INCREASING RESISTANCE TO ANTIBIotics

ORIGINAL CONTRIBUTION Changes in Antibiotic Prescribing for Children After a Community-wide Campaign Joseph F. Perz, DrPH Allen S. Craig, MD Christopher S. Coffey, PhD Daniel M. Jorgensen, MD, MPH Edward Mitchel, MS Stephanie Hall, MD, MPH William Schaffner, MD Marie R. Griffin, MD, MPH INCREASING RESISTANCE TO ANTIBIotics is compromising treatment of Streptococcus pneumoniae and other serious bacterial infections. 1,2 Antibiotic pressure, the use and misuse of large quantities of antibiotics, is the driving force behind the worldwide resistance phenomenon. 3,4 Concern regarding this problem has motivated a review of antibiotic prescribing patterns and treatment guidelines. 5-1 Children represent a population of particular concern because they have the highest rates of antibiotic use and infection with antibiotic-resistant pathogens. 2,11,12 By the early 199s, US children younger than 15 years were receiving an average of almost 1 oral antibiotic prescription per year, primarily for the treatment of respiratory infections. 11 A substantial proportion of this prescribing is thought to be unnecessary. 13,14 Responsible antimicrobial use as a means to curtail drug resistance has been broadly promoted by the Centers for Disease and Prevention (CDC), the American Academy of Pediatrics, and other groups and institutions. 5,15 In the United States, reductions in antibiotic prescribing have been demonstrated in targeted primary care See also pp 396 and 3133. Context Overuse of antibiotics has contributed to microbial resistance, compromising the treatment of bacterial infections. Very high levels ( 5%) of antibiotic resistance among invasive Streptococcus pneumoniae have been documented in County, Tennessee. Objective To determine the effectiveness of a community-wide intervention aimed at reducing inappropriate antibiotic use among children. Design, Setting, and Participants The County Health Department led a multifaceted year-long campaign (May 1997 through April 1998) aimed at decreasing unnecessary antibiotic use among children. Tennessee s 3 other major urban counties (Shelby, Hamilton, and Davidson) did not conduct similar campaigns and served as controls. Evaluation included white and black children (aged 15 years) enrolled in Tennessee s Medicaid Managed Care Program in the 4 study counties, representing 36% of the study counties children (4642 person-years observed). Intervention Educational efforts were directed toward health care practitioners (primarily via peer leader presentations) and to the parents of young children and the public (primarily via printed materials). Main Outcome Measure The intervention-attributable effect on antibiotic use, defined as the excess percentage change in oral antibiotic prescription rates in County between the 12-month preintervention and postintervention periods, relative to that of control counties. Results Antibiotic prescription rates declined 19% and 8% among County and control county children, respectively, yielding an 11% intervention-attributable decline (95% confidence interval, 8%-14%; P.1). The intervention-attributable decrease in prescription rates was greatest among children aged 1 to less than 5 years (among white children, 8% [P.1]; among black children, 18% [P.1]). Conclusions A community-wide educational intervention reduced antibiotic prescription levels among children in County. JAMA. 22;287:313-319 www.jama.com practices 16 and in 2 relatively isolated rural populations. 17,18 However, little is known about the effectiveness of broader community- or state-level campaigns. 5,19 Tennessee had the highest rate of prescription utilization in the United States Author Affiliations: Epidemic Intelligence Service, Epidemiology Program Office, Centers for Disease and Prevention, Atlanta, Ga (Dr Perz); Communicable and Environmental Disease Services, Tennessee Department of Health, Nashville (Drs Perz, Craig, and Schaffner); Department of Preventive Medicine, Vanderbilt University School of Medicine, Nashville, Tenn (Drs Craig, Coffey, Schaffner, and Griffin and Mr Mitchel); County Health Department, ville, Tenn (Drs Jorgensen and Hall). Dr Perz is currently affiliated with the Division of Viral Hepatitis, National Center for during 1998, based on capitated retail sales data. 2 Similarly, utilization rates for penicillins, cephalosporins, and trimethoprim-sulfamethoxazole in Tennessee were at least 2% higher than national averages. 2 Within Tennessee, strains of S pneumoniae isolated from in- Infectious Diseases, Centers for Disease and Prevention, Atlanta, Ga; Dr Coffey is currently affiliated with the Department of Biostatistics, School of Public Health, University of Alabama at Birmingham; and Dr Jorgensen is currently affiliated with Pfizer Global Research and Development, Groton, Conn. Corresponding Author and Reprints: Marie R. Griffin, MD, MPH, Vanderbilt University School of Medicine, Department of Preventive Medicine, A-1124 Medical Center North, Nashville, TN 37232-2637 (e-mail: Marie.Griffin@vanderbilt.edu). 22 American Medical Association. All rights reserved. (Reprinted) JAMA, June 19, 22 Vol 287, No. 23 313

vasive infections have demonstrated a high prevalence of penicillin resistance (35%) 2 ; the highest resistance levels ( 5%) were reported for County (1998 population, 375 21 ; county seat: ville). 22 In response to this problem, and stimulated by a recent multidrug-resistant pneumococcal meningitis outbreak in a nearby county, 23 the County Health Department (KCHD) conducted a multifaceted educational intervention. In this article, we evaluate the intervention s effect on pediatric antibiotic prescribing. METHODS The KCHD led a year-long communitywide intervention (May 1997 through April 1998) to decrease unnecessary antibiotic use among children. In 1997, KCHD created the East Tennessee Drug Resistance Task Force, with representatives of state, regional, and county health departments, a university medical center, a commercial laboratory, a managed care organization, and the CDC, to develop and implement the intervention. The campaign was directed at 3 main audiences: (1) 25 key health care providers (eg, pediatricians and family physicians) who provided most routine health care services to County children; (2) parents of young children; and (3) the general public. The educational campaign stressed that (1) antibiotics should be used only for bacterial infections; (2) colds and most coughs and sore throats are caused by viruses and should not be treated with antibiotics; and (3) when antibiotics are prescribed, they should be narrow spectrum. Major components of the campaign were as follows. Provider education consisted of (1) lectures by a CDC physician to 15 of the key providers; (2) presentations at hospital staff meetings, grand rounds, continuing medical education seminars, resident conferences, and targeted primary care clinics; (3) distribution of new prescribing guidelines for pediatric respiratory infections 6 to the 25 key providers; and (4) related articles published in the KCHD quarterly newsletter mailed to all 15 County physicians. Parent education consisted of (1) distribution of pamphlets to parents of all children in day care and grades K-3; (2) distribution of patient education materials to the 25 key providers; and (3) distribution of pamphlets to the parents of every newborn (incorporated with informational mailings regarding childhood immunizations). Public education consisted of (1) distribution of 3 pamphlets to hospitals, clinics, and dental offices; (2) communication of information through television, radio, and newspaper coverage and public service announcements; (3) distribution of 3 pamphlets to families receiving influenza vaccine; and (4) distribution of 53 pamphlets to pharmacy clients. One of the KCHD staff members, a medical epidemiologist, managed the campaign and performed the majority of the educational presentations. The majority of the educational materials (eg, pamphlets entitled Antibiotics and Your Child ) distributed in the campaign were developed by and are available from the CDC. 24,25 Study Design and Rationale Because there have been both general and localized efforts to promote the appropriate use of antibiotics, 25 the impact of the County intervention was evaluated by comparing outcomes with suitable control counties. Tennessee s 3 other urbanized counties were selected; these counties and their respective county seats were Shelby (Memphis), Davidson (Nashville), and Hamilton (Chattanooga). The control counties are geographically distant from County and did not conduct similar community-wide interventions. Prescription of oral antibiotics to children was compared between the intervention county and control counties during the 12-month periods before, during, and after the intervention. The intervention-attributable effect was defined as the excess percentage reduction in prescription rates in County relative to the control counties. The study also examined rates of outpatient visits for respiratory illnesses, ratios of prescriptions to respiratory illness visits, and antibiotic resistance among pneumococcal isolates from invasive infections. Because the absolute rate of antibiotic use was of interest, prescriptions were not linked to specific office visits and diagnoses, thus avoiding problems or omissions associated with mistakes or shifts in coding, 26 and prescriptions resulting from telephone consultations or emergency department visits. Study Population The study population included children younger than 15 years who were residents of 4 counties (, Davidson, Hamilton, and Shelby) and who were enrolled in the Tennessee Medicaid Managed Care Program (TennCare). On January 1, 1994, Medicaid was supplanted in Tennessee by TennCare, a managed care system that extended health insurance coverage to approximately 5% more persons than were eligible for Medicaid and shifted the care of enrollees to physicians in private practice. 27 The TennCare enrollment file identifies persons who are eligible to receive benefits; the specific dates of coverage; and the sex, race, date of birth, and county of residence of the enrollees. Children entered the study on the first day after May 1, 1996, on which they met the inclusion criteria, which were enrollment in TennCare within 3 days of birth or for 1 year, age younger than 15 years, and residence in 1 of the 4 study counties. Children were followed until loss of coverage by TennCare, age 15 years, death, or April 3, 1999. Person-time as a hospital inpatient was excluded. Children not designated as either white or black represented a small proportion (4%) of the eligible population and were also excluded. Person-time contributed by children included in the study was expressed in person-years and grouped according to age ( 1 year, 1 to 5 years, and5to 15 years), county of residence, and race. 314 JAMA, June 19, 22 Vol 287, No. 23 (Reprinted) 22 American Medical Association. All rights reserved.

Definitions, Outcomes, and Data Sources The 12-month periods before (May 1996 through April 1997), during (May 1997 through April 1998), and after (May 1998 through April 1999) the educational intervention were categorized as years 1, 2, and 3 for this study. Computerized TennCare files for 1996 through 1999 were used to determine the primary study outcome, oral antibiotic prescription use, and a secondary outcome, outpatient visits to a physician for a diagnosed respiratory illness, for enrolled children during the 3 study years. These files contained information on medical services reimbursed, including dates of medical services received on an outpatient basis, associated diagnoses and procedures, and prescriptions filled. Prescriptions were not linked with visits, and no more than 1 visit per patient per day was counted. Prescriptions included were those filled for antimicrobial drugs administered orally and typically used for treatment of respiratory infections in pediatric outpatients. Antibiotic categories included were penicillins (eg, amoxicillin and ampicillin), cephalosporins, trimethoprim-sulfamethoxazole, and macrolides/other (eg, erythromycin, erythromycin-sulfisoxazole, azithromycin, and clindamycin). For the purpose of this study, respiratory illness was defined as an outpatient diagnosis of otitis media (International Classification of Diseases, Ninth Revision [ICD- 9] 28 codes 381-382), common cold (ICD-9 code 46), sinusitis (ICD-9 codes 461, 473), pharyngitis (ICD-9 code 462), tonsillitis (ICD-9 code 463), laryngitis/tracheitis (ICD-9 code 464), bronchitis (ICD-9 codes 466, 49, 491); pneumonia and influenza (ICD-9 codes 4-487); or unspecified acute respiratory illness (ICD-9 code 465). Data on cases of invasive S pneumoniae infections occurring in County children younger than 15 years were provided by an ongoing, active, populationbased surveillance system sponsored by the CDC (the Active Bacterial Core Surveillance program 29 ). A case of invasive pneumococcal disease was defined as isolation of S pneumoniae from blood, cerebrospinal fluid, or other usually sterile site. Isolates were tested for antimicrobial susceptibility using the broth microdilution method by a designated reference laboratory. Susceptibilities to penicillin, cefotaxime, trimethoprimsulfamethoxazole, and erythromycin were examined. Isolates were defined as resistant in this study if they exhibited intermediate- or high-level resistance to a particular antibiotic. Statistical Analysis Prescription rates were calculated by dividing the number of antibiotic prescriptions administered in ambulatory care by the person-years observed. Prescription rates were stratified by study county, study year, race, age group, and antibiotic category and were expressed per 1 person-years. When stratified by race, baseline prescription rates were similar among the 3 control counties (TABLE 1). For this reason, the control counties were combined in the subsequent analyses. Negative Binomial Regression models 3 were used to estimate adjusted prescription rates, test whether a significant intervention-attributable effect existed, and examine potential interactions among the interventionattributable effect with age and race. Each model included variables representing county ( vs control), age group ( 1 year, 1 to 5 years, and 5 to 15 years), race (white and black), and study year (year 1, 2, and 3), as well as all relevant interaction terms. In addition, each model included random effects to account for unobserved heterogeneity within the counties. The intervention-attributable effect was represented by the excess percentage change in prescription rates from year 1 to year 3 for County over and above any temporal reductions observed in the control counties. The intervention-attributable change in the crude rate was determined by multiplying the intervention-attributable excess percentage change by the baseline rate in county and represents the estimated reduction in the number of prescriptions in county in year 3 attributable to the intervention. Visit rates, calculated by dividing the number of outpatient respiratory ill- Table 1. Study Population Characteristics and Baseline (Year 1, May 1996-April 1997) Rates of Respiratory Illness Visits and Antibiotic Prescriptions* County Intervention Sites Davidson Hamilton Shelby Annual mean (SD) person-years 18 476 (73) 34 22 (1853) 18 257 (886) 83 789 (47) Proportion of county children 27 34 32 42 aged 15 years included, % Age in years, % 1 9 9 9 8 1to 5 3 3 3 3 5to 15 61 61 62 62 Race, % White 73 39 46 1 Black 27 61 54 9 Crude antibiotic prescription rates, year 1 (per 1 person-years) Total 175 122 136 89 White 198 162 181 177 Black 112 95 98 79 Crude respiratory illness visit rates, year 1 (per 1 person-years) Total 161 113 118 84 White 181 157 166 175 Black 15 85 77 74 *Study population characteristics reflect the entire study period (years 1-3, May 1996-April 1999). Proportions based on US Census county population estimates for July 1, 1998. 21 22 American Medical Association. All rights reserved. (Reprinted) JAMA, June 19, 22 Vol 287, No. 23 315

Table 2. Changes in Antibiotic Prescription Rates (per 1 Person-years) and Intervention-Attributable Effects, by Age and Race, From Year 1 (May 1996-April 1997) to Year 3 (May 1998-April 1999) Age Group, y Race Year 3 Prescription Rate (per 1 Person-years) Percentage Change in Prescription Rates From Years 1 to 3 County Counties County Counties Intervention-Attributable Effect Percentage Change (95% Confidence Interval) P Value 1 White 238 236 8 1 2 ( 5 to 8).61 Black 182 2 19 3 16 ( 2 to 12).1 1to 5 White 222 25 22 14 8 ( 13 to 4).1 Black 137 133 2 2 18 ( 23 to 14).1 5to 15 White 127 11 17 14 3 ( 9 to 3).28 Black 53 5 25 5 2 ( 25 to 15).1 All ages ( to 15) Both 144 139 19 8 11 ( 14 to 8).1 ness visits by the person-years observed, and ratios of antibiotic prescriptions to the number of outpatient visits (ie, prescription to visit ratios) were examined as secondary outcome variables. Both were analyzed in a similar manner as described above for antibiotic prescription rates. The prevalence of resistance among S pneumoniae isolates from invasive infections occurring in County was calculated using the number of resistant isolates divided by the total number of isolates tested; these rates were expressed as percentages and stratified by study year and antibiotic category. P =.5 was the level of significance; basic analyses were performed using SAS Version 8.2 (SAS Institute Inc, Cary, NC). RESULTS The 3-year study encompassed 4642 person-years of observation representing 36% of all children younger than 15 years residing in the 4 study counties (Table 1). The average annual study population ranged from approximately 1 to 8 children per county per year. While the study populations were similar with regard to age and sex, the racial makeup differed substantially, consistent with underlying demographic differences among the counties; the County study population had the highest proportion of white children (73%), whereas Shelby County had the highest proportion of black children (9%). The total baseline (year 1) rates of antibiotic prescriptions and respiratory illness visits reflected the racial composition of each county s study population, with higher rates corresponding to higher proportions of white children (Table 1). For each of the 4 counties, both prescription and outpatient visit rates among white children were approximately twice as high as among black children. However, even when white and black children were examined separately, County s prescription and outpatient visit rates remained elevated relative to the control sites. Overall, antibiotic prescription rates declined 19% and 8% from year 1 to year 3 among County and control county children, respectively, yielding an 11% (95% confidence interval [CI], 8%- 14%) intervention-attributable decline (P.1) in prescriptions (TABLE 2). In County, prescription rates declined by 16% and 21% for white and black children respectively (FIGURE 1), with most of the decline occurring during year 2 when the intervention was conducted. Among controls, the decrease in prescription rates from year 1 to year 3 was more evident among white children (12%) than black children (3%). The changes in County s prescription rates exceeded these secular trends for black children (P.1) but not white children (P=.18). Antibiotic prescription rates in County and in the control counties decreased among all age and race groups examined (Table 2). These age-specific decreases were similar in magnitude among white and black children in County, but not in the control counties where the decrease was more pronounced among white children. The intervention s effect on prescription rates was significant (P.1) for black children in all 3 age groups (attributable decreases ranging from 16%-2%) and for white children in the 1- to less than 5-year age group (8% attributable decrease). The intervention-attributable effects, expressed in terms of their impact on baseline prescribing rates, were equivalent to decreases of 18 and 25 prescriptions per 1 child-years among white and black children aged 1 to less than 5 years, respectively. The observed changes in prescription rates did not appear to result from changes in respiratory illness visit rates; these rates were relatively stable during the 3-year study period (Figure 1), and there was no evidence of an unusual respiratory illness season among the study sites. The ratios of antibiotic prescriptions to respiratory illness visits were also examined (Figure 1). At baseline, the prescription to visit ratios were similar when comparing County and the control sites. During the intervention year, the prescription to visit ratio for both black and white children declined substantially in County, but not among the controls. By year 3 (postintervention), the prescription to visit ratio in County had decreased approximately 2% among both race groups; for black children the excess decline relative to the controls was 13% (P.1), while for white children it was 8% (P=.6). In the 1- to 4-year age group, the prescription to visit ratios declined significantly among both white children (11%, P=.2) and black children (17%, P.1). Use patterns for specific antibiotics were generally similar between 316 JAMA, June 19, 22 Vol 287, No. 23 (Reprinted) 22 American Medical Association. All rights reserved.

County and the control counties and for both white and black children (FIGURE 2). Overall, the majority of antibiotic prescriptions were for penicillins, and this proportion increased significantly (P.1) during the study period among black and white children in the intervention and control sites. Prescription rates among black and white children in County declined for all of the antibiotic categories examined. These declines were consistently greater among County children than among controls except for cephalosporins, which had a significantly greater decline in white children in the control counties. Resistance rates among isolates of invasive S pneumoniae occurring in County children remained high ( 5%) from year 1 through year 3 for all 4 antibiotic categories examined. Reductions in S pneumoniae resistance rates were not evident (TABLE 3). COMMENT County s public health community recognized the problem of antibiotic resistance and responded by conducting an educational intervention. Our evaluation used Medicaid data to demonstrate that antibiotic use declined substantially among County children in concert with the campaign. When control counties were examined, a secular downward trend in antibiotic prescription rates was documented; this finding is in agreement with other recent reports 31,32 and may reflect the impact of both national and local efforts to promote appropriate antibiotic use. In County, the reduced antibiotic prescribing was beyond that observed in the control counties, as demonstrated by 2 measures: population-based prescription rates and prescription to visit ratios. Since this study was not a controlled clinical trial, it is possible that the observed reduction in prescribing in County was due to other unmeasured factors or to the greater influence of temporal trends in a region with high baseline prescribing. However, the strong temporal association of the excess reduction in antibiotic prescribing that occurred coincident with the intervention confirmed our a priori hypothesis and suggests that this was indeed an effect of the intervention. To our knowledge, this is the first report to demonstrate reductions in pediatric antibiotic prescribing as a consequence of a community-wide educational intervention in a large urbanized setting. Of note, the magnitude of the intervention-attributable reductions in antibiotic prescription rates reported herein was similar to decreases reported in other recent interventions targeting pediatric antibiotic use. 17,18,32 Certain aspects of the intervention were noteworthy. The intervention was spearheaded by the local county health department and conducted on a limited budget using existing personnel. A coalition was developed that included key members of the local medical community. The educational efforts engaged both medical providers and parents, while also reaching the general public. Reductions in prescribing were sustained for at least 1 year after County s campaign ended, though the greatest effect occurred during the intervention year. Although encouraging, this suggests that interventions might need to be maintained over longer periods. The evaluation was limited to TennCare enrollees, which to some degree controlled for access to care and socioeconomic factors. The effect of the Figure 1. Measures of Antibiotic Prescription and Respiratory Illness Visit Use Among Pediatric Outpatients in County and the Counties, by Race Prescriptions per Visits per Ratio 2 2 16 2 2 16 1.2 1..8.6.4.2 4% ( 9% to 2%) 4% ( 8% to 16%) 8% ( 16% to %) White Children Year 1 Year 2 Year 3 Intervention Year Antibiotic Prescriptions 18% ( 2% to 16%) Respiratory Illness Outpatient Visits 5% ( 11% to 1%) Black Children Ratio of Antibiotic Prescriptions to Respiratory Illness Visits 13% ( 19% to 8%) Percentages indicate the point estimates and 95% confidence intervals for the intervention-attributable change in County rates from year 1 to year 3 relative to control counties. 22 American Medical Association. All rights reserved. (Reprinted) JAMA, June 19, 22 Vol 287, No. 23 317

Figure 2. Changes in Prescription Rates in County and the Counties, by Antibiotic Category and Race Antibiotic Prescriptions per Antibiotic Prescriptions per 1 6 2 1 6 2 Year 1 Year 3 Penicillins 4% ( 9% to 2%) Cephalosporins 11% (5% to 16%) White Children Trimethoprim- Sulfamethoxazole 5% ( 9% to 1%) Macrolides/Other 17% ( 36% to 3%) Penicillins 12% ( 19% to 6%) Cephalosporins 19% ( 21% to 18%) Black Children Trimethoprim- Sulfamethoxazole 3% ( 47% to 13%) Macrolides/Other 32% ( 64% to 1%) Percentages indicate point estimates and 95% confidence intervals for the intervention-attributable change in County rates from year 1 to year 3 relative to control counties. Table 3. Antibiotic Susceptibilities Among Isolates of Invasive Streptococcus pneumoniae From Pediatric Patients Younger Than 15 Years Residing in County Proportion Resistant, % Year 1 Year 2 Year 3 Antibiotic (n = 2) (n = 34) (n = 34) Penicillin 6 74 71 Cefotaxime 55 68 59 Trimethoprimsulfamethoxazole 6 71 65 Erythromycin 55 62 5 intervention on children of higher socioeconomic status, is not known. On the other hand, the study population was large and represented a substantial portion of the total pediatric population. Also, the exact mechanism by which prescription rates were lowered in County could not be ascertained. Although prescriptions were not linked to actual visits, the prescription to visit ratio provided a measure of the likelihood that a respiratory illness encounter resulted in an antibiotic prescription. The decreased ratios of prescriptions to visits suggest that, as a result of the educational intervention, County physicians adopted more stringent criteria for writing antibiotic prescriptions and/or that parents expectations for receiving prescriptions was reduced. The intervention effect was greater among black children, even though their baseline antibiotic prescription rates were lower. White children received care for respiratory illnesses approximately twice as often as black children. Higher rates of ambulatory health care among white children for otitis media and other respiratory conditions have been described previously. 33,34 The reasons why white children received physician care for respiratory illnesses more often than black children in our study are unknown and could not be examined directly. Because this study included only children who were covered by TennCare, differences in access to care should have been minimized. Antibiotic prescription rates also were approximately twice as high among white children as black children. Consequently, much of the observed excess in antibiotic prescribing at the intervention site appeared to be caused by the high proportion of white children in County. Within County, and among the control sites, prescribing levels among black and white children were similar when differences in respiratory illness visit rates were accounted for. These data indicate a need to examine the appropriateness of different levels of antibiotic and ambulatory care use. Younger children have the highest rates of antibiotic use. 12 For example, prescription rates among children aged 1 to less than 5 years were approximately twice as high as among children aged 5 to less than 15 years in our study. Therefore, educational interventions should target the parents of preschoolers, as was done in County. In fact, the largest intervention effects in County were observed among children aged 1 to less than 5 years. The correlation between levels of ambulatory care visits and antibiotic prescriptions identified in our study suggests that the provider visit itself could be a driving force behind antibiotic prescribing. In other words, unnecessary office visits might precipitate unnecessary prescriptions. 35-37 Therefore, more attention should be given to the education of parents and child care center personnel regarding the appropriate indications for seeking physician care and antibiotic treatment for children with acute respiratory illnesses. Among this study population, a general decline occurred across antibiotic categories. A primary message of this intervention was that narrow-spectrum antibiotics should be used preferentially. Our data indicated that even before the 318 JAMA, June 19, 22 Vol 287, No. 23 (Reprinted) 22 American Medical Association. All rights reserved.

intervention, narrow-spectrum penicillins dominated antibiotic use and that, during the study period, the proportion of antibiotic use accounted for by penicillins increased. Limited data were available regarding resistance among invasive S pneumoniae isolates among County children. There was no indication of any decrease in pneumococcal resistance 1 year after the County intervention; however, the sample size limited our ability to detect modest changes in resistance. It is likely that further sustained reductions in antibiotic use will be required to lower the prevalence of antibiotic resistance among S pneumoniae and other communityacquired bacterial pathogens. Clonal spread of resistant strains is thought to contribute to their persistence after introduction to a community, 1 and substantial time lags are expected to accompany their disappearance. 38 A national action plan to address the problem of antibiotic-resistant infections in the United States was recently developed by a governmental task force. 5,39 Educational interventions to counter the development and spread of microbial resistance through promotion of responsible antibiotic use were identified as essential to this plan. The decline in antibiotic prescribing documented after the County intervention should encourage these broader efforts. Author Contributions: Study concept and design: Perz, Craig, Coffey, Hall, Schaffner, Griffin. Acquisition of data: Perz, Jorgensen, Mitchel, Schaffner, Griffin. Analysis and interpretation of data: Perz, Craig, Coffey, Mitchel, Hall, Schaffner, Griffin. Drafting of the manuscript: Perz, Coffey, Mitchel, Schaffner, Griffin. Critical revision of the manuscript for important intellectual content: Perz, Craig, Coffey, Jorgensen, Hall, Schaffner, Griffin. Statistical expertise: Coffey. Obtained funding: Schaffner, Griffin, Craig. Administrative, technical, or material support: Perz, Jorgensen, Mitchel, Hall, Schaffner, Griffin, Craig. Study supervision: Craig, Schaffner, Griffin. Funding/Support: This work was supported in part by cooperative agreements UR6 CCU417579 and U5/CCU416123 with the Centers for Disease and Prevention. Acknowledgment: We are indebted to Richard E. Besser, MD, Laura J. Fehrs, MD, and Kathryn M. Edwards, MD, for their comments; to Paul C. Erwin, MD, MPH, members of the East Tennessee Drug Resistance Task Force, and personnel from the County Health Department for their contributions to the intervention; and to the Active Bacterial Core Surveillance program for providing S pneumoniae resistance data. REFERENCES 1. Schrag SJ, Beall B, Dowell SF. Limiting the spread of resistant pneumococci. Clin Microbiol Rev. 2; 13:588-61. 2. Whitney CG, Farley MM, Hadler J, et al. Increasing prevalence of multidrug-resistant Streptococcus pneumoniae in the United States. N Engl J Med. 2; 343:1917-1924. 3. Levy SB. Antibiotic resistance: an ecological imbalance. Ciba Found Symp. 1997;27:1-9. 4. Wenzel RP, Edmond MB. Managing antibiotic resistance. N Engl J Med. 2;343:1961-1963. 5. Bell DM. Promoting appropriate antimicrobial drug use: perspective from the Centers for Disease and Prevention. Clin Infect Dis. 21;33(suppl 3): S245-S25. 6. Dowell SF, Marcy SM, Phillips WR, Gerber MA, Schwartz B. Principles of judicious antimicrobial agents for pediatric upper respiratory tract infections. Pediatrics. 1998;11:163-165. 7. Jernigan DB, Cetron MS, Breiman RF. Minimizing the impact of drug-resistant Streptococcus pneumoniae (DRSP). JAMA. 1996;275:26-29. 8. Schwartz B, Bell DM, Hughes JM. 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