Talking about completely different "things" in shared decision making: Presenter(s): Ian Hargraves, Mayo Clinic, United States

In COVID vaccination stand-offs, what is "fact" for one is "fake" for another. Describing the effects of vaccines is counter-productive against positions or beliefs. Most patient-clinician interactions aren't this extreme. Yet, the issue of what types of things can productively be discussed remains. Broadly, shared decision making (SDM) discusses problems, options, and preferences. Yet one person's problem, "your blood sugar is too high" is not another's "I can't afford my insulin". It's not that they don't share priorities, what type of problem diabetes is, is different. For the clinician diabetes is the effects of excessive blood glucose, for the patient, the day-to-day impediment to life. SDM is unlikely to be productive unless the clinician can switch from talking about effects to situations. Otherwise, they're discussing fundamentally different things. Using a directed-content analysis based on Purposeful SDM and McKeon's interpretive-orientations model we identified different types of things that are problems, options, and preferences in video-recorded encounters. Patients and clinicians are frequently talking about different types of things. E.g. The clinician describing a problem as the effects of osteoporosis, and the patient expressing the problem as a position "I won't take medicines". It is unproductive when this is unrecognized in conversation. Types of "things" that are problems, options, and preferences are: Effects, People's positions, Situations, and Truths. For example, a problem may be located in competing positions, where options are alternative positions, and a preference is the acceptability of adopting another position. Alternatively, a problem may be the effects of illness, with options being counter effects with side effects, and preferences reactions to these effects. While discussing the same topic, patients and clinicians may be talking about different things. Evidence, decision aids, and medical science mostly discuss effects. Inclusiveness of other types of "things" is important in SDM. [ABSTRACT FROM AUTHOR] Copyright of Patient Education & Counseling is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Patients surviving COVID-19 had increased risk for incident diabetes vs. persons without COVID-19.

SOURCE CITATION: Xie Y, Al-Aly Z. Risks and burdens of incident diabetes in long COVID: a cohort study. Lancet Diabetes Endocrinol. 2022;10:311-21. 35325624.

Designing the careful and kind clinic: an evidence-based approach.

BACKGROUND: There is evidence that creating a 'healthy workplace' can be of profound importance for clinicians, team members and patients. Yet there have been few papers that have proposed mechanisms to take decades of research and translate this into a practical list of options for leaders and managers to take into account when structuring a clinic based on care and kindness to achieve optimal health. EVIDENCE: We bring together 20 years of scholarship linking care of the caregivers with outcomes for caregivers and patients. The data are used to support both structures and cultures that will result in satisfied and thriving healthcare team members, as well as satisfied and healthy patients. RESULTS: The clinic based on care of the caregivers will be structured to address key aspects of worklife that are known to cause either satisfaction or burnout. Aspects of care, such as time pressure, chaotic environments and worker control of their workplace, will be taken into account in clinical design; organisational culture will be supportive and cohesive, emphasising quality, values and communication. Experiences based on gender and race will be measured and continuously improved; and performance will be evaluated in a new, human-centred manner. OUTCOMES: The careful and kind clinic will be a remarkable place to work; in contrast to industrialised healthcare, this will be an environment where health can indeed be optimised, for both workers and patients.

Effect of Individualized Preventive Care Recommendations vs Usual Care on Patient Interest and Use of Recommendations: A Pilot Randomized Clinical Trial.

Importance: This randomized clinical trial examines the feasibility and acceptability of a decision-making tool for increasing patient interest in individualized recommendations for preventive care services. Objective: To pilot a tool to help patients compare life expectancy gains from evidence-based preventive services. Design, Setting, and Participants: This randomized clinical trial examined patient and physician responses to a pilot decision tool incorporating personalized risk factors at 3 US primary care clinics between 2017 and 2020. Eligible patients were between ages 45 to 70 years with 2 or more high-risk factors. Patients were followed-up after 1 year. Interventions: The gain in life expectancy associated with guideline adherence to each recommended preventive service was estimated. Personalized estimates incorporating risk factors in electronic health records were displayed in a physician-distributed visual aid. During development, physicians discussed individualized results with patients using shared decision-making (SDM). During the trial, patients were randomized to receive individualized recommendations or usual care (nonmasked, parallel, 1:1 ratio). Main Outcomes and Measures: Primary outcome was patient interest in individualized recommendations, assessed by survey. Secondary outcomes were use of SDM, decisional comfort, readiness to change, and preventive services received within 1 year. Results: The study enrolled 104 patients (31 development, 39 intervention, 34 control), of whom 101 were included in analysis (mean [SD] age, 56.5 [5.3] years; 73 [72.3%] women; 80 [79.2%] Black patients) and 20 physicians. Intervention patients found the tool helpful and wanted to use it again, rating it a median 9 of 10 (IQR, 8-10) and 10 of 10 (8-10), respectively. Compared with the control group, intervention patients more often correctly identified the service least likely (18 [46%] vs 0; P = .03) to improve their life expectancy. A greater number of patients also identified the service most likely to improve their life expectancy (26 [69%] vs 10 [30%]; P = .07), although this result was not statistically significant. Intervention patients reported greater mean [SD] improvement in SDM (4.7 [6.9] points) and near-term readiness to change (13.8 points for top-3-ranked recommendations). Point estimates indicated that patients in the intervention group experienced greater, although non-statistically significant, reductions in percentage of body weight (-2.96%; 95% CI, -8.18% to 2.28%), systolic blood pressure (-6.42 mm Hg; 95% CI, -16.12 to 3.27 mm Hg), hemoglobin A1c (-0.68%; 95% CI, -1.82% to 0.45%), 10-year atherosclerotic cardiovascular disease risk score (-1.20%; 95% CI, -3.65% to 1.26%), and low-density lipoprotein cholesterol (-8.46 mg/dL; 95% CI, -26.63 to 9.70 mg/dL) than the control group. Nineteen of 20 physicians wanted to continue using the decision tool in the future. Conclusions and Relevance: In this clinical trial, an individualized preventive care decision support tool improved patient understanding of primary prevention and demonstrated promise for improved shared decision-making and preventive care utilization. Trial Registration: ClinicalTrials.gov Identifier: NCT03023813.

Quality of life, burden of treatment, safety, and avoidance of future events (QBSAfe) protocol: a pilot study testing an intervention to shift the paradigm of diabetes care.

BACKGROUND: Diabetes care has been traditionally focused on targeting certain levels of glycemic control. This narrow emphasis may impose burdens on patients, including high treatment costs, illness-related work, or side effects from medications, while leaving other patient needs and goals under-addressed. The authors aim to shift the paradigm of care for people with diabetes, to focus on quality of life, burden of treatment, safety, and avoidance of future events: the QBSAfe domains. METHODS: We describe a single-arm pilot study to assess the feasibility and acceptability of using the QBSAfe agenda setting kit (ASK) during routine clinical visits. The set of 14 conversation aid cards was co-developed with patients, family caregivers, and clinicians. The ASK will be used in the context of a clinic visit, which will be recorded by members of the study team to identify patterns of clinician-patient conversations. Feasibility will be measured by the number of participants recruited, time to goal accrual, and completeness of data collection; acceptability will be assessed using post-visit surveys of patients and clinicians. A subgroup of patients will be invited to participate in post-visit qualitative semi-structured interviews for additional feedback. This study will be conducted across three medical centers in the Midwest and East Coast of the USA. DISCUSSION: Current healthcare infrastructure and associated demands and pressures on clinicians make changes in care difficult. However, this intervention has the potential to shift conversations during clinical encounters so they can address and directly respond to patient needs, symptoms, and capacity. As part of the QBSAfe ASK, the authors are also actively collaborating with a variety of stakeholders to create tools to help clinicians respond more effectively to patient concerns as they are raised during the clinical encounters. Additional insights about the use of the QBSAfe approach in the virtual space will be gathered during the process of our study due to restrictions imposed upon face to face visit during the COVID-19 pandemic. TRIAL REGISTRATION: ClinicalTrials.gov , NCT04514523 . Registered 17 August 2020-retrospectively registered.

Remote shared decision making through telemedicine: A systematic review of the literature.

OBJECTIVES: To assess the extent to which shared decision making (SDM) can take place in telemedicine (remote SDM). METHODS: We searched Medline, Cochrane, and Scopus from 2010 until August 7th, 2020 for articles on remote SDM in the care of any patient using any technology. We also conducted a search for telemedicine articles citing key reports on SDM outcome measures. Two reviewers independently screened titles and abstracts, reviewed full text eligible studies, and synthesized their content using thematic analysis. RESULTS: Of the 12 eligible articles, most were European with patients with chronic disease or mental and behavioral health. 8 articles used synchronous remote SDM and 1 used asynchronous remote SDM. Themes related to interactional workability of both telemedicine technologies and SDM emerged, namely access to broadband, digital literacy, and satisfaction with the convenience of remote visits. CONCLUSIONS: Telemedicine technologies may foster virtual interactions that support remote SDM, which, in turn, may promote productive patient-clinician interactions and patient-centered care. PRACTICE IMPLICATIONS: Digitally-mediated consultations surged amidst the COVID-19 pandemic. The extent to which SDM frameworks developed for in-person use need any adaptation for remote SDM remains unclear. Investment in innovation, design, implementation, and effectiveness research to advance remote SDM are needed.