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Lessons from the Johns Hopkins Multi-Disciplinary Venous Thromboembolism (VTE) Prevention Collaborative.
BMJ. 2012;344:e3935
Authors: Streiff MB, Carolan HT, Hobson DB, Kraus PS, Holzmueller CG, Demski R, Lau BD, Biscup-Horn P, Pronovost PJ, Haut ER
Abstract
PROBLEM: Venous thromboembolism (VTE) is a common cause of potentially preventable mortality, morbidity, and increased medical costs. Risk-appropriate prophylaxis can prevent most VTE events, but only a small fraction of patients at risk receive this treatment.
DESIGN: Prospective quality improvement programme.
SETTING: Johns Hopkins Hospital, Baltimore, Maryland, USA.
STRATEGIES FOR CHANGE: A multidisciplinary team established a VTE Prevention Collaborative in 2005. The collaborative applied the four step TRIP (translating research into practice) model to develop and implement a mandatory clinical decision support tool for VTE risk stratification and risk-appropriate VTE prophylaxis for all hospitalised adult patients. Initially, paper based VTE order sets were implemented, which were then converted into 16 specialty-specific, mandatory, computerised, clinical decision support modules.
KEY MEASURES FOR IMPROVEMENT: VTE risk stratification within 24 hours of hospital admission and provision of risk-appropriate, evidence based VTE prophylaxis.
EFFECTS OF CHANGE: The VTE team was able to increase VTE risk assessment and ordering of risk-appropriate prophylaxis with paper based order sets to a limited extent, but achieved higher compliance with a computerised clinical decision support tool and the data feedback which it enabled. Risk-appropriate VTE prophylaxis increased from 26% to 80% for surgical patients and from 25% to 92% for medical patients in 2011.
LESSONS LEARNT: A computerised clinical decision support tool can increase VTE risk stratification and risk-appropriate VTE prophylaxis among hospitalised adult patients admitted to a large urban academic medical centre. It is important to ensure the tool is part of the clinician's normal workflow, is mandatory (computerised forcing function), and offers the requisite modules needed for every clinical specialty.
PMID: 22718994 [PubMed - in process]