Dataset Information

Shared Decision Making and Autonomy Among US Participants with Multiple Sclerosis in the NARCOMS Registry.

ABSTRACT: Background:Treatment decisions in multiple sclerosis (MS) are affected by many factors and are made by the patient, doctor, or both. With new disease-modifying therapies (DMTs) emerging, the complexity surrounding treatment decisions is increasing, further emphasizing the importance of understanding decision-making preferences. Methods:North American Research Committee on Multiple Sclerosis (NARCOMS) Registry participants completed the Fall 2014 Update survey, which included the Control Preferences Scale (CPS). The CPS consists of five images showing different patient/doctor roles in treatment decision making. The images were collapsed to three categories: patient-centered, shared, and physician-centered decision-making preferences. Associations between decision-making preferences and demographic and clinical factors were evaluated using multivariable logistic regression. Results:Of 7009 participants, 79.3% were women and 93.5% were white (mean [SD] age, 57.6 [10.3] years); 56.7% reported a history of relapses. Patient-centered decision making was most commonly preferred by participants (47.9%), followed by shared decision making (SDM; 42.8%). SDM preference was higher for women and those taking DMTs and increased with age and disease duration (all P < .05). Patient-centered decisions were most common for respondents not taking a DMT at the time of the survey and were preferred by those who had no DMT history compared with those who had previously taken a DMT (P < .0001). There was no difference in SDM preference by current MS disease course after adjusting for other disease-related factors. Conclusions:Responders reported most commonly considering their doctor's opinion before making a treatment decision and making decisions jointly with their doctor. DMT use, gender, and age were associated with decision-making preference.

SUBMITTER: Cofield SS

PROVIDER: S-EPMC5734714 | biostudies-literature | 2017 Nov-Dec

REPOSITORIES: biostudies-literature

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Shared Decision Making and Autonomy Among US Participants with Multiple Sclerosis in the NARCOMS Registry.

Cofield Stacey S SS Thomas Nina N Tyry Tuula T Fox Robert J RJ Salter Amber A

International journal of MS care 20171101 6

<h4>Background</h4>Treatment decisions in multiple sclerosis (MS) are affected by many factors and are made by the patient, doctor, or both. With new disease-modifying therapies (DMTs) emerging, the complexity surrounding treatment decisions is increasing, further emphasizing the importance of understanding decision-making preferences.<h4>Methods</h4>North American Research Committee on Multiple Sclerosis (NARCOMS) Registry participants completed the Fall 2014 Update survey, which included the C ...[more]

PMID: 29270088

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Project description:BackgroundMultiple sclerosis (MS) is a chronic autoimmune inflammatory, demyelinating, and neurodegenerative disease affecting young adults. People with MS are highly interested in engaging in physical symptom management and decision-making but are often not actively engaged in symptom management discussions. Research examining the benefit of shared decision-making in the management of physical MS symptoms is sparse.ObjectivesThis study aimed to identify and synthesize the evidence on the use of shared decision-making in physical MS symptom management.DesignThis study is a systematic review of published evidence on the use of shared decision-making in physical MS symptom management.Data sources and methodsMEDLINE, CINAHL, EMBASE, and CENTRAL databases were searched in April 2021, June 2022, and April 2, 2023, for primary, peer-reviewed studies of shared decision-making in the management of MS physical symptoms. Citations were screened, data extracted, and study quality assessed according to Cochrane guidelines for systematic reviews, including risk of bias assessment. Statistical synthesis of the included study results was not appropriate; results were summarized in a nonstatistical manner using the vote-counting method to estimate beneficial versus harmful effects.ResultsOf 679 citations, 15 studies met the inclusion criteria. Six studies addressed shared decision-making in the management of pain, spasms, neurogenic bladder, fatigue, gait disorder, and/or balance issues, and nine studies addressed physical symptoms in general. One study was a randomized controlled trial; most studies were observational studies. All study results and study author conclusions indicated that shared decision-making is important to the effective management of physical MS symptoms. No study results suggested that shared decision-making was harmful or delayed the management of physical MS symptoms.ConclusionReported results consistently indicate that shared decision-making is important in effective MS symptomatic care. Further rigorous randomized controlled trials are warranted to investigate the effectiveness of shared decision-making associated with MS physical symptomatic care.RegistrationPROSPERO: CRD42023396270.

Project description:Background. Most people with multiple sclerosis (MS) want to be involved in medical decision making about disease-modifying therapies (DMTs), but new approaches are needed to overcome barriers to participation. Objectives. We sought to develop a shared decision-making (SDM) tool for MS DMTs, evaluate patient and provider responses to the tool, and address challenges encountered during development to guide a future trial. Methods. We created a patient-centered design process informed by image theory to develop the MS-SUPPORT SDM tool. Development included semistructured interviews and alpha and beta testing with MS patients and providers. Beta testing assessed dissemination and clinical integration strategies, decision-making processes, communication, and adherence. Patients evaluated the tool before and after a clinic visit. Results. MS-SUPPORT combines self-assessment with tailored feedback to help patients identify their treatment goals and preferences, correct misperceptions, frame decisions, and promote adherence. MS-SUPPORT generates a personal summary of their responses that patients can share with their provider to facilitate communication. Alpha testing (14 patients) identified areas needing improvement, resulting in reorganization and shortening of the tool. MS-SUPPORT was highly rated in beta testing (15 patients, 4 providers) on patient-provider communication, patient preparation, adherence, and other endpoints. Dissemination through both patient and provider networks appeared feasible. All patient testers wanted to share the summary report with their provider, but only 60% did. Limitations. Small sample size, no comparison group. Conclusions. The development process resulted in a patient-centered SDM tool for MS that may facilitate patient involvement in decision making, help providers understand their patients' preferences, and improve adherence, though further testing is needed. Beta testing in real-world conditions was critical to prepare the tool for future testing and inform the design of future studies.

Project description:BackgroundShared decision-making (SDM) is widely recommended and required by the Centers for Medicare and Medicaid for patients considering lung cancer screening (LCS).ObjectiveWe examined clinicians' communication practices and perceived barriers of SDM for LCS at three medical centers with established screening programs.DesignMulticenter qualitative study of clinicians participating in LCS.ApproachWe performed semi-structured interviews, which were transcribed and analyzed using directed content analysis, guided by a theoretical model of patient-clinician communication.ParticipantsWe interviewed 24 clinicians including LCS coordinators (2), pulmonologists (3), and primary care providers (17), 4 of whom worked for the LCS program, a thoracic surgeon, and a radiologist.ResultsAll clinicians agreed with the goal of SDM, to ensure the screening decision was congruent with the patient's values. The depth and type of information presented by each clinician role varied considerably. LCS coordinators presented detailed information including numeric estimates of benefit and harm. Most PCPs explained the process more generally, focusing on logistics and the high rate of nodule detection. No clinician explicitly elicited values or communication preferences. Many PCPs tailored the conversation based on their implicit understanding of patients' values and preferences, gained from past experiences. PCPs reported that time, lack of detailed personal knowledge of LCS, and patient preferences were barriers to SDM. Many clinicians perceived that a significant proportion of patients were not interested in specific percentages and preferred to receive a clinician recommendation.ConclusionsOur results suggest that clinicians support the goal of SDM for LCS decisions but PCPs may not perform some of its elements. The lack of completion of some elements, such as PCPs' lack of in-depth information exchange, may reflect perceived patient preferences for communication. As LCS is implemented, further research is needed to support a personalized, patient-centered approach to produce better outcomes.

Project description:Background. Accurate diagnosis of patients' preferences is central to shared decision making. Missing from clinical practice is an approach that links pretreatment preferences and patient-reported outcomes. Objective. We propose a Bayesian collaborative filtering (CF) algorithm that combines pretreatment preferences and patient-reported outcomes to provide treatment recommendations. Design. We present the methodological details of a Bayesian CF algorithm designed to accomplish 3 tasks: 1) eliciting patient preferences using conjoint analysis surveys, 2) clustering patients into preference phenotypes, and 3) making treatment recommendations based on the posttreatment satisfaction of like-minded patients. We conduct a series of simulation studies to test the algorithm and to compare it to a 2-stage approach. Results. The Bayesian CF algorithm and 2-stage approaches performed similarly when there was extensive overlap between preference phenotypes. When the treatment was moderately associated with satisfaction, both methods made accurate recommendations. The kappa estimates measuring agreement between the true and predicted recommendations were 0.70 (95% confidence interval = 0.052-0.88) and 0.73 (0.56-0.90) under the Bayesian CF and 2-stage approaches, respectively. The 2-stage approach failed to converge in settings in which clusters were well separated, whereas the Bayesian CF algorithm produced acceptable results, with kappas of 0.73 (0.56-0.90) and 0.83 (0.69-0.97) for scenarios with moderate and large treatment effects, respectively. Limitations. Our approach assumes that the patient population is composed of distinct preference phenotypes, there is association between treatment and outcomes, and treatment effects vary across phenotypes. Findings are also limited to simulated data. Conclusion. The Bayesian CF algorithm is feasible, provides accurate cluster treatment recommendations, and outperforms 2-stage estimation when clusters are well separated. As such, the approach serves as a roadmap for incorporating predictive analytics into shared decision making.

Dataset Information

Shared Decision Making and Autonomy Among US Participants with Multiple Sclerosis in the NARCOMS Registry.

Publications

Shared Decision Making and Autonomy Among US Participants with Multiple Sclerosis in the NARCOMS Registry.

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