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Comparing traditional and participatory dissemination of a shared decision making intervention (ADAPT-NC): a cluster randomized trial.

ABSTRACT: Asthma is a common disease that affects people of all ages and has significant morbidity and mortality. Poor outcomes and health disparities related to asthma result in part from the difficulty of disseminating new evidence and care delivery methods such as shared decision making (SDM) into clinical practice.This non-blinded study will randomize 30 primary care clinics in NC stratified by four PBRNs. We will test dissemination across these practices using a facilitator-led participatory approach to dissemination (FLOW), a novel method of participatory dissemination involving key principles of community-based participatory research, and a more typical "lunch and learn" dissemination method. Specifically, we will use cluster randomization to assign each of the 30 practices to one of three arms: (1) control, no dissemination; (2) traditional dissemination, one didactic session a year and distribution of educational material; and (3) FLOW dissemination. We hypothesize that at the unit of randomization, the clinic, patients in the FLOW dissemination arm will be more likely to share in their treatment decisions compared to patients in the traditional dissemination or control arms. All outcomes will be measured at the level of the clinic. Adoption of the SDM approach will be evaluated by 1) asthma exacerbations, 2) level of patient involvement in the decision making process, and 3) qualitative assessments from patients and providers.The trial was registered on January 27, 2014 through the United States National Institutes of Health's ClinicalTrials.gov NCT02047929 and funded by the Patient-Centered Outcomes Research Institute (PCORI).

SUBMITTER: Tapp H

PROVIDER: S-EPMC4219101 | biostudies-literature | 2014 Oct

REPOSITORIES: biostudies-literature

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Comparing traditional and participatory dissemination of a shared decision making intervention (ADAPT-NC): a cluster randomized trial.

Tapp Hazel H McWilliams Andrew A Ludden Thomas T Kuhn Lindsay L Taylor Yhenneko Y Alkhazraji Thamara T Halladay Jacquie J Derkowski Diane D Mohanan Sveta S Dulin Michael M

Implementation science : IS 20141029

<h4>Background</h4>Asthma is a common disease that affects people of all ages and has significant morbidity and mortality. Poor outcomes and health disparities related to asthma result in part from the difficulty of disseminating new evidence and care delivery methods such as shared decision making (SDM) into clinical practice.<h4>Methods/design</h4>This non-blinded study will randomize 30 primary care clinics in NC stratified by four PBRNs. We will test dissemination across these practices usin ...[more]

PMID: 25359128

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Project description:IMPORTANCE:For antidepressants, the translation of evidence of comparative effectiveness into practice is suboptimal. This deficit directly affects outcomes and quality of care for patients with depression. To overcome this problem, we developed the Depression Medication Choice (DMC) encounter decision aid, designed to help patients and clinicians consider the available antidepressants and the extent to which they improved depression and other issues important to patients. OBJECTIVE:Estimate the effect of DMC on quality of the decision-making process and depression outcomes. DESIGN, SETTING, AND PARTICIPANTS:We conducted a cluster randomized trial of adults with moderate to severe depression considering treatment with an antidepressant. Primary care practices in 10 rural, suburban, and urban primary care practices across Minnesota and Wisconsin were randomly allocated to treatment of depression with or without use of the DMC decision aid. INTERVENTION:Depression Medication Choice, a series of cards, each highlighting the effect of the available options on an issue of importance to patients for use during face-to-face consultations. MAIN OUTCOMES AND MEASURES:Decision-making quality as judged by patient knowledge and involvement in decision making, patient and clinician decisional comfort (Decisional Conflict Scale) and satisfaction, encounter duration, medication adherence, depression symptoms, and the Patient Health Questionnaire for depression (PHQ-9). RESULTS:We enrolled 117 clinicians and 301 patients (67% women; mean [SD] age, 44 [15] years; mean [SD] PHQ-9 score, 15 [4]) into the trial. Compared with usual care (UC), use of DMC significantly improved patients' decisional comfort (DMC, 80% vs UC, 75%; P = .02), knowledge (DMC, 65% vs UC, 56%; P =?.03), satisfaction (risk ratio [RR], from 1.25 [P =?.81] to RR, 2.4 [P =?.002] depending on satisfaction domain), and involvement (DMC, 47% vs UC, 33%; P<.001). It also improved clinicians' decisional comfort (DMC, 80% vs UC, 68%; P <?.001) and satisfaction (RR, 1.64; P =?.02). There were no differences in encounter duration, medication adherence, or improvement of depression control between arms. CONCLUSIONS AND RELEVANCE:The DMC decision aid helped primary care clinicians and patients with moderate to severe depression select antidepressants together, improving the decision-making process without extending the visit. On the other hand, DMC had no discernible effect on medication adherence or depression outcomes. By translating comparative effectiveness into patient-centered care, use of DMC improved the quality of primary care for patients with depression. TRIAL REGISTRATION:clinicaltrials.gov Identifier: NCT01502891.

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:BackgroundInnovative interventions are needed to address gaps in preventive cancer care, especially in rural areas. This study evaluated the impact of clinical decision support (CDS) with and without shared decision making (SDM) on cancer-screening completion.MethodsIn this 3-arm, parallel-group, cluster-randomized trial conducted at a predominantly rural medical group, 34 primary care clinics were randomized to clinical decision support (CDS), CDS plus shared decision making (CDS+SDM), or usual care (UC). The CDS applied web-based clinical algorithms identifying patients overdue for United States Preventive Services Task Force-recommended preventive cancer care and presented evidence-based recommendations to patients and providers on printouts and on the electronic health record interface. Patients in the CDS+SDM clinic also received shared decision-making tools (SDMTs). The primary outcome was a composite indicator of the proportion of patients overdue for breast, cervical, or colorectal cancer screening at index who were up to date on these 1 y later.ResultsFrom August 1, 2018, to March 15, 2019, 69,405 patients aged 21 to 74 y had visits at study clinics and 25,198 were overdue for 1 or more cancer screening tests at an index visit. At 12-mo follow-up, 9,543 of these (37.9%) were up to date on the composite endpoint. The adjusted, model-derived percentage of patients up to date was 36.5% (95% confidence interval [CI]: 34.0-39.1) in the UC group, 38.1% (95% CI: 35.5-40.9) in the CDS group, and 34.4% (95% CI: 31.8-37.2) in the CDS+SDM group. For all comparisons, the screening rates were higher than UC in the CDS group and lower than UC in the CDS+SDM group, although these differences did not reach statistical significance.ConclusionThe CDS did not significantly increase cancer-screening rates. Exploratory analyses suggest a deeper understanding of how SDM and CDS interact to affect cancer prevention decisions is needed. Trial registration: ClinicalTrials.gov ID: NCT02986230, December 6, 2016.

Project description:BackgroundShared decision-making (SDM) is a model of interaction between doctors and patients in which both actors contribute to the medical decision-making process. SDM has raised great interest in mental healthcare over the last decade, as it is considered a fundamental part of patient-centered care. However, there is no research evaluating the efficacy of SDM compared to usual care (CAU), as it relates to quality of care and more specifically treatment adherence, in bipolar disorder (BD).Methods/designThis is a 12-month multi-centre, cluster-randomized controlled trial comparing the efficacy of SDM to CAU. Adult BD patients (n = 300) will be eligible after stabilization for at least 4 weeks following an acute mood episode. The intervention will consist of applying the standardized SDM process as developed by the Ottawa Hospital Research Institute in order to choose the maintenance treatment of BD. A multidisciplinary team developed a decision aid "choose my long-term treatment with my doctor" for BD patients to clarify possible therapeutic options. Primary outcome will assess the patient's level of adherence (based on hetero-evaluation) of ongoing treatment at 12 months. Secondary outcomes will assess the difference between the 2 groups of patients in terms of adherence to maintenance drug therapy based on other measures (self-assessment scale and plasma levels of mood stabilizers). Additionally, other dimensions will be assessed: decisional conflict, satisfaction with care and involvement in decision making, beliefs about treatment, therapeutic relationship, knowledge about information for medical decision and clinical outcomes (depression, mania, functioning and quality of life). The primary endpoint will be analysed without adjustment by comparison of adherence scores between the two groups using Student t-tests or Mann-Whitney tests according to the variable distribution. A set of secondary analyses will be adjusted for covariates of clinical interest using generalized linear mixed regression models.DiscussionThis will be the first study evaluating the effect of an SDM intervention on patient adherence in BD. This is also an innovative protocol because it proposes the development of an evidence-based tool that should help patients and clinicians to initiate discussions regarding the use of BD treatment.Trial registrationThe study has been registered with ClinicalTrials.gov as NCT03245593 .

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.

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Comparing traditional and participatory dissemination of a shared decision making intervention (ADAPT-NC): a cluster randomized trial.

Publications

Comparing traditional and participatory dissemination of a shared decision making intervention (ADAPT-NC): a cluster randomized trial.

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