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Prev Chronic Dis ; 10: E161, 2013 Sep 26.
Article in English | MEDLINE | ID: mdl-24070033

ABSTRACT

INTRODUCTION: Quality improvement collaboratives are a popular model used to address gaps between evidence-based practice and patient care. Little is known about use of such collaboratives in emergency medical services, particularly for improving prehospital stroke care. To determine the feasibility of using this approach to improve prehospital stroke care, we conducted a pilot study of the Emergency Medical Services Stroke Quality Improvement Collaborative. METHODS: Seventeen Massachusetts emergency medical service agencies participated in the quality improvement collaborative pilot project. We identified 5 prehospital stroke performance measures to assess the quality of prehospital care, guide collaborative activities, and monitor change in performance over time. During learning sessions, participants were trained in quality improvement and performance measurement, analyzed performance measure results, and shared successes and challenges. Focus groups were conducted to understand participants' experiences with the collaborative. RESULTS: Participating emergency medical service agencies collected stroke performance measures on 3,009 stroke patients during the pilot study. Adherence to 4 of 5 performance measures increased significantly over time. Participants acknowledged that the collaborative provided them with an efficient and effective framework for stroke quality improvement and peer-learning opportunities. CONCLUSION: As evidenced in Massachusetts, quality improvement collaboratives can be an effective tool to improve prehospital stroke care. The data collected, improvements made, participation of emergency medical service agencies, and positive experiences within the collaborative support the continued use of this approach.


Subject(s)
Emergency Medical Services/standards , Quality Improvement/organization & administration , Stroke/prevention & control , Evidence-Based Emergency Medicine/standards , Evidence-Based Emergency Medicine/statistics & numerical data , Humans , Massachusetts/epidemiology , Stroke/epidemiology , Time Factors
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