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      The design of a low literacy decision aid about rheumatoid arthritis medications developed in three languages for use during the clinical encounter

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          Abstract

          Background

          Shared decision-making in rheumatoid arthritis (RA) care is a priority among policy makers, clinicians and patients both nationally and internationally. Demands on patients to have basic knowledge of RA, treatment options, and details of risk and benefit when making medication decisions with clinicians can be overwhelming, especially for those with limited literacy or limited English language proficiency. The objective of this study is to describe the development of a medication choice decision aid for patients with rheumatoid arthritis (RA) in three languages using low literacy principles.

          Methods

          Based on the development of a diabetes decision aid, the RA decision aid (RA Choice) was developed through a collaborative process involving patients, clinicians, designers, decision-aid and health literacy experts. A combination of evidence synthesis and direct observation of clinician-patient interactions generated content and guided an iterative process of prototype development.

          Results

          Three iterations of RA Choice were developed and field-tested before completion. The final tool organized data using icons and plain language for 12 RA medications across 5 issues: frequency of administration, time to onset, cost, side effects, and special considerations. The tool successfully created a conversation between clinician and patient, and garnered high acceptability from clinicians.

          Conclusions

          The process of collaboratively developing an RA decision aid designed to promote shared decision making resulted in a graphically-enhanced, low literacy tool. The use of RA Choice in the clinical encounter has the potential to enhance communication for RA patients, including those with limited health literacy and limited English language proficiency.

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          Most cited references 34

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          EULAR recommendations for the management of rheumatoid arthritis with synthetic and biological disease-modifying antirheumatic drugs

          Treatment of rheumatoid arthritis (RA) may differ among rheumatologists and currently, clear and consensual international recommendations on RA treatment are not available. In this paper recommendations for the treatment of RA with synthetic and biological disease-modifying antirheumatic drugs (DMARDs) and glucocorticoids (GCs) that also account for strategic algorithms and deal with economic aspects, are described. The recommendations are based on evidence from five systematic literature reviews (SLRs) performed for synthetic DMARDs, biological DMARDs, GCs, treatment strategies and economic issues. The SLR-derived evidence was discussed and summarised as an expert opinion in the course of a Delphi-like process. Levels of evidence, strength of recommendations and levels of agreement were derived. Fifteen recommendations were developed covering an area from general aspects such as remission/low disease activity as treatment aim via the preference for methotrexate monotherapy with or without GCs vis-à-vis combination of synthetic DMARDs to the use of biological agents mainly in patients for whom synthetic DMARDs and tumour necrosis factor inhibitors had failed. Cost effectiveness of the treatments was additionally examined. These recommendations are intended to inform rheumatologists, patients and other stakeholders about a European consensus on the management of RA with DMARDs and GCs as well as strategies to reach optimal outcomes of RA, based on evidence and expert opinion.
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            Helping patients decide: ten steps to better risk communication.

            With increasing frequency, patients are being asked to make complex decisions about cancer screening, prevention, and treatment. These decisions are fraught with emotion and cognitive difficulty simultaneously. Many Americans have low numeracy skills making the cognitive demands even greater whenever, as is often the case, patients are presented with risk statistics and asked to make comparisons between the risks and benefits of multiple options and to make informed medical decisions. In this commentary, we highlight 10 methods that have been empirically shown to improve patients' understanding of risk and benefit information and/or their decision making. The methods range from presenting absolute risks using frequencies (rather than presenting relative risks) to using a risk format that clarifies how treatment changes risks from preexisting baseline levels to using plain language. We then provide recommendations for how health-care providers and health educators can best to communicate this complex medical information to patients, including using plain language, pictographs, and absolute risks instead of relative risks.
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              A randomized comparative effectiveness study of oral triple therapy versus etanercept plus methotrexate in early aggressive rheumatoid arthritis: the treatment of Early Aggressive Rheumatoid Arthritis Trial.

              To assess whether it is better to intensively treat all patients with early rheumatoid arthritis (RA) using combinations of drugs or to reserve this approach for patients who do not have an appropriate response (as determined by a Disease Activity Score in 28 joints using the erythrocyte sedimentation rate [DAS28-ESR] of ≥ 3.2 at week 24) to methotrexate (MTX) monotherapy, and to assess whether combination therapy with MTX plus etanercept is superior to the combination of MTX plus sulfasalazine plus hydroxychloroquine. The Treatment of Early Aggressive Rheumatoid Arthritis (TEAR) study is a 2-year, randomized, double-blind trial. A 2 × 2 factorial design was used to randomly assign subjects to 1 of 4 treatment arms: immediate treatment with MTX plus etanercept, immediate oral triple therapy (MTX plus sulfasalazine plus hydroxychloroquine), or step-up from MTX monotherapy to one of the combination therapies (MTX plus etanercept or MTX plus sulfasalazine plus hydroxychloroquine) at week 24 if the DAS28-ESR was ≥ 3.2. All treatment arms included matching placebos. The primary outcome was an observed-group analysis of DAS28-ESR values from week 48 to week 102. At week 24 (beginning of the step-up period), subjects in the 2 immediate-treatment groups demonstrated a greater reduction in the DAS28-ESR compared with those in the 2 step-up groups (3.6 versus 4.2; P < 0.0001); no differences between the combination-therapy regimens were observed. Between week 48 and week 102, subjects randomized to the step-up arms had a DAS28-ESR clinical response that was not different from that of subjects who initially received combination therapy, regardless of the treatment arm. There was no significant difference in the DAS28-ESR between subjects randomized to oral triple therapy and those randomized to receive MTX plus etanercept. By week 102, there was a statistically significant difference in the change in radiographic measurements from baseline between the group receiving MTX plus etanercept and the group receiving oral triple therapy (0.64 versus 1.69; P = 0.047). There were no differences in the mean DAS28-ESR during weeks 48-102 between subjects randomized to receive MTX plus etanercept and those randomized to triple therapy, regardless of whether they received immediate combination treatment or step-up from MTX monotherapy. At 102 weeks, immediate combination treatment with either strategy was more effective than MTX monotherapy prior to the initiation of step-up therapy. Initial use of MTX monotherapy with the addition of sulfasalazine plus hydroxychloroquine (or etanercept, if necessary, after 6 months) is a reasonable therapeutic strategy for patients with early RA. Treatment with the combination of MTX plus etanercept resulted in a statistically significant radiographic benefit compared with oral triple therapy. Copyright © 2012 by the American College of Rheumatology.
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                Author and article information

                Contributors
                Jennifer.Barton@va.gov
                Christopher.Koenig@ucsf.edu
                Gina.Evans-Young@ucsf.edu
                Laura.Trupin@ucsf.edu
                jennie.e.anderson@gmail.com
                drzeos@gmail.com
                maggie.breslin@gmail.com
                future.timothy@gmail.com
                dschillinger@medsfgh.ucsf.edu
                Montori.Victor@mayo.edu
                Ed.Yelin@ucsf.edu
                Journal
                BMC Med Inform Decis Mak
                BMC Med Inform Decis Mak
                BMC Medical Informatics and Decision Making
                BioMed Central (London )
                1472-6947
                25 November 2014
                25 November 2014
                2014
                : 14
                Affiliations
                [ ]Department of Medicine, University of California, San Francisco, CA USA
                [ ]Division of Hospital & Specialty Medicine, Portland Veterans Affairs Medical Center, 3710 SW US Veterans Hospital Road, Portland, OR 97239 USA
                [ ]Phillip R. Lee Institute for Health Policy Studies, San Francisco, CA USA
                [ ]San Francisco, CA USA
                [ ]Brooklyn, NY USA
                [ ]Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, MN 55905 USA
                Article
                104
                10.1186/s12911-014-0104-8
                4363399
                25649726
                © Barton et al.; licensee BioMed Central. 2014

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                Categories
                Research Article
                Custom metadata
                © The Author(s) 2014

                Bioinformatics & Computational biology

                health literacy, rheumatoid arthritis, decision aid

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