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Hypotheses and Specific Aims:
The continued emergence of antibiotic-resistance in the outpatient setting underlines the need to responsibly manage antimicrobial prescribing. It is in this context that we seek to test an effective strategy for reducing the inappropriate use of antibiotics in primary care office practices. Our overall objective is to identify an effective and efficient strategy for decreasing the contribution of primary care clinicians to the emergence of antimicrobial-resistant bacteria in the community and to disseminate widely those strategies found to be effective and sustainable.
We hypothesize that implementation of a clinician decision support system, with an active education component, will reduce the inappropriate use of antibiotics in primary care office practices. Our hypothesis is based on the premise that most inappropriate prescribing is the result of multiple factors that include difficulty in distinguishing a benign, self-limited viral infection from a more serious bacterial infection; overdiagnosis of a bacterial infection in cases where there is clinical uncertainty as to the true nature of the illness; and constraints on the time available for clinicians to explain to patients the nature of the illness and the reasons an antibiotic is not indicated.
The focus of this proposal will be to compare the impact of clinical decision support and active education to no intervention for enhancing the appropriate use of antimicrobials for common outpatient infections. In this randomized control trial, primary care providers participating in the intervention arm will receive active education coupled with the implementation of a clinical decision support tool, while providers in the control arm will have no intervention. At the end of the study, providers in the control arm will receive a thorough analysis of their antibiotic prescribing patterns and suggested opportunities for improvement, as well as access to the intervention tools once the study has ended.
Our interdisciplinary team will integrate novel methods in implementation science with clinical and laboratory expertise in infectious diseases, antimicrobial stewardship, primary care, information technology, performance improvement, health services research, and biostatistics. The Specific Aims are constructed to validate our hypothesis in the primary care setting by demonstrating two results of our intervention strategy:
1. Reduced use of antibiotics to treat conditions for which those drugs are known not to be effective
2. Decreased prescribing of broad-spectrum antibiotics to treat common bacterial infections.
The degree of impact in terms of prescriptions per 100 visits for each targeted outpatient infection will be compared with active education and clinical decision support versus no intervention. The study will be able to measure the value of clinical decision support with active education that will inform future efforts in disseminating outpatient antibiotic stewardship interventions.
Allocation: Randomized, Control: Active Control, Endpoint Classification: Safety/Efficacy Study, Intervention Model: Parallel Assignment, Masking: Open Label, Primary Purpose: Health Services Research
Intervention: Education, Decision Support Tools
Denver Health and Hospitals Authority
Enrolling by invitation
University of Colorado, Denver
Published on BioPortfolio: 2014-08-27T03:14:44-0400
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Mathematical or statistical procedures used as aids in making a decision. They are frequently used in medical decision-making.
Computer-based information systems used to integrate clinical and patient information and provide support for decision-making in patient care.
Diminished or failed response of an organism, disease or tissue to the intended effectiveness of a chemical or drug. It should be differentiated from DRUG TOLERANCE which is the progressive diminution of the susceptibility of a human or animal to the effects of a drug, as a result of continued administration.
A graphic device used in decision analysis, series of decision options are represented as branches (hierarchical).
Simultaneous resistance to several structurally and functionally distinct drugs.
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