Richard Lechtenberg, MPH University of California, Berkeley California Dept. of Public Health Enough...
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Transcript of Richard Lechtenberg, MPH University of California, Berkeley California Dept. of Public Health Enough...
Richard Lechtenberg, MPHUniversity of California, BerkeleyCalifornia Dept. of Public Health
Enough to Make You CRiNGe:Variation in Adherence
to the Treatment Guidelines for Neisseria gonorrhoeae,
California, 2009-2011
Gonorrhea: Nothing to Clap About• 2nd most common reported infectious disease• Risk factor for…– Pelvic inflammatory disease– Ectopic pregnancy– Infertility
• Facilitates transmission and acquisition of HIV• Largest racial health disparities• Antimicrobial resistance
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Study Question
• How does adherence to the CDC treatment guidelines for gonorrhea vary by clinical practice setting?
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Provider diagnosis Positive lab test
Case report Lab report
Local health jurisdiction
Electronic submission to the state
Random sample of cases drawn
Pre-populated interview record sent via secure e-mail
Patient and provider interviewed by phone
Data entered at the state
Small LHJs
The California Gonorrhea Surveillance System
2006 guidelinesin effect 2010 guidelines
in effect
lag
12/16/10
Adherent Treatment 8/4/2006 – 12/16/2010 12/17/2010 – 8/9/2012
Cervix,
Urethra, &
Rectum
Ceftriaxone 125 mg IM OR
Cefixime 400 mgCeftriaxone 250 mg IM OR, IF NOT AN OPTION
Cefixime 400 mgPLUS
Azithromycin 1g OR Doxycycline 100 mg BIDx7
Pharynx
Ceftriaxone 125 mg IMCeftriaxone 250 mg IM
PLUSAzithromycin 1g
OR Doxycycline 100 mg BIDx7
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Analysis
Inclusion and exclusion criteria related to specific diagnoses
Bivariate associations tested using weighted χ2 tests
Directed acyclic graphs (DAG) used to identify confounders
Independent cumulative incidence ratios (CIR) estimated using weighted generalized linear models
Adjusted Wald tests used to test the significance of sets of coefficients (α=0.10)
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Software
• Dataset compiled in SAS 9.2• Analyses in R 2.13.1• DAG in daggity.net
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Percent receiving a non-rec. treatment by clinical setting
STD clinic
HIV clinic
Comm./Pbl Hlth clinic
Family planning facility
Private physician/HMO
Hospital
Other
ER/Urgent Care
Correctional facility
Military/VA
0% 5% 10% 15% 20% 25% 30% 35% 40%
Causal Diagram & Modeling Process
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p=0.48
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Summary and Recommendations• >2-fold increase in risk of non-rec. tx in
nearly all settings compared to STD clinics; esp. high at...–Military/VA facilities–Correctional facilities
• But intervention may be most fruitful at…– family planning facilities –private physicians/HMOs
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Summary and Recommendations (contd.)
• Lower risk of receiving a non-rec. tx among…–MSM–Blacks and Hispanics
• Directions for future research–Identification of specific barriers to the
provision of guideline-concordant treatment
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Limitations Strengths
Selection Bias•Response Bias•Reporting Bias
Information Bias•Misclassification of the outcome
Sample size•Large
Data•variety of clinical settings•Large geographic region
Robust results•Robust to sensitivity analyses
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• Colleagues at CDPH– Michael Samuel, DrPH*– Heidi Bauer, MD, MS,
MPH*– Joan Chow, DrPH, MPH– Ina Park, MD, MS– Nicole Olson, MPH*– Scott Baker, MPH– Jessica Frasure-Williams,
MPH– Mary Fredrickson– Carol Kong, MPH*
• My professors at UC Berkeley– Kyle Bernstein, PhD, ScM*– Maureen Lahiff, PhD*– Barbara Abrams, DrPH– Jack Colford, MD, PhD
*Co-authors
Acknowledgements
Contact Info
Richard Lechtenberg, [email protected]