Victor M. Montori

Body composition and quality of life in adults treated with GH therapy: a systematic review and meta-analysis.

OBJECTIVEnTo summarise the evidence about the efficacy and safety of using GH in adults with GH deficiency focusing on quality of life and body composition.nnnDATA SOURCESnWe searched MEDLINE, EMBASE, Cochrane CENTRAL, Web of Science and Scopus through April 2011. We also reviewed reference lists and contacted experts to identify candidate studies.nnnSTUDY SELECTIONnReviewers, working independently and in duplicate, selected randomised controlled trials (RCTs) that compared GH to placebo.nnnDATA SYNTHESISnWe pooled the relative risk (RR) and weighted mean difference (WMD) by the random effects model and assessed heterogeneity using the I(2) statistic.nnnRESULTSnFifty-four RCTs were included enrolling over 3400 patients. The quality of the included trials was fair. GH use was associated with statistically significant reduction in weight (WMD, 95% confidence interval (95% CI): -2.31u200akg, -2.66 and -1.96) and body fat content (WMD, 95% CI: -2.56u200akg, -2.97 and -2.16); increase in lean body mass (WMD, 95% CI: 1.38, 1.10 and 1.65), the risk of oedema (RR, 95% CI: 6.07, 4.34 and 8.48) and joint stiffness (RR, 95% CI: 4.17, 1.4 and 12.38); without significant changes in body mass index, bone mineral density or other adverse effects. Quality of life measures improved in 11 of the 16 trials although meta-analysis was not feasible.nnnRESULTSnGH therapy in adults with confirmed GH deficiency reduces weight and body fat, increases lean body mass and increases oedema and joint stiffness. Most trials demonstrated improvement in quality of life measures.

Does the chronic care model meet the emerging needs of people living with multimorbidity? A systematic review and thematic synthesis

Background The Chronic Care Model (CCM) emerged in the 1990s as an approach to re-organize primary care and implement critical elements that enable it to proactively attend to patients with chronic conditions. The chronic care landscape has evolved further, as most patients now present with multiple chronic conditions and increasing psychosocial complexity. These patients face accumulating and overwhelming complexity resulting from the sum of uncoordinated responses to each of their problems. Minimally Disruptive Medicine (MDM) was proposed to respond to this challenge, aiming at improving outcomes that matter to patients with the smallest burden of treatment. We sought to critically appraise the extent to which MDM constructs (e.g., reducing patient work, improving patients’ capacity) have been adopted within CCM implementations. Methods We conducted a systematic review and qualitative thematic synthesis of reports of CCM implementations published from 2011–2016. Results CCM implementations were mostly aligned with the healthcare system’s goals, condition-specific, and targeted disease-specific outcomes or healthcare utilization. No CCM implementation addressed patient work. Few reduced treatment workload without adding additional tasks. Implementations supported patient capacity by offering information, but rarely offered practical resources (e.g., financial assistance, transportation), helped patients reframe their biography with chronic illness, or assisted them in engaging with a supportive social network. Few implementations aimed at improving functional status or quality of life, and only one-third of studies were targeted for patients of low socioeconomic status. Conclusion MDM provides a lens to operationalize how to care for patients with multiple chronic conditions, but its constructs remain mostly absent from how implementations of the CCM are currently reported. Improvements to the primary care of patients with multimorbidity may benefit from the application of MDM, and the current CCM implementations that do apply MDM constructs should be considered exemplars for future implementation work.

Fostering Choice Awareness for Shared Decision Making: A Secondary Analysis of Video-Recorded Clinical Encounters

Objective To assess the extent to which (1) clinicians, using or not using conversation aids, foster choice awareness during clinical encounters and (2) fostering choice awareness, with or without conversation aids, is associated with greater patient involvement in shared decision making (SDM). Patients and Methods We randomly selected 100 video-recorded encounters, stratified by topic and study arm, from a database of 10 clinical trials of SDM interventions in 7 clinical contexts: low-risk acute chest pain, stable angina, diabetes, depression, osteoporosis, and Graves disease. Reviewers, unaware of our hypothesis, coded recordings with the OPTION-12 scale to quantify the extent to which clinicians involved patients in decision making (SDM, 0-100 score). Blinded to OPTION-12 scale scores, we used a self-developed coding scale to code whether and how choice awareness was fostered. Results Clinicians fostered choice awareness in 53 of 100 encounters. Fostering choice awareness was associated with a higher OPTION-12 scale score (adjusted [for using vs not using a conversation aid] predicted mean difference, 20; 95% CI, 11-29). Using a conversation aid was associated with a higher, nonsignificant chance of fostering choice awareness (N=31 of 50 [62%] vs N=22 of 50 [44%]; adjusted [for trial] P=.34) and with a higher OPTION-12 scale score, although adjusting for fostering choice awareness mitigated this effect (adjusted predicted mean difference 5.8; 95% CI, −1.3-12.8). Conclusion Fostering choice awareness is linked to a better execution of other SDM steps, such as informing patients or discussing preferences, even when SDM tools are not available or not used.

Primary Prevention with Statins: Strategies to Support Shared Decision-Making

Purpose of ReviewThis paper proposes several strategies for health systems, primary care clinicians, cardiologists, and other members of the healthcare team to better engage individuals in decisions around primary preventive statin therapy.Recent FindingsThe 2013 American College of Cardiology and American Heart Association (ACC/AHA) guidelines for cholesterol management provide an opportunity to better engage patients in decisions about primary prevention of cardiovascular disease, including the initiation of statin therapy.SummaryIn the shared decision making process, clinicians and patients work together to determine what is best for the patient, taking into account the scientific evidence informing guideline recommendations, the clinician’s knowledge and experience, the known burdens of taking a daily lifelong medication, and the patient’s preferences, values and goals. Several challenges exist to adopting shared decision making as a patient-centered model of care.

Big Science for patient centred care

Only massive and fearless collaboration can produce evidence that works for patient care

An Informatics Approach to Implement Support for Shared Decision Making for Primary Prevention Statin Therapy

Background. Shared decision making (SDM) is recommended prior to initiation of statin therapy for primary prevention but is underutilized. We designed an informatics decision-support tool to facilitate use of the Mayo Clinic Statin Choice decision aid at the point-of-care and evaluated its impact. Methods. Using an iterative approach, we designed and implemented a single-click decision-support tool embedded within the electronic health records (EHRs) to automate the calculation of 10-year atherosclerotic cardiovascular disease (ASCVD) risk and populate the Statin Choice decision aid. We surveyed primary care providers at two clinics regarding their attitudes about SDM before and after deployment of intervention, as well as their usage of and perceived competence regarding SDM for primary prevention statin therapy. Three-month web traffic to the Statin Choice website was calculated before and after deployment of the intervention. Results. Pre–post surveys were completed by 60 primary care providers (24 [40%] attending physicians and 36 [60%] housestaff physicians). After deployment of the EHR tool, respondents were more aware of the Statin Choice decision aid (P < 0.001), reported being more competent regarding SDM (P = 0.047), and reported using decision aids more often when considering statin initiation (P = 0.043). There was no significant change in attitudes about SDM as measured through the Patient Provider Orientation Scale (pre 4.23 ± 0.40 v. post 4.16 ± 0.38, P = 0.11) and the SDM belief scale (pre 21.4 ± 2.1 v. post 21.1 ± 2.0, P = 0.35). Web-based usage rates for the Statin Choice decision aid increased from 3.4 to 5.2 per 1,000 outpatient clinic visits (P = 0.002). Conclusions. Implementation of a point-of-care decision-support tool increased the usage of decision aids for primary prevention statin therapy. This effect does not appear to be mediated by any concomitant changes in physician attitude toward SDM.

Humor During Clinical Practice: Analysis of Recorded Clinical Encounters

Objective: Little is known about humors use in clinical encounters, despite its many potential benefits. We aimed to describe humor during clinical encounters. Design: We analyzed 112 recorded clinical encounters. Two reviewers working independently identified instances of humor, as well as information surrounding the logistics of its use. Results: Of the 112 encounters, 66 (59%) contained 131 instances of humor. Humor was similarly frequent in primary care (36/61, 59%) and in specialty care (30/51, 59%), was more common in gender-concordant interactions (43/63, 68%), and was most common during counseling (81/112, 62%). Patients and clinicians introduced humor similarly (63 vs 66 instances). Typically, humor was about the patients medical condition (40/131, 31%). Discussion and Conclusion: Humor is used commonly during counseling to discuss the patients medical condition and to relate to general life events bringing warmth to the medical encounter. The timing and topic of humor and its use by all parties suggests humor plays a role in the social connection between patients and physicians and allows easier discussion of difficult topics. Further research is necessary to establish its impact on clinicians, patients, and outcomes.

Shared decision-making in atrial fibrillation: navigating complex issues in partnership with the patient

Atrial fibrillation (AF) is an important risk factor for stroke. Although anticoagulation is effective in mitigating this risk, many high-risk patients are not anticoagulated in routine practice. Furthermore, as many as 50% of those who are prescribed an anticoagulant stop treatment within a year. This under treatment may be due, in part, to difficulty in navigating difficult decisions about initiating potentially lifelong therapy with significant costs, potential risks, and impact on daily life. To address these challenges, the most recent American guidelines issued a class I recommendation to use shared decision-making (SDM) to individualize patients’ antithrombotic care. The call by the major cardiovascular organizations for SDM is in an effort to improve quality of care by promoting decisions that reflect what is best for an individual patient based on their stroke and bleeding risks, as well as their comorbid conditions and socio-personal context. SDM is readily applicable to current cardiovascular practice, but ongoing work will be needed to determine whether brief, evidence-based, and patient-oriented tools are able to support thoughtful, patient-centered decision-making and, ultimately, improve the rates of appropriate treatment initiation and adherence.

Impact of decision aids used during clinical encounters on clinician outcomes and consultation length: a systematic review

Background Clinicians’ satisfaction with encounter decision aids is an important component in facilitating implementation of these tools. We aimed to determine the impact of decision aids supporting shared decision making (SDM) during the clinical encounter on clinician outcomes. Methods We searched nine databases from inception to June 2017. Randomised clinical trials (RCTs) of decision aids used during clinical encounters with an unaided control group were eligible for inclusion. Due to heterogeneity among included studies, we used a narrative evidence synthesis approach. Results Twenty-five papers met inclusion criteria including 22 RCTs and 3 qualitative or mixed-methods studies nested in an RCT, together representing 23 unique trials. These trials evaluated healthcare decisions for cardiovascular prevention and treatment (n=8), treatment of diabetes mellitus (n=3), treatment of osteoporosis (n=2), treatment of depression (n=2), antibiotics to treat acute respiratory infections (n=3), cancer prevention and treatment (n=4) and prenatal diagnosis (n=1). Clinician outcomes were measured in only a minority of studies. Clinicians’ satisfaction with decision making was assessed in only 8 (and only 2 of them showed statistically significantly greater satisfaction with the decision aid); only three trials asked if clinicians would recommend the decision aid to colleagues and only five asked if clinicians would use decision aids in the future. Outpatient consultations were not prolonged when a decision aid was used in 9 out of 13 trials. The overall strength of the evidence was low, with the major risk of bias related to lack of blinding of participants and/or outcome assessors. Conclusion Decision aids can improve clinicians’ satisfaction with medical decision making and provide helpful information without affecting length of consultation time. Most SDM trials, however, omit outcomes related to clinicians’ perspective on the decision making process or the likelihood of using a decision aid in the future.

External validity, generalisability, applicability and directness: a brief primer

External validity is a construct that attempts to answer the question of whether we can use the results of a study in patients other than those enrolled in the study. External validity consists of two unique underlying concepts, generalisability and applicability. When the concern is about extending the results from a sample to the population from which the sample was drawn, the problem is one of generalisability. When the concern is about using inferences drawn from study participants in the care of specific patients belonging to any population, the problem is one of applicability. Clinicians, guideline developers and policymakers do not struggle with generalisability, but often struggle with applicability. When applicability is deemed to be low for a certain population, certainty in the supporting evidence becomes low due to indirectness.