Dataset Information

Randomized controlled trial of a coordinated care intervention to improve risk factor control after stroke or transient ischemic attack in the safety net: Secondary stroke prevention by Uniting Community and Chronic care model teams Early to End Disparities (SUCCEED).

ABSTRACT: Recurrent strokes are preventable through awareness and control of risk factors such as hypertension, and through lifestyle changes such as healthier diets, greater physical activity, and smoking cessation. However, vascular risk factor control is frequently poor among stroke survivors, particularly among socio-economically disadvantaged blacks, Latinos and other people of color. The Chronic Care Model (CCM) is an effective framework for multi-component interventions aimed at improving care processes and outcomes for individuals with chronic disease. In addition, community health workers (CHWs) have played an integral role in reducing health disparities; however, their effectiveness in reducing vascular risk among stroke survivors remains unknown. Our objectives are to develop, test, and assess the economic value of a CCM-based intervention using an Advanced Practice Clinician (APC)-CHW team to improve risk factor control after stroke in an under-resourced, racially/ethnically diverse population.In this single-blind randomized controlled trial, 516 adults (?40 years) with an ischemic stroke, transient ischemic attack or intracerebral hemorrhage within the prior 90 days are being enrolled at five sites within the Los Angeles County safety-net setting and randomized 1:1 to intervention vs usual care. Participants are excluded if they do not speak English, Spanish, Cantonese, Mandarin, or Korean or if they are unable to consent. The intervention includes a minimum of three clinic visits in the healthcare setting, three home visits, and Chronic Disease Self-Management Program group workshops in community venues. The primary outcome is blood pressure (BP) control (systolic BP <130 mmHg) at 1 year. Secondary outcomes include: (1) mean change in systolic BP; (2) control of other vascular risk factors including lipids and hemoglobin A1c, (3) inflammation (C reactive protein [CRP]), (4) medication adherence, (5) lifestyle factors (smoking, diet, and physical activity), (6) estimated relative reduction in risk for recurrent stroke or myocardial infarction (MI), and (7) cost-effectiveness of the intervention versus usual care.If this multi-component interdisciplinary intervention is shown to be effective in improving risk factor control after stroke, it may serve as a model that can be used internationally to reduce race/ethnic and socioeconomic disparities in stroke in resource-constrained settings.ClinicalTrials.gov Identifier NCT01763203 .

SUBMITTER: Towfighi A

PROVIDER: S-EPMC5294765 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Randomized controlled trial of a coordinated care intervention to improve risk factor control after stroke or transient ischemic attack in the safety net: Secondary stroke prevention by Uniting Community and Chronic care model teams Early to End Disparities (SUCCEED).

Towfighi Amytis A Cheng Eric M EM Ayala-Rivera Monica M McCreath Heather H Sanossian Nerses N Dutta Tara T Mehta Bijal B Bryg Robert R Rao Neal N Song Shlee S Razmara Ali A Ramirez Magaly M Sivers-Teixeira Theresa T Tran Jamie J Mojarro-Huang Elizabeth E Montoya Ana A Corrales Marilyn M Martinez Beatrice B Willis Phyllis P Macias Mireya M Ibrahim Nancy N Wu Shinyi S Wacksman Jeremy J Haber Hilary H Richards Adam A Barry Frances F Hill Valerie V Mittman Brian B Cunningham William W Liu Honghu H Ganz David A DA Factor Diane D Vickrey Barbara G BG

BMC neurology 20170206 1

<h4>Background</h4>Recurrent strokes are preventable through awareness and control of risk factors such as hypertension, and through lifestyle changes such as healthier diets, greater physical activity, and smoking cessation. However, vascular risk factor control is frequently poor among stroke survivors, particularly among socio-economically disadvantaged blacks, Latinos and other people of color. The Chronic Care Model (CCM) is an effective framework for multi-component interventions aimed at ...[more]

PMID: 28166784

Similar Datasets

Project description:Importance:The timely delivery of guideline-concordant care may reduce the risk of recurrent vascular events for patients with transient ischemic attack (TIA) and minor stroke. Although many health care organizations measure stroke care quality, few evaluate performance for patients with TIA or minor stroke, and most include only a limited subset of guideline-recommended processes. Objective:To assess the quality of guideline-recommended TIA and minor stroke care across the Veterans Health Administration (VHA) system nationwide. Design, Setting, and Participants:This cohort study included 8201 patients with TIA or minor stroke cared for in any VHA emergency department (ED) or inpatient setting during federal fiscal year 2014 (October 1, 2013, through September 31, 2014). Patients with length of stay longer than 6 days, ventilator use, feeding tube use, coma, intensive care unit stay, inpatient rehabilitation stay before discharge, or receipt of thrombolysis were excluded. Outlier facilities for each process of care were identified by constructing 95% CIs around the facility pass rate and national pass rate sites when the 95% CIs did not overlap. Data analysis occurred from January 16, 2016, through June 30, 2017. Main Outcomes and Measures:Ten elements of care were assessed using validated electronic quality measures. Results:In the 8201 patients included in the study (mean [SD] age, 68.8 [11.4] years; 7877 [96.0%] male; 4856 [59.2%] white), performance varied across elements of care: brain imaging by day 2 (6720/7563 [88.9%]; 95% CI, 88.2%-89.6%), antithrombotic use by day 2 (6265/7477 [83.8%]; 95% CI, 83.0%-84.6%), hemoglobin A1c measurement by discharge or within the preceding 120 days (2859/3464 [82.5%]; 95% CI, 81.2%-83.8%), anticoagulation for atrial fibrillation by day 7 after discharge (1003/1222 [82.1%]; 95% CI, 80.0%-84.2%), deep vein thrombosis prophylaxis by day 2 (3253/4346 [74.9%]; 95% CI, 73.6%-76.2%), hypertension control by day 90 after discharge (4292/5979 [71.8%]; 95% CI, 70.7%-72.9%), neurology consultation by day 1 (5521/7823 [70.6%]; 95% CI, 69.6%-71.6%), electrocardiography by day 2 or within 1 day prior (5073/7570 [67.0%]; 95% CI, 65.9%-68.1%), carotid artery imaging by day 2 or within 6 months prior (4923/7685 [64.1%]; 95% CI, 63.0%-65.2%), and moderate- to high-potency statin prescription by day 7 after discharge (3329/7054 [47.2%]; 95% CI, 46.0%-48.4%). Performance varied substantially across facilities (eg, neurology consultation had a facility outlier rate of 53.0%). Performance was higher for admitted patients than for patients cared for only in EDs with the greatest disparity for carotid artery imaging (4478/5927 [75.6%] vs 445/1758 [25.3%]; P < .001). Conclusions and Relevance:This national study of VHA system quality of care for patients with TIA or minor stroke identified opportunities to improve care quality, particularly for patients who were discharged from the ED. Health care systems should engage in ongoing TIA care performance assessment to complement existing stroke performance measurement.

Project description:BackgroundPatients with ischemic stroke or transient ischemic attack (TIA) are at increased risk for future cardiovascular events despite current preventive therapies. The identification of insulin resistance as a risk factor for stroke and myocardial infarction raised the possibility that pioglitazone, which improves insulin sensitivity, might benefit patients with cerebrovascular disease.MethodsIn this multicenter, double-blind trial, we randomly assigned 3876 patients who had had a recent ischemic stroke or TIA to receive either pioglitazone (target dose, 45 mg daily) or placebo. Eligible patients did not have diabetes but were found to have insulin resistance on the basis of a score of more than 3.0 on the homeostasis model assessment of insulin resistance (HOMA-IR) index. The primary outcome was fatal or nonfatal stroke or myocardial infarction.ResultsBy 4.8 years, a primary outcome had occurred in 175 of 1939 patients (9.0%) in the pioglitazone group and in 228 of 1937 (11.8%) in the placebo group (hazard ratio in the pioglitazone group, 0.76; 95% confidence interval [CI], 0.62 to 0.93; P=0.007). Diabetes developed in 73 patients (3.8%) and 149 patients (7.7%), respectively (hazard ratio, 0.48; 95% CI, 0.33 to 0.69; P<0.001). There was no significant between-group difference in all-cause mortality (hazard ratio, 0.93; 95% CI, 0.73 to 1.17; P=0.52). Pioglitazone was associated with a greater frequency of weight gain exceeding 4.5 kg than was placebo (52.2% vs. 33.7%, P<0.001), edema (35.6% vs. 24.9%, P<0.001), and bone fracture requiring surgery or hospitalization (5.1% vs. 3.2%, P=0.003).ConclusionsIn this trial involving patients without diabetes who had insulin resistance along with a recent history of ischemic stroke or TIA, the risk of stroke or myocardial infarction was lower among patients who received pioglitazone than among those who received placebo. Pioglitazone was also associated with a lower risk of diabetes but with higher risks of weight gain, edema, and fracture. (Funded by the National Institute of Neurological Disorders and Stroke; ClinicalTrials.gov number, NCT00091949.).

Project description:BackgroundQuestions persist about how learning healthcare systems should integrate audit and feedback (A&F) into quality improvement (QI) projects to support clinical teams' use of performance data to improve care quality.ObjectiveTo identify how a virtual "Hub" dashboard that provided performance data for patients with transient ischemic attack (TIA), a resource library, and a forum for sharing QI plans and tools supported QI activities among newly formed multidisciplinary clinical teams at six Department of Veterans Affairs (VA) medical centers.DesignAn observational, qualitative evaluation of how team members used a web-based Hub.ParticipantsExternal facilitators and multidisciplinary team members at VA facilities engaged in QI to improve the quality of TIA care.ApproachQualitative implementation process and summative evaluation of observational Hub data (interviews with Hub users, structured field notes) to identify emergent, contextual themes and patterns of Hub usage.Key resultsThe Hub supported newly formed multidisciplinary teams in implementing QI plans in three main ways: as an information interface for integrated monitoring of TIA performance; as a repository used by local teams and facility champions; and as a tool for team activation. The Hub enabled access to data that were previously inaccessible and unavailable and integrated that data with benchmark and scientific evidence to serve as a common data infrastructure. Led by champions, each implementation team used the Hub differently: local adoption of the staff and patient education materials; benchmarking facility performance against national rates and peer facilities; and positive reinforcement for QI plan development and monitoring. External facilitators used the Hub to help teams leverage data to target areas of improvement and disseminate local adaptations to promote resource sharing across teams.ConclusionsAs a dynamic platform for A&F operating within learning health systems, hubs represent a promising strategy to support local implementation of QI programs by newly formed, multidisciplinary teams.

Dataset Information

Randomized controlled trial of a coordinated care intervention to improve risk factor control after stroke or transient ischemic attack in the safety net: Secondary stroke prevention by Uniting Community and Chronic care model teams Early to End Disparities (SUCCEED).

Publications

Randomized controlled trial of a coordinated care intervention to improve risk factor control after stroke or transient ischemic attack in the safety net: Secondary stroke prevention by Uniting Community and Chronic care model teams Early to End Disparities (SUCCEED).

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets