Shared Decision Making in Gastroenterology: Challenges and Opportunities.
Ontology highlight
ABSTRACT:
SUBMITTER: Fox JC
PROVIDER: S-EPMC7139984 | biostudies-literature | 2020 Apr
REPOSITORIES: biostudies-literature
Publications
Shared Decision Making in Gastroenterology: Challenges and Opportunities.
Fox Jean C JC Lipstein Ellen A EA
Mayo Clinic proceedings. Innovations, quality & outcomes 20200309 2
This article reviews the current uses of shared decision making in gastroenterology and discusses additional areas of opportunity for shared decision making, especially in the area of functional gastrointestinal disorders. PubMed, MEDLINE, and Cochrane library databases were searched for articles published during a 10-year period from January 1, 2007, through December 31, 2017. Search terms included <i>shared decision making and gastroenterology</i>, <i>shared decision making in gastrointestinal ...[more]
Similar Datasets
Project description:Shared decision-making has become a new focus of health policy. Though its core elements are largely agreed upon, there is little consensus regarding which outcomes to prioritize for policy-mandated shared decision-making.
| S-EPMC9060309 | biostudies-literature
Project description:BACKGROUND:Shared decision-making (SDM) improves patient engagement and may improve outpatient health outcomes. Little is known about inpatient SDM. OBJECTIVE:To assess overall quality, provider behaviors, and contextual predictors of SDM during inpatient rounds on medicine and pediatrics hospitalist services. DESIGN:A 12-week, cross-sectional, single-blinded observational study of team SDM behaviors during rounds, followed by semistructured patient interviews. SETTING:Two large quaternary care academic medical centers. PARTICIPANTS:Thirty-five inpatient teams (18 medicine, 17 pediatrics) and 254 unique patient encounters (117 medicine, 137 pediatrics). INTERVENTION:Observational study. MEASUREMENTS:We used a 9-item Rochester Participatory Decision-Making Scale (RPAD) measured team-level SDM behaviors. Same-day interviews using a modified RPAD assessed patient perceptions of SDM. RESULTS:Characteristics associated with increased SDM in the multivariate analysis included the following: service, patient gender, timing of rounds during patient's hospital stay, and amount of time rounding per patient (P < .05). The most frequently observed behaviors across all services included explaining the clinical issue and matching medical language to the patient's level of understanding. The least frequently observed behaviors included checking understanding of the patient's point of view, examining barriers to follow-through, and asking if the patient has any questions. Patients and guardians had substantially higher ratings for SDM quality compared to peer observers (7.2 vs 4.4 out of 9). CONCLUSIONS:Important opportunities exist to improve inpatient SDM. Team size, number of learners, patient census, and type of decision being made did not affect SDM, suggesting that even large, busy services can perform SDM if properly trained.
| S-EPMC6392000 | biostudies-literature
Project description:Characterizing population variability, including identifying susceptible populations and quantifying their increased susceptibility, is an important aspect of chemical risk assessment, but one that is challenging with traditional experimental models and risk assessment methods. New models and methods to address population variability can be used to advance the human health assessments of chemicals in three key areas. First, with respect to hazard identification, evaluating toxicity using population-based in vitro and in vivo models can potentially reduce both false positive and false negative signals. Second, with respect to evaluating mechanisms of toxicity, enhanced ability to do genetic mapping using these models allows for the identification of key biological pathways and mechanisms that may be involved in toxicity and/or susceptibility. Third, with respect to dose-response assessment, population-based toxicity data can serve as a surrogate for human variability, and thus be used to quantitatively estimate the degree of human toxicokinetic/toxicodynamic variability and thereby increase confidence in setting health-protective exposure limits. A number of case studies have been published that demonstrate the potential opportunities for improving risk assessment and decision-making, and include studies using Collaborative Cross and Diversity Outbred mice, as well as populations of human cell lines from the 1000 Genomes project. Key challenges include the need to apply more sophisticated computational and statistical models analyzing population-based toxicity data, and the need to integrate these more complex analyses into risk assessments and decision-making.
| S-EPMC5849521 | biostudies-literature
Project description:ObjectivesIn 2020, Canada spent 12.9 percent of its GDP on healthcare, of which 3 percent was on medical devices. Early adoption of innovative surgical devices is mostly driven by physicians and delaying adoption can deprive patients of important medical treatments. This study aimed to identify the criteria in Canada used to decide on the adoption of a surgical device and identify challenges and opportunities.MethodsThis scoping review was guided by the Joanna Briggs Institute Manual for Evidence Synthesis and PRISMA-ScR reporting guidelines. The search strategy included Canada's provinces, different surgical fields, and adoption. Embase, Medline, and provincial databases were searched. Grey literature was also searched. Data were analyzed by reporting the criteria that were used for technology adoption. Finally, a thematic analysis by subthematic categorization was conducted to arrange the criteria found.ResultsOverall, 155 studies were found. Seven were hospital-specific studies and 148 studies were from four provinces with publicly available Web sites for technology assessment committees (Alberta, British Columbia, Ontario, and Quebec). Seven main themes of criteria were identified: economic, hospital-specific, technology-specific, patients/public, clinical outcomes, policies and procedures, and physician specific. However, standardization and specific weighted criteria for decision making in the early adoption stage of novel technologies are lacking in Canada.ConclusionsSpecific criteria for decision making in the early adoption stage of novel surgical technologies are lacking. These criteria need to be identified, standardized, and applied in order to provide innovative, and the most effective healthcare to Canadians.
| S-EPMC11569962 | biostudies-literature
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.
| S-EPMC7018920 | biostudies-literature
Project description:BackgroundShared decision making (SDM) is a health communication model promoting patient-centered care that has not been routinely utilized in mental health. Inconsistent definitions, models, measurement tools, and lack of sufficient evidence for the effectiveness of SDM interventions are potential contributors to the limited use of SDM in mental health.Aims(1) Provide the first systematic analysis of global development trends and challenges of SDM research; (2) clarify the meaning, role, and measurement of SDM in mental health; (3) create a theoretical framework for key effective SDM components to guide future development and implementation of SDM interventions.MethodsA comprehensive search strategy was conducted in CINAHL, PubMed, Scopus, MEDLINE, EMBASE, Cochrane Library, Web of Science, Scopus, and PsycInfo. Included reviews focused on SDM interventions for prevention and/or treatment of mental illness in adults. A narrative synthesis was performed to capture the range of interventions, populations, measurement tools, comparisons, and outcomes.Results10 systematic reviews of SDM in mental health were included with 100 nested studies spanning from 2006 to 2020. All reviews focused on dyadic and psychopharmacological decision-making. Primary outcomes of SDM in mental health interventions include treatment satisfaction, medication adherence, symptom severity, quality of life, and hospital readmissions. Participant-related factors unique to SDM in mental health, such as stigma and mental capacity, were not reported.ConclusionsThe current landscape of SDM in mental health is overwhelmingly disconnected from the needs and experiences of potential end-users; clients, clinicians, and family members. Most SDM interventions and tools were adapted from physical health and are mainly geared to psychopharmacological decision-making. The SDM in Mental Health Framework (SDM-MH), developed here, expands the scope of decisions to non-psychopharmacological discussions, diversifies the pool of SDM participants and settings, and offers potential primary target outcomes of SDM in mental health to reduce heterogeneity across studies.
| S-EPMC10240653 | biostudies-literature
Project description:ObjectiveThe objective of this study is to determine the factors influencing pancreatic surgery patients' perceptions of the shared decision-making process (SDM).BackgroundDecision-making in pancreatic surgery is complicated by the risk of morbidity and mortality and risk of early recurrence of disease. Improvement in SDM has the potential to improve the receipt of goal- and value-concordant care.MethodsThis cross-sectional survey included patients who underwent pancreatic surgery. The following components were studied in relation to SDM: modified satisfaction with decision scale (SWD), modified decisional regret scale (DRS), quality of physician and patient interaction, and the impact of quality of life (FACT-Hep). Correlations were computed using Pearson's correlation score and a regression model.ResultsThe survey completion rate was 72.2% (of 40/55) and the majority (72.5%) of patients underwent pancreaticoduodenectomy. There were significant positive relationships between the SDM measure and (DRS, SWD; r = 0.70, P < 0.001) and responses to questions regarding how well the patient's actual recovery matched their expectations before treatment (r = 0.62, P < 0.001). The quality of the physician-patient relationship correlated with how well recovery matched expectations (r = 0.53, P = 0.002). SDM measure scores were significant predictors of the decision evaluation measure (R2(adj) = 0.48, P < 0.001), FACT-Hep (R2(adj) = 0.15, P < 0.001), and recovery expectations measure (R2(adj) = 0.37, P < 0.001).ConclusionsImproved SDM in pancreatic surgery is associated with more realistic recovery expectations, decreased decisional regret, and improved quality of life.
| S-EPMC10431427 | biostudies-literature
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.
| S-EPMC7676870 | biostudies-literature
Project description:Policymakers and researchers are strongly encouraging clinicians to support patient autonomy through shared decision-making (SDM). In setting policies for clinical care, decision-makers need to understand that current models of SDM have tended to focus on major decisions (e.g., surgeries and chemotherapy) and focused less on everyday primary care decisions. Most decisions in primary care are substantive everyday decisions: intermediate-stakes decisions that occur dozens of times every day, yet are non-trivial for patients, such as whether routine mammography should start at age 40, 45, or 50. Expectations that busy clinicians use current models of SDM (here referred to as "detailed" SDM) for these decisions can feel overwhelming to clinicians. Evidence indicates that detailed SDM is simply not realistic for most of these decisions and without a feasible alternative, clinicians usually default to a decision-making approach with little to no personalization. We propose, for discussion and refinement, a compromise approach to personalizing these decisions (everyday SDM). Everyday SDM is based on a feasible process for supporting patient autonomy that also allows clinicians to continue being respectful health advocates for their patients. We propose that alternatives to detailed SDM are needed to make progress toward more patient-centered care.
| S-EPMC7572954 | biostudies-literature
Project description:ObjectivesTo analyze current practices in shared decision-making (SDM) in primary care and perform a needs assessment for the role of information technology (IT) interventions.Materials and methodsA mixed-methods study was conducted in three phases: (1) ethnographic observation of clinical encounters, (2) patient interviews, and (3) physician interviews. SDM was measured using the validated OPTION scale. Semistructured interviews followed an interview guide (developed by our multidisciplinary team) informed by the Traditional Decision Conflict Scale and Shared Decision Making Questionnaire. Field notes were independently coded and analyzed by two reviewers in Dedoose.ResultsTwenty-four patient encounters were observed in 3 diverse practices with an average OPTION score of 57.2 (0-100 scale; 95% confidence interval [CI], 51.8-62.6). Twenty-two patient and 8 physician interviews were conducted until thematic saturation was achieved. Cohen's kappa, measuring coder agreement, was 0.42. Patient domains were: establishing trust, influence of others, flexibility, frustrations, values, and preferences. Physician domains included frustrations, technology (concerns, existing use, and desires), and decision making (current methods used, challenges, and patients' understanding).DiscussionGiven low SDM observed, multiple opportunities for technology to enhance SDM exist based on specific OPTION items that received lower scores, including: (1) checking the patient's preferred information format, (2) asking the patient's preferred level of involvement in decision making, and (3) providing an opportunity for deferring a decision. Based on data from interviews, patients and physicians value information exchange and are open to technologies that enhance communication of care options.ConclusionFuture primary care IT platforms should prioritize the 3 quantitative gaps identified to improve physician-patient communication and relationships. Additionally, SDM tools should seek to standardize common workflow steps across decisions and focus on barriers to increasing adoption of effective SDM tools into routine primary care.
| S-EPMC6993997 | biostudies-literature