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Structured Abstract
Objective:
Unnecessary prescribing of antibiotics is a major problem in the US and worldwide, contributing to the problem of antimicrobial resistance (AMR). This review examines the effects of quality improvement strategies on reducing inappropriate prescribing of antibiotics, targeting both prescribing of antibiotics for non-bacterial illnesses (“the antibiotic treatment decision”) and prescribing of broad-spectrum antibiotics when narrow-spectrum agents are indicated (“the antibiotic selection decision”).
Search Strategy and Inclusion Criteria:
We evaluated studies examining the effectiveness of quality improvement (QI) strategies targeting outpatient antibiotic prescribing for acute illnesses. Studies were identified by searching the Cochrane Collaboration's Effective Practice and Organisation of Care registry and MEDLINE®. We included randomized and quasi-randomized controlled trials, controlled before-after studies, and interrupted time series that reported measures of antimicrobial use. QI strategies were classified as clinician education, patient education, provision of delayed prescriptions, audit and feedback, clinician reminders, and financial or regulatory incentives. Our primary outcomes were the percentage of patients prescribed an antibiotic (for antibiotic treatment studies); or the percentage of patients prescribed a recommended antibiotic or guideline-concordant antibiotic therapy (for antibiotic selection studies). Secondary outcomes included effects on antimicrobial resistance, intervention safety (disease outcomes and adverse events), prescribing costs, and patient satisfaction.
Data Collection and Analysis:
Two reviewers abstracted data on the components of the QI intervention, study population, targets, and outcomes. We compared the effects of QI strategies in terms of the median effect achieved for the primary outcomes, using nonparametric tests; studies not eligible for median effects analysis were summarized qualitatively.
Main Results:
Fifty-four studies reporting a total of 74 trials met the inclusion criteria; 34 studies (reporting 41 trials) addressed the treatment decision, and 26 studies (reporting 33 trials) addressed the selection decision. Six studies evaluated both decisions. Study methodologic quality was generally fair. Nearly all studies took place in outpatient primary care clinics.
Studies addressing the antibiotic treatment decision: Most studies addressed prescribing for acute respiratory infections (ARIs). Interventions were effective at reducing prescribing, with a median absolute effect of -8.9% [interquartile range (IQR) -12.4% to -6.7%]. No individual QI strategy (or combination of strategies) was more effective at reducing prescribing. Within clinician education, active educational strategies appeared more effective than passive strategies. When extrapolated to a population level, strategies targeting general antibiotic prescribing appeared to reduce antibiotic prescribing more than strategies targeting prescribing for a single condition. Few studies addressed secondary endpoints; patient satisfaction was not worsened by QI interventions, but effects on AMR or costs could not be assessed.
Studies addressing the antibiotic selection decision: Interventions targeted prescribing for ARIs or urinary tract infections (UTIs). Interventions were effective, with a median absolute improvement in prescribing of recommended antibiotics of 10.6% (IQR 3.4% to 18.2%). Clinician education alone appeared more effective than education in combination with audit and feedback, but this finding likely represents confounding. Very few studies addressed secondary outcomes.
Conclusion:
Quality improvement efforts appear generally effective at reducing both inappropriate treatment with antibiotics and inappropriate selection of antibiotics. While no single QI strategy was more effective than others, active clinician education may be more effective than passive education, particularly for addressing the antibiotic treatment decision. Greater reductions in overall prescribing may be achieved through efforts targeting prescribing for all acute respiratory infections, rather than targeting single conditions. The available evidence is of only fair quality, and further research on the cost-effectiveness and potential harms of these interventions is needed.
Contents
- Preface
- Acknowledgments
- Executive Summary
- 1. Introduction
- Rationale for Reducing Excess Antibiotic Use in Ambulatory Practice
- Current Antibiotic Prescribing Practice Patterns in US Ambulatory Practices
- The Purpose of This Evidence-based Practice Center Report
- An Explanatory Model of Antibiotic Prescribing Behavior
- Clinician Factors
- Public/Patient Factors
- Health Care Delivery System Factors
- 2. Methods
- Scope
- Definitions of Quality Improvement Terms Used in This Report
- Classification of Interventions
- Classification of Quality Improvement Strategies
- Inclusion and Exclusion Criteria
- Literature Search and Review Process
- Outcome Measures
- Assessment of Study Quality
- An Explanatory Model for Evaluating the Different QI Strategies To Improve Antibiotic Prescribing Behavior
- Statistical Analysis
- Calculation of Effective Sample Sizes
- Calculation of the Population Effect Size
- Particularly Salient Studies
- 3. Results
- 4. Discussion
- Appendixes
- Appendix A Summary of Key Studies
- Appendix B Summaries of Included Studies, Grouped by Setting and Measured Population
- Appendix C EPOC and Medline Search for Antibiotic QI Articles
- Appendix D Antibiotic Abstraction Forms for Screening and Full-Text Review
- Appendix E Random Effects Meta-Analysis of Included Trials
- Appendix F Technical Expert Panel and Peer Reviewers
- References
- Listing of Excluded Studies
- Summary Tables
- Table References
Series Editors: Kaveh G Shojania, MD, University of California, San Francisco, Kathryn M McDonald, MM, Stanford University, Robert M Wachter, MD, University of California, San Francisco, Douglas K Owens, MD, MS, VA Palo Alto Health Care System, Palo Alto, California, and Stanford University. Managing Editor: Amy J Markowitz, JD.
Prepared for: Agency for Healthcare Research and Quality, U.S. Department of Health and Human Services.1 Contract No. 290-02-0017. Prepared by: Stanford-UCSF Evidence-based Practice Center.
Suggested citation:
Ranji SR, Steinman MA, Shojania KG, Sundaram V, Lewis R, Arnold S, Gonzales R. Antibiotic Prescribing Behavior. Vol. 4 of: Shojania KG, McDonald KM, Wachter RM, Owens DK, editors. Closing the Quality Gap: A Critical Analysis of Quality Improvement Strategies. Technical Review 9 (Prepared by the Stanford University-UCSF Evidence-based Practice Center under Contract No. 290-02-0017). AHRQ Publication No. 04(06)-0051-4. Rockville, MD: Agency for Healthcare Research and Quality. January 2006.
This report is based on research conducted by the Stanford-UCSF Evidence-based Practice Center (EPC) under contract to the Agency for Healthcare Research and Quality (AHRQ), Rockville, MD (Contract No. 290-02-0017). The findings and conclusions in this document are those of the author(s), who are responsible for its content, and do not necessarily represent the views of AHRQ. No statement in this report should be construed as an official position of AHRQ or of the U.S. Department of Health and Human Services.
The information in this report is intended to help clinicians, employers, policymakers, and others make informed decisions about the provision of health care services. This report is intended as a reference and not as a substitute for clinical judgment.
This report may be used, in whole or in part, as the basis for the development of clinical practice guidelines and other quality enhancement tools, or as a basis for reimbursement and coverage policies. AHRQ or U.S. Department of Health and Human Services endorsement of such derivative products may not be stated or implied.
None of the investigators has any affiliations or financial involvement that conflicts with the material presented in this report.
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540 Gaither Road, Rockville, MD 20850. www
.ahrq.gov
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