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Using Clinical Vignettes to Assess Quality of Care for Acute Respiratory Infections
- Source :
- Inquiry: The Journal of Health Care Organization, Provision, and Financing, Vol 53 (2016)
- Publication Year :
- 2016
- Publisher :
- SAGE Publishing, 2016.
-
Abstract
- Overprescribing of antibiotics for acute respiratory infections (ARIs) is common. Our objective was to develop and validate a vignette-based method to estimate clinician ARI antibiotic prescribing. We surveyed physicians (n = 78) and retail clinic clinicians (n = 109) between January and September 2013. We surveyed clinicians using a set of ARI vignettes and linked the responses to electronic health record data for all ARI visits managed by these clinicians during 2012. We then created a new measure of antibiotic prescribing, the comprehensive ARI management rate. This was defined as not prescribing antibiotics for antibiotic-inappropriate diagnoses and prescribing guideline-concordant antibiotics for antibiotic-appropriate diagnoses (and also included appropriate use of streptococcal testing for the pharyngitis vignettes). We compared the vignette-based and chart-based comprehensive ARI management at the clinician level. We then identified the combination of vignettes that best predicted comprehensive ARI management rates, using a partitioning algorithm. Responses to 3 vignettes partitioned clinicians into 4 groups with chart-based comprehensive ARI management rates of 61% (n = 121), 50% (n = 47), 31% (n = 12), and 22% (n = 7). Responses to 3 clinical vignettes can identify clinicians with relatively poor quality ARI antibiotic prescribing. Vignettes may be a mechanism to target clinicians for quality improvement efforts.
- Subjects :
- Public aspects of medicine
RA1-1270
Subjects
Details
- Language :
- English
- ISSN :
- 00469580 and 19457243
- Volume :
- 53
- Database :
- Directory of Open Access Journals
- Journal :
- Inquiry: The Journal of Health Care Organization, Provision, and Financing
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.7acae413c623484cbe38a680138be542
- Document Type :
- article
- Full Text :
- https://doi.org/10.1177/0046958016636531