BACKGROUND: Increasing indications for oral anticoagulation has led to pressure on general practices to undertake therapeutic monitoring. Computerized decision support (DSS) has been shown to be effective in hospitals for improving clinical management. Its usefulness in primary care has previously not been investigated. AIM: To test the effectiveness of using DSS for oral anticoagulation monitoring in primary care by measuring the proportions of patients adequately controlled, defined as within the appropriate therapeutic range of International Normalised Ratio (INR). METHOD:All patients receiving warfarin from two Birmingham inner city general practices were invited to attend a practice-based anticoagulation clinic. In practice A all patients were managed using DSS. In practice B patients were randomized to receive dosing advice either through DSS or through the local hospital laboratory. Clinical outcomes, adverse events and patient acceptability were recorded. RESULTS: Forty-nine patients were seen in total. There were significant improvements in INR control from 23% to 86% (P > 0.001) in the practice where all patients received dosing through DSS. In the practice where patients were randomized to either DSS or hospital dosing, logistic regression showed a significant trend for improvement in intervention patients which was not apparent in the hospital-dosed patients (P < 0.001). Mean recall times were significantly extended in patients who were dosed by the practice DSS through the full 12 months (24 days to 36 days) (P = 0.033). Adverse events were comparable between hospital and practice-dosed patients, although a number of esoteric events occurred. Patient satisfaction with the practice clinics was high. CONCLUSION:Computerized DSS enables the safe and effective transfer of anticoagulation management from hospital to primary care and may result in improved patient outcome in terms of the level of control, frequency of review and general acceptability.
RCT Entities:
BACKGROUND: Increasing indications for oral anticoagulation has led to pressure on general practices to undertake therapeutic monitoring. Computerized decision support (DSS) has been shown to be effective in hospitals for improving clinical management. Its usefulness in primary care has previously not been investigated. AIM: To test the effectiveness of using DSS for oral anticoagulation monitoring in primary care by measuring the proportions of patients adequately controlled, defined as within the appropriate therapeutic range of International Normalised Ratio (INR). METHOD: All patients receiving warfarin from two Birmingham inner city general practices were invited to attend a practice-based anticoagulation clinic. In practice A all patients were managed using DSS. In practice B patients were randomized to receive dosing advice either through DSS or through the local hospital laboratory. Clinical outcomes, adverse events and patient acceptability were recorded. RESULTS: Forty-nine patients were seen in total. There were significant improvements in INR control from 23% to 86% (P > 0.001) in the practice where all patients received dosing through DSS. In the practice where patients were randomized to either DSS or hospital dosing, logistic regression showed a significant trend for improvement in intervention patients which was not apparent in the hospital-dosed patients (P < 0.001). Mean recall times were significantly extended in patients who were dosed by the practice DSS through the full 12 months (24 days to 36 days) (P = 0.033). Adverse events were comparable between hospital and practice-dosed patients, although a number of esoteric events occurred. Patient satisfaction with the practice clinics was high. CONCLUSION: Computerized DSS enables the safe and effective transfer of anticoagulation management from hospital to primary care and may result in improved patient outcome in terms of the level of control, frequency of review and general acceptability.
Authors: Siaw-Teng Liaw; Nabil Sulaiman; Christopher Pearce; Jane Sims; Keith Hill; Heather Grain; Justin Tse; Choon-Kiat Ng Journal: J Am Med Inform Assoc Date: 2003-06-04 Impact factor: 4.497
Authors: Anne Holbrook; Sam Schulman; Daniel M Witt; Per Olav Vandvik; Jason Fish; Michael J Kovacs; Peter J Svensson; David L Veenstra; Mark Crowther; Gordon H Guyatt Journal: Chest Date: 2012-02 Impact factor: 9.410
Authors: Natalie Oake; Alison Jennings; Alan J Forster; Dean Fergusson; Steve Doucette; Carl van Walraven Journal: CMAJ Date: 2008-07-29 Impact factor: 8.262