Antibiotic Prescribing at CHOP: Primary Care

Jeffrey S. Gerber MD, PhD, MSCEDivision of Infectious Diseases

The Children’s Hospital of Philadelphia

• Primary Care PediatricsBob Grundmeier, Alex Fiks, Mort Wasserman

• General PediatricsLou Bell, Ron Keren

• Pediatric Infectious DiseasesTheo Zaoutis, Priya Prasad, Jeff Gerber

• Biostatistics/data managementRussell Localio, Lihai Song

• PeRC AdministratorJim Massey

Study Team

Agenda

1. Rationale for assessing antibiotic use2. Antibiotic prescribing data

• across-practice analyses• within-clinician analyses

3. Intervention

Agenda

1. Rationale for assessing antibiotic use2. 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 effective2. 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 use2. 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

8,204prior ABX

14,298 ABX allergy

399,793 sick visits

630,502 office visits

363,049 sick visits

230,709 preventive

666,015phone, refills

36,744 visits w/ CCC

260,947no antibiotics

Antibiotic Prescribing for Sick Visits

Excluding: preventive visits, CCCStandardized by: age, sex, age-sex, race, Medicaid

Antibiotic Prescribing: Std for ARTI Dx

Excluding: preventive visits, CCCStandardized by: age, sex, age-sex, race, Medicaid, ARTI Dx

Broad Antibiotic Prescribing

Excluding: preventive visits, CCC, antibiotic allergy, prior antibioticsStandardized by: age, sex, age-sex, race, Medicaid

Broad Antibiotics: Std ARTI Dx

Excluding: preventive visits, CCC, antibiotic allergy, prior antibioticsStandardized by: age, sex, age-sex, race, Medicaid, ARTI Dx

Diagnosis rate of AOM

Excluding: preventive visits, CCC, prior antibioticsStandardized by: age, sex, age-sex, race, Medicaid

Broad Antibiotics for AOM

Excluding: preventive visits, CCC, prior antibioticsStandardized by: age, sex, age-sex, race, Medicaid

Broad Antibiotics for Sinusitis

Excluding: preventive visits, CCC, antibiotic allergy, prior antibioticsStandardized by: age, sex, age-sex, race, Medicaid

Broad Antibiotics for GAS pharyngitis

Excluding: preventive visits, CCC, antibiotic allergy, prior antibioticsStandardized by: age, sex, age-sex, race, Medicaid

Broad Antibiotics for Pneumonia

Excluding: preventive visits, CCC, antibiotic allergy, prior antibioticsStandardized 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 use2. 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% CI Margins P-value0.764 0.738, 0.790 0.29, 0.24 <0.0001

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 Black Non-black

sick visits 1.2 2.0preventive visits 1.1 1.1

CHOP ED (5 practices) Black Non-black

all ED visits 0.57 0.63ED visits for ARTI 0.02 0.02

Antibiotic Prescribing by Patient Race

IRR (black) 95% CI P-value0.64 0.63, 0.65 <0.0001

Receipt of antibiotic prescription per CHILD:

• Excluding: CCC

• Adjusted for: age category, sex, Medicaid

Diagnosis by Patient Race

Diagnosis of various ARTIs:

condition OR 95% CI Margins P-valueAOM 0.767 0.735, 0.801 0.15, 0.12 <0.0001acute sinusitis 0.817 0.761, 0.877 0.06, 0.05 <0.0001GAS pharyngitis 0.623 0.576, 0.674 0.05, 0.03 <0.0001pneumonia 1.058 0.963, 1.163 0.02, 0.02 0.235UTI 0.985 0.903, 1.074 0.02, 0.02 0.733

• Excluding: CCC, asthma

• Adjusted for: age category, sex, Medicaid

Antibiotic Prescribing by Patient Race

OR 95% CI Margins P-value0.834 0.781, 0.891 0.36, 0.32 <0.0001

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:condition OR 95% CI Margins P-valueAOM 0.737 0.662,

0.8210.38, 0.31 <0.0001

GAS pharyngitis 0.849 0.569, 1.266

0.08, 0.07 0.421

sinusitis 0.947 0.814, 1.102

0.44, 0.43 0.483

pneumonia 1.003 0.712, 1.412

0.17, 0.17 0.988

• 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 use2. 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 infections2. 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 development2. education3. 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

• email (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

VIRALcommon coldURIacute bronchitistonsillitispharyngitis (non-strep)

Outcomes

no antibiotics

BACTERIALacute sinusitisStrep pharyngitispneumonia

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 ofaudit/feedback

12 months afterfeedback ends

12 monthsbaseline data

Site presentation

Feedback reports

**

*

*

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?