Antibiotic Prescribing at CHOP: Primary Care Jeffrey S. Gerber MD, PhD, MSCE Division of Infectious Diseases The Children’s Hospital of Philadelphia

Primary Care Pediatrics Bob Grundmeier, Alex Fiks, Mort Wasserman General Pediatrics Lou Bell, Ron Keren Pediatric Infectious Diseases Theo Zaoutis, Priya Prasad, Jeff Gerber Biostatistics/data management Russell Localio, Lihai Song PeRC Administrator Jim Massey Study Team

Agenda 1.Rationale for assessing antibiotic use 2.Antibiotic prescribing data across-practice analyses within-clinician analyses 3.Intervention

Agenda 1.Rationale for assessing antibiotic use 2.Antibiotic prescribing data across-practice analyses within-clinician analyses 3.Intervention

AHRQ Goal To implement and evaluate evidence- based methods or strategies for reducing the inappropriate use of antibiotics in primary care office practices must address: 1.conditions for which abx are not effective 2.broad-spectrum antibiotic use when narrow-spectrum antibiotics are indicated

Background about half of antibiotic use is unnecessary overuse well-documented in primary care antibiotic overuse leads to:  bacterial resistance  drug-related adverse events  increases in health care costs  $20 billion estimated by IOM

Antibiotic Resistance

Resistance Aside... 5%–25% diarrhea 1 in 1000 visit emergency department for adverse effect of antibiotic –comparable to insulin, warfarin, and digoxin 1 in 4000 chance that an antibiotic will prevent serious complication from URI Shehab N. CID 2008:47; Linder JA. CID 2008:47

Antimicrobial Stewardship Antimicrobial Stewardship Programs recommended for hospitals most antibiotic use (and misuse) occurs in the outpatient setting is outpatient “stewardship” achievable?

Agenda 1.Rationale for assessing antibiotic use 2.Antibiotic prescribing data across-practice analyses within-clinician analyses 3.Intervention

Study Setting: CHOP Care Network 5 urban, academic 24 “private” practices urban, suburban, rural common EHR

Case Definitions ICD9 codes for common infections (+/- GAS testing, antibiotic use) verified by chart review and provider feedback Excluding: –antibiotic allergy –visit within prior 3 months with antibiotic –concurrent bacterial infection AOM, SSTI, UTI, lyme, acne, chronic sinusitis, mycoplasma, scarlet fever, animal bite, proph, oral infections, pertussis, STD, bone/joint –complex chronic conditions (Feudtner, Pediatrics 2000)

Broad-Spectrum Antibiotics amoxicillin-clavulanate cephalosporins azithromycin* * not considered broad-spectrum therapy for pneumonia

Table 1. Demographic characteristics of the study cohort, by site

1,296,517 Encounters 51,421 narrow ABX 29,635 broad ABX 102,102 antibiotic Rx 8,204 prior ABX 8,204 prior ABX 14,298 ABX allergy 14,298 ABX allergy 399,793 sick visits 399,793 sick visits 630,502 office visits 363,049 sick visits 230,709 preventive 666,015 phone, refills 666,015 phone, refills 36,744 visits w/ CCC 36,744 visits w/ CCC 260,947 no antibiotics 260,947 no antibiotics

Antibiotic Prescribing for Sick Visits Excluding: preventive visits, CCC Standardized by: age, sex, age-sex, race, Medicaid

Antibiotic Prescribing: Std for ARTI Dx Excluding: preventive visits, CCC Standardized by: age, sex, age-sex, race, Medicaid, ARTI Dx

Broad Antibiotic Prescribing Excluding: preventive visits, CCC, antibiotic allergy, prior antibiotics Standardized by: age, sex, age-sex, race, Medicaid

Broad Antibiotics: Std ARTI Dx Excluding: preventive visits, CCC, antibiotic allergy, prior antibiotics Standardized by: age, sex, age-sex, race, Medicaid, ARTI Dx

Diagnosis rate of AOM Excluding: preventive visits, CCC, prior antibiotics Standardized by: age, sex, age-sex, race, Medicaid

Broad Antibiotics for AOM Excluding: preventive visits, CCC, prior antibiotics Standardized by: age, sex, age-sex, race, Medicaid

Broad Antibiotics for Sinusitis Excluding: preventive visits, CCC, antibiotic allergy, prior antibiotics Standardized by: age, sex, age-sex, race, Medicaid

Broad Antibiotics for GAS pharyngitis Excluding: preventive visits, CCC, antibiotic allergy, prior antibiotics Standardized by: age, sex, age-sex, race, Medicaid

Broad Antibiotics for Pneumonia Excluding: preventive visits, CCC, antibiotic allergy, prior antibiotics Standardized by: age, sex, age-sex, race, Medicaid

Summary of variability data antibiotic prescribing at sick visits varies significantly across practice sites broad-spectrum antibiotic prescribing at sick visits varies significantly across practice sites the rate of diagnosis of ARTIs varies significantly across practice sites adherence to prescribing guidelines for AOM, sinusitis, GAS pharyngitis, and pneumonia varies significantly across practice sites

Agenda 1.Rationale for assessing antibiotic use 2.Antibiotic prescribing data across-practice analyses within-clinician analyses 3.Intervention

Antibiotic Prescribing by Patient Race within clinician analyses of antibiotic prescribing and diagnoses in same cohort Excluding: –complex chronic conditions –preventive visits, asthma, (allergy, prior antibiotics) Adjusted for: –sex, age category (0-1; 1-5; 6-10; 11-18) –Medicaid, site

Antibiotic Prescribing by Patient Race OR (black)95% CIMarginsP-value , , 0.24< Receipt of antibiotic prescription per SICK VISIT: Excluding: CCC, asthma Adjusted for: age category, sex, Medicaid

Visit Rate by Patient Race Sick visits per year by race: Primary care BlackNon-black sick visits preventive visits1.1 CHOP ED (5 practices) BlackNon-black all ED visits ED visits for ARTI0.02

Antibiotic Prescribing by Patient Race IRR (black)95% CIP-value , 0.65< Receipt of antibiotic prescription per CHILD: Excluding: CCC Adjusted for: age category, sex, Medicaid

Diagnosis by Patient Race Diagnosis of various ARTIs: conditionOR95% CIMarginsP-value AOM , , 0.12< acute sinusitis , , 0.05< GAS pharyngitis , , 0.03< pneumonia , , UTI , , Excluding: CCC, asthma Adjusted for: age category, sex, Medicaid

Antibiotic Prescribing by Patient Race OR95% CIMarginsP-value , , 0.32< Receipt of broad-spectrum antibiotic (if any antibiotic prescribed) Excluding: CCC, asthma, allergy Adjusted for: age category, sex, Medicaid

Antibiotic Prescribing by Patient Race Receipt of broad antibiotics for ARTI: conditionOR95% CIMarginsP-value AOM , , 0.31< GAS pharyngitis , , sinusitis , , pneumonia , , Excluding: CCC, asthma, allergy Adjusted for: age category, sex, Medicaid

Summary of race data black children receive fewer antibiotic prescriptions per sick visit and per child than non-black children black children are diagnosed with less ARTI than non-black children when diagnosed with AOM, black children receive more appropriate (i.e. less broad- spectrum) antibiotics black children have less sick visits than non- black children (but equal number of well visits)

Why? confounding? difference in epidemiology of disease, including BOTH prevalence and severity of illness linked with race? parental expectations/pressure linked with race? perception of parental expectations/pressure linked with race?

Agenda 1.Rationale for assessing antibiotic use 2.Antibiotic prescribing data across-practice analyses within-clinician analyses 3.Intervention

Specific Aim To determine the impact of an outpatient antimicrobial stewardship bundle within a pediatric primary care network on antibiotic prescribing for common ARTI: 1.Antibiotic prescribing for viral infections 2.Broad-spectrum antibiotic prescribing for conditions for which narrow-spectrum antibiotics are indicated.

Study Design cluster-randomized controlled trial bundled intervention vs. no intervention unit of observation will be the practitioner but randomized at practice level –natural distribution of physicians –avoids intra-practice contamination

Intervention 1.guideline development 2.education 3.audit and feedback

Why Might Unnecessary Prescribing Occur? Prescribing Awareness Antibiotic Prescribing Parental Expectations Knowledge Gaps Diagnostic Challenges Time Constraints

Parental Expectations Diagnostic Challenges Time Constraints Knowledge Gaps Prescribing Awareness Why Might Unnecessary Prescribing Occur? Antibiotic Prescribing

Hypotheses 1.clinicians have incomplete knowledge of the data regarding the effectiveness of antibiotics for respiratory tract infections  GAS and broad spectrum antibiotics  antibiotic activity against pneumococcus  prevention of bacterial superinfection  role of moraxella and Hflu in disease 2.clinicians are unaware of/have not been presented with data regarding their own prescribing of antibiotics

Education on site, interactive sessions for each practice randomized to the intervention –present the purpose of the study –discuss guideline development/contents –instruct how to access guidelines –explain audit & feedback –present baseline data –gather feedback

Guidelines review AAP and Red Book guidelines pediatric primary care/ID/clinical pharmacy modified if necessary generate benchmarks

GAS: Rationale for penicillin/amox GAS resistance to pcn has NEVER been seen azithromycin and cephalosporins  have NOT been shown to be superior for pharyngitis or for prevention of sequelae  data does not support increased patient compliance over oral penicillin or amoxicillin.  exposure promotes resistance to these and other antibiotics.  AAP/Red Book endorsed

Guideline Access (pdf) EPIC link:  linked to chief complaint  NOT decision support  optional  no workflow interruption PARTI

Study Setting: CHOP Care Network 5 urban, academic 24 “private” practices  urban  suburban  rural

VIRAL common cold URI acute bronchitis tonsillitis pharyngitis (non-strep) VIRAL common cold URI acute bronchitis tonsillitis pharyngitis (non-strep) Outcomes no antibiotics BACTERIAL acute sinusitis Strep pharyngitis pneumonia BACTERIAL acute sinusitis Strep pharyngitis pneumonia penicillin/amoxicillin

Case Definitions ICD9 codes for common infections (+/- GAS testing, antibiotic use) verified by chart review and provider feedback Excluding: –antibiotic allergy –visit within prior 3 months with antibiotic –concurrent bacterial infection AOM, SSTI, UTI, lyme, acne, chronic sinusitis, mycoplasma, scarlet fever, animal bite, proph, oral infections, pertussis, STD, bone/joint –children with complex chronic diseases

Data Collection EPIC EMR ICD9 coding –diagnoses –chronic medical conditions antibiotic orders telephone encounters age, race/ethnicity, sex, insurance, allergies provider: degree, yr grad, sex, % effort, practice volume, support staff

Analysis/Sample Size descriptive analysis of changes within and among sites. multivariable repeated measures analysis using generalized linear models 140 clinicians; 70 each arm power > 0.9 to detect 10% improvement in prescribing

Randomization 22 of 24 Enrolled (18 “sites”) 143,254 patients; 512,943 encounters –49.5% female –69% White each site enumerated by location and volume block-randomized 9 sites to each arm

Intervention: Timeline 12 months of audit/feedback 12 months after feedback ends 12 months baseline data Site presentation Feedback reports

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Some Limitations ICD9 codes –misclassification of outcome –intervention may change coding contamination of intervention lack of “buy-in” by practitioners generalizability

Future Directions complete analysis assess durability of effect (if there is one) gather qualitative data from providers predictors of prescribing clinical pathways/decision support?