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    Physician and Patient Influences on Provider Performance: {beta}-Blockers in Post-Myocardial Infarction Management in the MI-Plus Study

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    Authors
    Funkhouser, Ellen M.
    Houston, Thomas K.
    Levine, Deborah A.
    Richman, Joshua S.
    Allison, Jeroan J.
    Kiefe, Catarina I.
    UMass Chan Affiliations
    Department of Quantitative Health Sciences
    Document Type
    Journal Article
    Publication Date
    2011-01-01
    Keywords
    Physician's Practice Patterns
    Adrenergic beta-Antagonists
    Myocardial Infarction
    UMCCTS funding
    Biostatistics
    Epidemiology
    Health Services Research
    
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    Link to Full Text
    http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3099457/pdf/nihms273063.pdf
    Abstract
    Background efforts to improve the quality of care for patients with cardiovascular disease frequently target the decrease of physician-level performance variability. We assessed how variability in providing beta-blockers to ambulatory postmyocardial infarction (MI) patients was influenced by physician and patient level characteristics. Methods and Results beta-Blocker prescription and patient characteristics were abstracted from charts of post-MI patients treated by 133 primary care physicians between 2003 and 2007 and linked to physician and practice characteristics. Associations of beta-blocker prescription with physician- and patient-level characteristics were examined using mixed-effects models, with physician-level effects as random. Mean physician-specific predicted probabilities and the intraclass correlations, which assessed the proportion of variance explainable at the physician level, were estimated. Of 1901 patients without major contraindication, 69.1% (range across physicians, 20% to 100%) were prescribed beta-blockers. Prescription varied with comorbidity from 78.3% in patients with chronic kidney disease to 54.7% for patients with stroke. Although physician characteristics such as older physician age, group practice, and rural location were each positively associated with beta-blocker prescription, physician factors accounted for only 5% to 8% of the variance in beta-blocker prescription; the preponderance of the variance, 92% to 95%, was at the patient level. The mean physician-specific probability of beta-blocker prescription (95% confidence interval) in the fully adjusted model was 63% (61% to 65%). Conclusions beta-Blocker prescription rates were surprisingly low. The contribution of physician factors to overall variability in beta-blocker prescription, however, was limited. Increasing evidence-based use of beta-blockers may not be accomplished by focusing mostly on differential performance across physicians.
    Source
    Circ Cardiovasc Qual Outcomes. 2011 Jan 1;4(1):99-106. Epub 2010 Dec 7. doi:10.1161/CIRCOUTCOMES.110.942318. Link to article on publisher's site
    DOI
    10.1161/CIRCOUTCOMES.110.942318
    Permanent Link to this Item
    http://hdl.handle.net/20.500.14038/47764
    PubMed ID
    21139090
    Related Resources
    Link to Article in PubMed
    ae974a485f413a2113503eed53cd6c53
    10.1161/CIRCOUTCOMES.110.942318
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