Dataset Information

An Informatics Approach to Implement Support for Shared Decision Making for Primary Prevention Statin Therapy.

ABSTRACT: Background. Shared decision making (SDM) is recommended prior to initiation of statin therapy for primary prevention but is underutilized. We designed an informatics decision-support tool to facilitate use of the Mayo Clinic Statin Choice decision aid at the point-of-care and evaluated its impact. Methods. Using an iterative approach, we designed and implemented a single-click decision-support tool embedded within the electronic health records (EHRs) to automate the calculation of 10-year atherosclerotic cardiovascular disease (ASCVD) risk and populate the Statin Choice decision aid. We surveyed primary care providers at two clinics regarding their attitudes about SDM before and after deployment of intervention, as well as their usage of and perceived competence regarding SDM for primary prevention statin therapy. Three-month web traffic to the Statin Choice website was calculated before and after deployment of the intervention. Results. Pre-post surveys were completed by 60 primary care providers (24 [40%] attending physicians and 36 [60%] housestaff physicians). After deployment of the EHR tool, respondents were more aware of the Statin Choice decision aid (P < 0.001), reported being more competent regarding SDM (P = 0.047), and reported using decision aids more often when considering statin initiation (P = 0.043). There was no significant change in attitudes about SDM as measured through the Patient Provider Orientation Scale (pre 4.23 ± 0.40 v. post 4.16 ± 0.38, P = 0.11) and the SDM belief scale (pre 21.4 ± 2.1 v. post 21.1 ± 2.0, P = 0.35). Web-based usage rates for the Statin Choice decision aid increased from 3.4 to 5.2 per 1,000 outpatient clinic visits (P = 0.002). Conclusions. Implementation of a point-of-care decision-support tool increased the usage of decision aids for primary prevention statin therapy. This effect does not appear to be mediated by any concomitant changes in physician attitude toward SDM.

SUBMITTER: Ye S

PROVIDER: S-EPMC6157431 | biostudies-literature | 2018 Jan-Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

An Informatics Approach to Implement Support for Shared Decision Making for Primary Prevention Statin Therapy.

Ye Siqin S Leppin Aaron L AL Chan Amy Y AY Chang Nancy N Moise Nathalie N Poghosyan Lusine L Montori Victor M VM Kronish Ian I

MDM policy & practice 20180101 1

<b>Background.</b> Shared decision making (SDM) is recommended prior to initiation of statin therapy for primary prevention but is underutilized. We designed an informatics decision-support tool to facilitate use of the Mayo Clinic Statin Choice decision aid at the point-of-care and evaluated its impact. <b>Methods.</b> Using an iterative approach, we designed and implemented a single-click decision-support tool embedded within the electronic health records (EHRs) to automate the calculation of ...[more]

PMID: 30288449

Similar Datasets

Project description:BackgroundThe Dutch multidisciplinary sciatica guideline recommends that the team of professionals involved in sciatica care and the patient together decide on surgical or prolonged conservative treatment (shared decision making [SDM]). Despite this recommendation, SDM is not yet integrated in sciatica care. Existing literature concerning barriers and facilitators to SDM implementation mainly focuses on one discipline only, whereas multidisciplinary care may involve other barriers and facilitators, or make these more complex for both professionals and patients. Therefore, this qualitative study aims to identify barriers and facilitators perceived by patients and professionals for SDM implementation in multidisciplinary sciatica care.MethodsWe conducted 40 semi-structured interviews with professionals involved in sciatica care (general practitioners, physical therapists, neurologists, neurosurgeons, and orthopedic surgeons) and three focus groups among patients (six to eight per group). The interviews and focus groups were audiotaped and transcribed in full. Reported barriers and facilitators were classified according to the framework of Grol and Wensing. The software package Atlas.ti 7.0 was used for analysis.ResultsProfessionals reported 53 barriers and 5 facilitators, and patients 35 barriers and 18 facilitators for SDM in sciatica care. Professionals perceived most barriers at the level of the organizational context, and facilitators at the level of the individual professional. Patients reported most barriers and facilitators at the level of the individual professional. Several barriers and facilitators correspond with barriers and facilitators found in the literature (e.g., lack of time, motivation) but also new barriers and facilitators were identified. Many of these new barriers mentioned by both professionals and patients were related to the multidisciplinary setting, such as lack of visibility, lack of trust in expertise of other disciplines, and lack of communication between disciplines.ConclusionsThis study identified barriers and facilitators for SDM in the multidisciplinary sciatica setting, by both professionals and patients. It is clear that more barriers than facilitators are perceived for implementation of SDM in sciatica care. Newly identified barriers and facilitators are related to the multidisciplinary care setting. Therefore, an effective implementation strategy of SDM in a multidisciplinary setting such as in sciatica care should focus on these barriers and facilitators.

Project description:BackgroundThere is a critical need to improve support for families making difficult shared decisions about patient care with clinicians in the neuroscience ICU (neuro-ICU). The aim of this study is to identify patient- and family-related factors associated with dissatisfaction with shared decision-making support among families of neuro-critically ill patients.MethodsWe conducted a retrospective observational cohort study using survey data that had been collected from a consecutive sample of family members of patients in the neuro-ICU (one family member per patient) at two US academic centers. Satisfaction with shared decision-making support on ICU discharge had been measured among family members using one specific Likert scale item on the Family Satisfaction in the ICU 24 survey, a validated survey instrument for families of patients in the ICU. We dichotomized top-box responses for this particular item as an outcome variable and identified available patient- and family-related covariates associated with dissatisfaction (i.e., less than complete satisfaction) via univariate and multivariate analyses.ResultsAmong 355 surveys, 180 (49.5%) of the surveys indicated dissatisfaction with support during decision-making. In a multivariate model, no preexisting characteristics of families or patients ascertainable on ICU admission were predictive of dissatisfaction. However, among family factors determined during the ICU course, experiencing three or fewer formal family meetings (odds ratio 1.93 [confidence interval 1.13-3.31]; p = 0.01) was significantly predictive of dissatisfaction with decisional support in this cohort with an average patient length of stay of 8.6 days (SD 8.4). There was also a trend toward a family's decision to keep a patient as full code, without treatment limitations, being predictive of dissatisfaction (odds ratio 1.80 [confidence interval 0.93-3.51]; p = 0.08).ConclusionsFamily dissatisfaction with neuro-ICU shared decision-making support is not necessarily predicted by any preexisting family or patient variables but appears to correlate with participating in fewer formal family meetings during ICU admission. Future studies to improve family satisfaction with neurocritical care decision-making support should have broad inclusion criteria for participants and should consider promoting frequency of family meetings as a core strategy.

Project description:ObjectivePatient values and preferences are an important component to decision making when tradeoffs exist that impact quality of life, such as tradeoffs between stroke prevention and hemorrhage in patients with atrial fibrillation (AF) contemplating anticoagulant therapy. Our objective is to describe the development of an Atrial Fibrillation Guideline Support Tool (AFGuST) to assist the process of integrating patients' preferences into this decision.Materials and methodsCHA2DS2VASc and HAS-BLED were used to calculate risks for stroke and hemorrhage. We developed a Markov decision analytic model as a computational engine to integrate patient-specific risk for stroke and hemorrhage and individual patient values for relevant outcomes in decisions about anticoagulant therapy.ResultsIndividual patient preferences for health-related outcomes may have greater or lesser impact on the choice of optimal antithrombotic therapy, depending upon the balance of patient-specific risks for ischemic stroke and major bleeding. These factors have been incorporated into patient-tailored booklets which, along with an informational video, were developed through an iterative process with clinicians and patient focus groups.Key limitationsCurrent risk prediction models for hemorrhage, such as the HAS-BLED, used in the AFGuST, do not incorporate all potentially significant risk factors. Novel oral anticoagulant agents recently approved for use in the United States, Canada, and Europe have not been included in the AFGuST. Rather, warfarin has been used as a conservative proxy for all oral anticoagulant therapy.ConclusionsWe present a proof of concept that a patient-tailored decision-support tool could bridge the gap between guidelines and practice by incorporating individual patient's stroke and bleeding risks and their values for major bleeding events and stroke to facilitate a shared decision making process. If effective, the AFGuST could be used as an adjunct to published guidelines to enhance patient-centered conversations about the anticoagulation management.

Dataset Information

An Informatics Approach to Implement Support for Shared Decision Making for Primary Prevention Statin Therapy.

Publications

An Informatics Approach to Implement Support for Shared Decision Making for Primary Prevention Statin Therapy.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets