Dataset Information

Improvement of shared decision making in integrated stroke care: a before and after evaluation using a questionnaire survey.

ABSTRACT: BACKGROUND:Shared decision making (SDM) is at the core of policy measures for making healthcare person-centred. However, the context-sensitive nature of the challenges in integrated stroke care calls for research to facilitate its implementation. This before and after evaluation study identifies factors for implementation and concludes with key recommendations for adoption. METHODS:Data were collected at the start and end of an implementation programme in five stroke services (December 2017 to July 2018). The SDM implementation programme consisted of training for healthcare professionals (HCPs), tailored support, development of decision aids and a social map of local stroke care. Participating HCPs were included in the evaluation study: A questionnaire was sent to 25 HCPs at baseline, followed by 11 in-depth interviews. Data analysis was based on theoretical models for implementation and 51 statements were formulated as a result. Finally, all HCPs were asked to validate and to quantify these statements and to formulate recommendations for further adoption. RESULTS:The majority of respondents said that training of all HCPs is essential. Feedback on consultation and peer observation are considered to help improve performance. In addition, HCPs stated that SDM should also be embedded in multidisciplinary meetings, whereas implementation in the organisation could be facilitated by appointed ambassadors. Time was not seen as an inhibiting factor. According to HCPs, negotiating patients' treatment decisions improves adherence to therapy. Despite possible cognitive or communications issues, all are convinced patients with stroke can be involved in a SDM-process. Relatives play an important role too in the further adoption of SDM. HCPs provided eight recommendations for adoption of SDM in integrated stroke care. CONCLUSIONS:HCPs in our study indicated it is feasible to implement SDM in integrated stroke care and several well-known implementation activities could improve SDM in stroke care. Special attention should be given to the following activities: (1) the appointment of knowledge brokers, (2) agreements between HCPs on roles and responsibilities for specific decision points in the integrated stroke care chain and (3) the timely investigation of patient's preferences in the care process - preferably before starting treatment through discussions in a multidisciplinary meeting.

SUBMITTER: Voogdt-Pruis HR

PROVIDER: S-EPMC6896582 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Improvement of shared decision making in integrated stroke care: a before and after evaluation using a questionnaire survey.

Voogdt-Pruis H R HR Ras T T van der Dussen L L Benjaminsen S S Goossens P H PH Raats I I Boss G G van Hoef E F M EFM Lindhout M M Tjon-A-Tsien M R S MRS Vrijhoef H J M HJM

BMC health services research 20191205 1

<h4>Background</h4>Shared decision making (SDM) is at the core of policy measures for making healthcare person-centred. However, the context-sensitive nature of the challenges in integrated stroke care calls for research to facilitate its implementation. This before and after evaluation study identifies factors for implementation and concludes with key recommendations for adoption.<h4>Methods</h4>Data were collected at the start and end of an implementation programme in five stroke services (Dec ...[more]

PMID: 31805927

Similar Datasets

Project description:PURPOSE:The SDM-Q-9 and SDM-Q-Doc measure patient and physician perception of the extent of shared decision making (SDM) during a physician-patient consultation. So far, no self-report instrument for SDM was available in Dutch, and validation of the scales in other languages has been limited. The aim of this study was to translate both scales into Dutch and assess their psychometric characteristics. METHODS:Participants were patients and their treating physicians (general practitioners and medical specialists). Patients (N = 182) rated their consultation using the SDM-Q-9, 43 physicians rated their consultations using the SDM-Q-Doc (N = 201). Acceptability, reliability (internal consistency), and the factorial structure of the instruments were determined. For convergent validity the CPSpost was used. RESULTS:Reliabilities of both scales were high (alpha SDM-Q-9 0.88; SDM-Q-Doc 0.87). The SDM-Q-9 and SDM-Q-Doc total scores correlated as expected with the CPSpost (SDM-Q-9: r = 0.29; SDM-Q-Doc: r = 0.48) and were significantly different between the CPSpost categories, with lowest mean scores when the physician made the decision alone. Principal Component Analyses showed a two-component model for each scale. A confirmatory factor analysis yielded a mediocre, but acceptable, one-factor model, if Item 1 was excluded; for both scales the best indices of fit were obtained for a one-factor solution, if both Items 1 and 9 were excluded. CONCLUSION:The Dutch SDM-Q-9 and SDM-Q-Doc demonstrate good acceptance and reliability; they correlated as expected with the CPSpost and are suitable for use in Dutch primary and specialised care. Although the best model fit was found when excluding Items 1 and 9, we believe these items address important aspects of SDM. Therefore, also based on the coherence with theory and comparability with other studies, we suggest keeping all nine items of the scale. Further research on the SDM-concept in patients and physicians, in different clinical settings and different countries, is necessary to gain a better understanding of the SDM-construct and its measurement.

Project description:BackgroundGoal attainment of guideline-recommended low-density lipoprotein cholesterol (LDL-C) is suboptimal. Little is known about how patient factors influence physicians' treatment decision-making in hypercholesterolemia. We examined physicians' treatment recommendations in high-risk patients whose LDL-C remained uncontrolled despite statin monotherapy.MethodsPhysicians completed a questionnaire prior to randomization into period I of a two-period randomized controlled trial evaluating LDL-C goal attainment in patients whose LDL-C remained ≥100 mg/dL after 5 weeks' treatment with atorvastatin 10 mg/day (NCT01154036). Physicians' treatment recommendations were surveyed for two hypothetical and one real scenario: (1) LDL-C presumed near goal (between 100-105 mg/dL), (2) LDL-C presumed far from goal (~120 mg/dL), and (3) observed baseline LDL-C of enrolled patients. Prognostic factors considered during decision-making were identified by regression analysis. Observed lipid outcomes at the end of period I (following 6 weeks' treatment with ezetimibe 10 mg plus atorvastatin 10 mg, atorvastatin 20 mg, or rosuvastatin 10 mg) were compared with estimated LDL-C outcomes for physicians' treatment recommendations after 6 weeks (based on individual patients' pre-randomization LDL-C and expected incremental change).ResultsQuestionnaires were completed for 1,534 patients. No change in therapy, or double atorvastatin dose, were frequently recommended, even when LDL-C was far from goal (6.5% and 52.2% of patients, respectively). Double atorvastatin dose was commonly recommended in all scenarios (43-52% of patients). More intensive LDL-C-lowering regimens were recommended infrequently e.g. double atorvastatin dose and add ezetimibe only <12% in all scenarios. Overall, cardiovascular risk factors and desire to achieve a more aggressive LDL-C goal were prominent factors in decision-making for treatment. Comparison of observed and estimated LDL-C levels showed that physicians tended to overestimate the effectiveness of their recommendations.ConclusionsThis study provides insight into physicians' perspectives on clinical management of hypercholesterolemia and highlights a gap in knowledge translation from guidelines to clinical practice. The need for lower LDL-C and cardiovascular risk were key drivers in clinical decision-making, but physicians' treatment choices were more conservative than guideline recommendations, potentially resulting in poorer LDL-C reduction. When compared with actual outcomes, projected LDL-C control was better if physicians used more comprehensive strategies rather than simply doubling the statin dose.Trial registrationClinicaltrials.gov: NCT01154036.

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 Oral anticoagulation reduces stroke and disability in atrial fibrillation (AF) but is underused. We evaluated the effects of a novel patient-clinician shared decision-making (SDM) tool in reducing oral anticoagulation patient's decisional conflict as compared with usual care. Methods and Results We designed and evaluated a new digital decision aid in a multicenter, randomized, comparative effectiveness trial, ENHANCE-AF (Engaging Patients to Help Achieve Increased Patient Choice and Engagement for AF Stroke Prevention). The digital AF shared decision-making toolkit was developed using patient-centered design with clear health communication principles (eg, meaningful images, limited text). Available in English and Spanish, the toolkit included the following: (1) a brief animated video; (2) interactive questions with answers; (3) a quiz to check on understanding; (4) a worksheet to be used by the patient during the encounter; and (5) an online guide for clinicians. The study population included English or Spanish speakers with nonvalvular AF and a CHA2DS2-VASc stroke score ≥1 for men or ≥2 for women. Participants were randomized in a 1:1 ratio to either usual care or the shared decision-making toolkit. The primary end point was the validated 16-item Decision Conflict Scale at 1 month. Secondary outcomes included Decision Conflict Scale at 6 months and the 10-item Decision Regret Scale at 1 and 6 months as well as a weighted average of Mann-Whitney U-statistics for both the Decision Conflict Scale and the Decision Regret Scale. A total of 1001 participants were enrolled and followed at 5 different sites in the United States between December 18, 2019, and August 17, 2022. The mean patient age was 69±10 years (40% women, 16.9% Black, 4.5% Hispanic, 3.6% Asian), and 50% of participants had CHA2DS2-VASc scores ≥3 (men) or ≥4 (women). The primary end point at 1 month showed a clinically meaningful reduction in decisional conflict: a 7-point difference in median scores between the 2 arms (16.4 versus 9.4; Mann-Whitney U-statistics=0.550; P=0.007). For the secondary end point of 1-month Decision Regret Scale, the difference in median scores between arms was 5 points in the direction of less decisional regret (P=0.078). The treatment effects lessened over time: at 6 months the difference in medians was 4.7 points for Decision Conflict Scale (P=0.060) and 0 points for Decision Regret Scale (P=0.35). Conclusions Implementation of a novel shared decision-making toolkit (afibguide.com; afibguide.com/clinician) achieved significantly lower decisional conflict compared with usual care in patients with AF. Registration URL: https://www.clinicaltrials.gov; Unique identifier: NCT04096781.

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.

Project description:IntroductionDecision aids (DAs) are helpful instruments used to support shared decision making (SDM). Patients with atrial fibrillation (AF) face complex decisions regarding stroke prevention strategies. While a few DAs have been made for AF stroke prevention, an encounter DA (EDA) and patient DA (PDA) have not been created to be used in conjunction with each other before.DesignUsing iterative user-centered design, we developed 2 DAs for anticoagulation choice and stroke prevention in AF. Prototypes were created, and we elicited feedback from patients and experts via observations of encounters, usability testing, and semistructured interviews.ResultsUser testing was done with 33 experts (in AF and SDM) and 51 patients from 6 institutions. The EDA and PDA underwent 1 and 4 major iterations, respectively. Major differences between the DAs included AF pathophysiology and a preparation to meet with the clinician in the PDA as well as different language throughout. Content areas included personalized stroke risk, differences between anticoagulants, and risks of bleeding. Based on user feedback, developers 1) addressed feelings of isolation with AF, 2) improved navigation options, 3) modified content and flow for users new to AF and those experienced with AF, 4) updated stroke risk pictographs, and 5) added structure to the preparation for decision making in the PDA.LimitationsThese DAs focus only on anticoagulation for stroke prevention and are online, which may limit participation for those less comfortable with technology.ConclusionsDesigning complementary DAs for use in tandem or separately is a new method to support SDM between patients and clinicians. Extensive user testing is essential to creating high-quality tools that best meet the needs of those using them.HighlightsFirst-time complementary encounter and patient decision aids have been designed to work together or separately.User feedback led to greater structure and different experiences for patients naïve or experienced with anticoagulants in patient decision aids.Online tools allow for easier dissemination, use in telehealth visits, and updating as new evidence comes out.

Dataset Information

Improvement of shared decision making in integrated stroke care: a before and after evaluation using a questionnaire survey.

Publications

Improvement of shared decision making in integrated stroke care: a before and after evaluation using a questionnaire survey.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets