, Montori VM. Meaningful conversations in living with and treating chronic conditions: development of the ICAN discussion aid. BMC Health Serv Res 2016: 16(1): 514.
Obesity is a complex condition that places a substantial burden on patients. Not only does excess weight gain increase one’s risk for many serious health issues, including coronary artery disease, obstructive sleep apnea, type 2 diabetes, stroke, and various malignancies, but obesity and its associated health problems also result in significant economic impact for individuals and the United States health care system as a whole. Additionally, the emotional impact of obesity should not be forgotten; studies suggest that obesity and depression often go hand-in-hand. Obese individuals are at a significantly higher risk for major depression, and the burden of depression is often reduced with sustained excess weight loss.
Even as obesity continues to affect a greater number of this country’s adults, more and more treatment options are becoming available to assist patients with losing weight. However, these treatments involve a dizzying variety of risks, benefits, cost, and relative impact, making for a difficult decision for patients and a challenging discussion for physicians. The importance of this patient-physician interaction and the presence of shared decision making is apparent, as the treatment of obesity, like any other chronic disease, cannot be separated from the patient’s life and circumstances. Instead, it must be personalized and integrated into the context of one’s life.
The patient-physician conversation is an important setting for exploring how current evidence and knowledge may help patients clarify which treatment option makes intellectual, practical, and emotional sense for them. Shared decision making (SDM) tools used during the clinical encounter support these vital conversations about diagnostic and treatment decisions. Such tools have been devised for complex conditions including diabetes, Graves’ disease, and rheumatoid arthritis; however, no SDM tools have yet been developed to support conversations about the treatment of obesity. Therefore, I have decided to join the Knowledge and Evaluation Research Unit to work with the team in developing a SDM tool for obesity treatment. Once created, it will facilitate patients’ engagement in the decision-making process to ensure that the chosen treatments are congruent with each patient’s values, preferences, and lifestyle.
I am very honored and eager to begin working with patients in this capacity as a compliment to my clinical training as a resident physician here at Mayo Rochester. It is my hope that in working on this project, patients will be more confident, active participants in choosing the right treatment for them based on current evidence. I know that I will learn so much from the process and from patients, and I couldn’t be more excited to be working with the KER Unit to further the cause for patient-centered outcomes and research!
Jennifer Clark is an Internal Medicine Resident at the Mayo Clinic.
Communication is a challenge in my practice. As a rheumatologist in a busy, public hospital clinic, I had the privilege of caring for patients who spoke Spanish (a third), Cantonese (a third), Vietnamese, Russian, Lao, Tagalog, or English. Much can be conveyed in a smile or a warm handshake, but this is insufficient when patient and doctor need to make decisions about a complex chronic condition like rheumatoid arthritis (RA). In particular, it was hard to identify how best to manage their conditions with one of over a dozen available treatments. In my toolbox, there was a gaping hole with no tools available to facilitate RA treatment conversations for this needy population.
Sitting at my desk on a Sunday afternoon drafting a grant proposal to create tools for shared decision making for diverse populations with RA, I came across a paper describing a clinical trial of a decision aid for diabetes. Diabetes and RA share many similarities:
both are chronic diseases,
both have many options for treatment with differing risks and benefits and costs, and
both require substantial patient self-management.
This decision aid was colorful, broken out into “issue” cards – like baseball cards (except not by player, or in this case by drug, but by feature), which I thought would be a great template for an RA decision aid, one that could be presented in different languages for patients with limited health literacy.
On a whim, I wrote to the corresponding author to see if I could learn more about the process and perhaps even use their tool as a template. Within hours, I received an enthusiastic reply from Victor Montori at the Mayo Clinic. This led to a phone call, the proposal, funding, and the work generated from fruitful collaboration and inspiration.
The journey from grant writing to project completion was filled with many adventures. I had never worked with designers or with patients in research. I looked forward to the meetings of our patient advisory board. They were full of laughter and shared stories. Thanks to them I learned about real life with RA. I got a chance to listen to the patients share experiences living with RA, getting tips, and finding value and support in one another. Working with patients was hands down the most satisfying and humbling part of the process for me.
Our most recent paper describes the results of a pilot study of 166 patients with RA from vulnerable populations (racial/ethnic minority, age >65, limited health literacy, immigrant status, non-English language) that tested a low literacy RA medication summary guide and RA Choice, the decision aid. We showed that the tools improved knowledge and reduced decisional conflict in this diverse population.
Now after all the hard work, and the results of the pilot study showing the tools worked in our patient population, we want to share the tools and improve conversations for patients with RA and their clinicians everywhere. RA is a chronic, disabling condition which leads to early mortality. Patients made vulnerable by how we deliver healthcare to them experience worse outcomes, and communication in these groups still needs work. Our hope is that with these tools and continued attention to the needs of all groups in the RA community, we can help reduce disparities and improve care for all patients with RA.
Jennifer Barton, MD Associate Professor of Medicine, OHSU Staff Rheumatologist, Portland VA Medical Center Dr. Barton is an academic rheumatologist with a research focus on health communication and rheumatic diseases.
For more information on Rheumatoid Arthritis (RA) Choice, click here.
Sat May 7th. All set, ready to go! Excited to visit the KER Unit for a few weeks and to join them at the SAEM SDM Consensus Conference in New Orleans. This will be my first visit to the Mayo Clinic, and one I’ve been looking forward to since I became a research collaborator last winter.
Wed May 11th. We just returned from the Consensus Conference. It was inspiring and motivating to see so many participants (most of them clinicians) trying to find ways to make SDM work in practice and to improve care for their patients. Victor presented his keynote lecture ‘What is SDM? (and what it is not)’ and we worked on writing a paper on this keynote for Academic Emergency Medicine.
Thu May 12th. First day at the KER Unit. What a day! I attended a course on EBM, discussed grants and ongoing research projects with Juan Pablo, Mike and Aaron, and had a braindump on SDM (old and new thinking) with Victor and Ian. Note to self: replace ‘yes, but…’ by ‘yes, and…’.
Sun May 15th. Friday, I finished the AEM paper with Ana and Erik. Gaby presented her study on the effects of social networks in management of diabetes on Saturday. In the evening, we got together for drinks and laughs (with bubbles, cheese and chocolates) at Annie’s place. Today, I’m going out to meet Nilay for brunch.
Mon May 16th. Started with the weekly huddle this morning: what a great way to get an overview of what each member of the team is working on right now. I worked on our Choice Awareness project* and attended the Patient Advisory Group to discuss Juan Pablo’s project on SDM in Thyroid cancer treatment. Amazing how this group of patients manages to come together every month (for over 10 years!), to improve the work of the researchers and to make sure that researchers don’t lose the connection with ‘the real world’.
Tue May 17th. Trying to see whether the Choice Awareness project can take us to the moon! Maybe. Also met with Kasey to learn more about the ICAN tool.
Wed May 18th. No trip to the moon (yet), we will have to find other methods to make this journey. I worked with Victor to build my Apollo II. Juan Pablo and Ian joined, which led to a conversational dance of thoughts, (crazy) ideas, hypotheses, and approaches. Best day ever! In spite of, as well as because of the challenges we faced this morning. In the afternoon we came together with a group of clinicians and researchers interested in SDM in diagnostics to see how to take this field forward.
Fri May 20th. Yesterday, I discussed the progress and challenges around the Choice Awareness project in the SDM journal club. We went for dinner and drinks afterwards to continue our discussion on SDM old and new thinking. I continued with the project today, focusing on capturing the differences in SDM between a mechanical approach and a human connection. It takes two to tango, but we have no way to measure that dance. Speaking of dancing (and of mechanical approach versus human connection), in the evening we had a birthday party at the local salsa place.
May 22nd. BBQ with the KER Unit team at Aaron’s place yesterday and smores at the river with Gaby, Mike and the Montori family today.
May 25th. Worked on the Choice Awareness project for the past few days. Met with the department of Neurology yesterday to discuss possible collaboration. Kasey received good news (scholarship), as did Laura (residency). Maggie arrived, and Ana said goodbye. Sara had her last day before her maternity leave. I worked on Aaron’s manuscript and discussed a second paper for AEM on SDM/informed consent with Rachel.
May 26th. Last day at the KER Unit. Overwhelmed by how much I learned about the team, the work, the collaborations. And, to be honest: about myself and about my work as a researcher. I’m impressed how a team that advocates kind and careful care manages to practice what they preach and welcome guests in such a warm and friendly way. After saying goodbye to Kirsten, this kind and careful visit ended with a road trip with Ben to the airport. What an experience.
With love, Marleen
Marleen Kunneman, PhD. Research fellow at the department of Medical Psychology of the Academic Medical Center, University of Amsterdam (the Netherlands), and research collaborator of the KER Unit.
*Note: Results of our Choice Awareness project will be presented at the European Association for Communication in Healthcare (EACH) Conference in Heidelberg (September 7th-10th, 2016). Oral presentation on September 10th: ‘Choice Awareness as Pre-requisite for Shared Decision Making in Videos of Clinical Encounters’.
