Dataset Information

"I Will Respect the Autonomy of My Patient": A Scoping Review of Shared Decision Making in Multiple Sclerosis.

ABSTRACT:

Background

Patient autonomy is a bioethical principle that was strengthened in the revised Declaration of Geneva. Shared decision making (SDM) is particularly relevant in the management of multiple sclerosis (MS) because many preference-sensitive decisions have to be made during the disease course. We aimed to summarize the available evidence on SDM in the MS field and to inform future research and practice.

Methods

We performed a scoping review by searching MEDLINE (past 5 years). Studies were included if they reported primary/secondary research and focused on SDM related to people with MS. Data were grouped into topics, with results presented in narrative form.

Results

From 865 references, we included 55 studies conducted mostly in Europe. Half of the studies were observational, followed by qualitative (20%), mixed-methods (17%), randomized controlled trials (RCTs, 5%), quasi-experimental (5%), and reviews (4%). Most studies addressed people with relapsing-remitting MS (85%); the remaining addressed health care professionals, patients' significant others, or a combination. We identified five main topics: decisions on disease-modifying drugs, decisions on chronic cerebrospinal venous insufficiency treatment, information provision and patient education, health literacy, and risk knowledge.

Conclusions

The high proportion of included studies on SDM in MS in Europe suggests an earlier adoption of these concepts in this area. Decisions on disease-modifying drugs was the prevalent topic. Only 5% of studies were RCTs, indicating that more research is needed to study the effectiveness of SDM interventions. Studies addressing people with primary and secondary progressive MS are also needed.

SUBMITTER: Rahn AC

PROVIDER: S-EPMC7780705 | biostudies-literature | 2020 Nov-Dec

REPOSITORIES: biostudies-literature

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Publications

"I Will Respect the Autonomy of My Patient": A Scoping Review of Shared Decision Making in Multiple Sclerosis.

Rahn Anne Christin AC Solari Alessandra A Beckerman Heleen H Nicholas Richard R Wilkie David D Heesen Christoph C Giordano Andrea A

International journal of MS care 20201101 6

<h4>Background</h4>Patient autonomy is a bioethical principle that was strengthened in the revised Declaration of Geneva. Shared decision making (SDM) is particularly relevant in the management of multiple sclerosis (MS) because many preference-sensitive decisions have to be made during the disease course. We aimed to summarize the available evidence on SDM in the MS field and to inform future research and practice.<h4>Methods</h4>We performed a scoping review by searching MEDLINE (past 5 years) ...[more]

PMID: 33424485

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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:BackgroundMany suggest that shared decision-making (SDM) is the most effective approach to clinical counseling. It is unclear if this applies to surgical decision-making-especially regarding urgent, highly-morbid operations. In this scoping review, we identify articles that address patient and surgeon preferences toward SDM in surgery.MethodsWe used the Preferred Reporting Items for Systematic Reviews and Meta-analyses extension for Scoping Reviews (PRISMA-ScR) to develop our protocol. Medline, EMBASE, and Cochrane databases were searched from inception through 11.2017. Title/abstract review identified peer-reviewed, empirical articles that addressed patient/surgeon preferences toward SDM in surgery. Identified articles underwent full review by two independent investigators. We addressed the following questions: (1) What is known from existing empirical evidence about patients' and/or surgeons' surgical decision-making preferences? (2) Why might patients and/or surgeons prefer SDM? (3) Does acuity of intervention impact surgical decision-making preferences? Outcome measures included study methods, surgical specialty, diagnosis, study location/setting, type/number of subjects, acuity of intervention, surgeon/patient decision-making preferences, and factors associated with favoring SDM. Data was analyzed in Microsoft Excel.Results20,359 articles were identified with 4988 duplicates, yielding 15,371 articles for title/abstract review. 74 articles were included in final analysis. 68% of articles discussed oncologic decision-making. 46% of these focused on breast cancer. 92% of articles included patients, 22% included surgeons. 75% of articles found surgeons favored SDM, 25% demonstrated surgeons favored surgeon guidance. 54% of articles demonstrated patients favored SDM, 35% showed patients favored surgeon guidance, 11% showed patients preferred independent decision-making. The most common factors for patients favoring SDM included female gender, higher education, and younger age. For surgeons, the most common factors for favoring SDM included limited evidence for a given treatment plan, multiple treatment options, and impact on patient lifestyle. No articles evaluated decision-making preferences in an emergent setting.ConclusionsThere has been limited evaluation of patient and surgeon preferences toward SDM in surgical decision-making. Generally, patients and surgeons expressed preference toward SDM. None of the articles evaluated decision-making preferences in an emergent setting, so assessment of the impact of acuity on decision-making preferences is limited. Extension of research to complex, emergent clinical settings is needed.

Project description:ObjectiveTo assess decision-making in multiple sclerosis (MS) from third observer and patient perspectives.MethodAudio recordings of first-ever consultations with a participating physician (88 outpatients, 10 physicians) at four tertiary MS care clinics in Italy, were rated by a third observer using the Observing Patient Involvement in Shared Decision Making (OPTION) and by patients using the Perceived Involvement in Care Scale (PICS).ResultsMean patient age was 37.5, 66% were women, 72% had MS, and 28% had possible MS or other disease. Mean PICS subscale scores (range 0 poor, 100 best possible) were 71.9 (SD 24.3) for "physician facilitation" (PICS-F); 74.6 (SD 22.9) for "patient information exchange" (PICS-I); and only 22.5 (SD 16.2) for "patient decision making" (PICS-DM). Mean OPTION total score (0 poor, 100 best possible) was 29.6 (SD 10.3). Poorest OPTION scores were found for items assessing "preferred patient approach to receiving information" and "preferred patient level of involvement." Highest scores were for "clinician drawing attention to identified problem", "indicating need for decision making," and "need to review the decision." Consultation time, woman physician, patient-physician gender concordance and PICS-F were associated with higher OPTION total score; older physician and second opinion consultation were associated with lower OPTION score.ConclusionsIn line with findings in other settings, our third observer findings indicated limited patient involvement abilities of MS physicians during first consultations. Patient perceptions of physician skills were better than third observers', although they correlated. Consultations with women physicians, and younger physicians, were associated with higher third observer and patient-based scores. Our findings reveal a need to empower Italian MS physicians with better communication and shared decision-making skills, and show in particular that attention to MS patient preferences for reception of information and involvement in health decisions, need to be improved.

Project description:ObjectivesTo provide a comprehensive overview of interventions that support shared decision-making (SDM) for treatment modality decisions in advanced kidney disease (AKD). To provide summarised information on their content, use and reported results. To provide an overview of interventions currently under development or investigation.DesignThe JBI methodology for scoping reviews was followed. This review conforms to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) checklist.Data sourcesMEDLINE, Embase, Web of Science, Cochrane Library, Emcare, PsycINFO, PROSPERO and Academic Search Premier for peer-reviewed literature. Other online databases (eg, clinicaltrials.gov, OpenGrey) for grey literature.Eligibility for inclusionRecords in English with a study population of patients >18 years of age with an estimated glomerular filtration rate <30 mL/min/1.73 m2. Records had to be on the subject of SDM, or explicitly mention that the intervention reported on could be used to support SDM for treatment modality decisions in AKD.Data extraction and synthesisTwo reviewers independently screened and selected records for data extraction. Interventions were categorised as prognostic tools (PTs), educational programmes (EPs), patient decision aids (PtDAs) or multicomponent initiatives (MIs). Interventions were subsequently categorised based on the decisions they were developed to support.ResultsOne hundred forty-five interventions were identified in a total of 158 included records: 52 PTs, 51 EPs, 29 PtDAs and 13 MIs. Sixteen (n=16, 11%) were novel interventions currently under investigation. Forty-six (n=46, 35.7%) were reported to have been implemented in clinical practice. Sixty-seven (n=67, 51.9%) were evaluated for their effects on outcomes in the intended users.ConclusionThere is no conclusive evidence on which intervention is the most efficacious in supporting SDM for treatment modality decisions in AKD. There is a lot of variation in selected outcomes, and the body of evidence is largely based on observational research. In addition, the effects of these interventions on SDM are under-reported.

Project description:BackgroundArtificial intelligence (AI) has shown promising results in various fields of medicine. It has the potential to facilitate shared decision making (SDM). However, there is no comprehensive mapping of how AI may be used for SDM.ObjectiveWe aimed to identify and evaluate published studies that have tested or implemented AI to facilitate SDM.MethodsWe performed a scoping review informed by the methodological framework proposed by Levac et al, modifications to the original Arksey and O'Malley framework of a scoping review, and the Joanna Briggs Institute scoping review framework. We reported our results based on the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) reporting guideline. At the identification stage, an information specialist performed a comprehensive search of 6 electronic databases from their inception to May 2021. The inclusion criteria were: all populations; all AI interventions that were used to facilitate SDM, and if the AI intervention was not used for the decision-making point in SDM, it was excluded; any outcome related to patients, health care providers, or health care systems; studies in any health care setting, only studies published in the English language, and all study types. Overall, 2 reviewers independently performed the study selection process and extracted data. Any disagreements were resolved by a third reviewer. A descriptive analysis was performed.ResultsThe search process yielded 1445 records. After removing duplicates, 894 documents were screened, and 6 peer-reviewed publications met our inclusion criteria. Overall, 2 of them were conducted in North America, 2 in Europe, 1 in Australia, and 1 in Asia. Most articles were published after 2017. Overall, 3 articles focused on primary care, and 3 articles focused on secondary care. All studies used machine learning methods. Moreover, 3 articles included health care providers in the validation stage of the AI intervention, and 1 article included both health care providers and patients in clinical validation, but none of the articles included health care providers or patients in the design and development of the AI intervention. All used AI to support SDM by providing clinical recommendations or predictions.ConclusionsEvidence of the use of AI in SDM is in its infancy. We found AI supporting SDM in similar ways across the included articles. We observed a lack of emphasis on patients' values and preferences, as well as poor reporting of AI interventions, resulting in a lack of clarity about different aspects. Little effort was made to address the topics of explainability of AI interventions and to include end-users in the design and development of the interventions. Further efforts are required to strengthen and standardize the use of AI in different steps of SDM and to evaluate its impact on various decisions, populations, and settings.

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.

Dataset Information

"I Will Respect the Autonomy of My Patient": A Scoping Review of Shared Decision Making in Multiple Sclerosis.

Background

Methods

Results

Conclusions

Publications

"I Will Respect the Autonomy of My Patient": A Scoping Review of Shared Decision Making in Multiple Sclerosis.

Similar Datasets

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