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Trends in antibiotic utilization in eight Latin American countries, 1997-2007 Translated title: Tendencias en el consumo de antibióticos en ocho países latinoamericanos entre 1997 y 2007
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March 2010
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Organización Panamericana de la Salud
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Abstract
OBJECTIVE: To describe the trends in antibiotic utilization in eight Latin American countries between 1997-2007 METHODS: We analyzed retail sales data of oral and injectable antibiotics (World Health Organization (WHO) Anatomic Therapeutic Chemical (ATC) code J01) between 1997 and 2007 for Argentina, Brazil, Chile, Colombia, Mexico, Peru, Uruguay, and Venezuela. Antibiotics were aggregated and utilization was calculated for all antibiotics (J01); for macrolides, lincosamindes, and streptogramins (J01 F); and for quinolones (J01 M). The kilogram sales of each antibiotic were converted into defined daily dose per 1 000 inhabitants per day (DID) according to the WHO ATC classification system. We calculated the absolute change in DID and relative change expressed in percent of DID variation, using 1997 as a reference RESULTS: Total antibiotic utilization has increased in Peru, Venezuela, Uruguay, and Brazil, with the largest relative increases observed in Peru (5.58 DID, +70.6%) and Venezuela (4.81 DID, +43.0%). For Mexico (-2.43 DID; -15.5%) and Colombia (-4.10; -33.7%), utilization decreased. Argentina and Chile showed major reductions in antibiotic utilization during the middle of this period. In all countries, quinolone use increased, particularly sharply in Venezuela (1.86 DID, +282%). The increase in macrolide, lincosaminde, and streptogramin use was greatest in Peru (0.76 DID, +82.1%), followed by Brazil, Argentina, and Chile CONCLUSIONS: Analyzing antibiotic utilization in Latin America presents a series of challenges. Creating policy-relevant evidence based on antimicrobial consumption patterns is needed in order to foster policies aimed at improving appropriate use of antibiotics in the region.
Translated abstract
OBJETIVO: Describir las tendencias en el consumo de antibióticos en ocho países latinoamericanos entre 1997 y el 2007. MÉTODOS: Se analizaron los datos de las ventas al por menor de antibióticos orales e inyectables (Código J01 de la clasificación anatómica, terapéutica y química [ATC] de la Organización Mundial de la Salud [OMS]), entre 1997 y el 2007, en Argentina, Brasil, Chile, Colombia, México, Perú, Uruguay y Venezuela. Se consolidaron los datos correspondientes a todos los antibióticos y se calculó el consumo de todos los antibióticos (J01); los macrólidos, lincosamidas y estreptograminas (J01 F); y las quinolonas (J01 M). Las ventas de cada antibiótico expresadas en kilogramos se convirtieron en dosis diarias definidas por 1 000 habitantes por día (DHD), según el sistema de clasificación anatómica, terapéutica y química de la OMS. Calculamos la variación absoluta de los valores de las DHD y la variación relativa, expresada en porcentaje de variación de las DHD, adoptando como referencia los datos correspondientes a 1997. RESULTADOS: El consumo total de antibióticos ha aumentado en Perú, Venezuela, Uruguay y Brasil, observándose los mayores incrementos relativos en Perú (5,58 DHD, +70,6%) y Venezuela (4,81 DHD, +43,0%). En México (-2,43 DHD; -15,5%) y Colombia (-4,10 DHD; -33,7%), el consumo ha disminuido. En Argentina y Chile se observaron grandes reducciones en el consumo de antibióticos a mediados de este período. En todos los países, aumentó el consumo de quinolonas, de forma particularmente pronunciada en Venezuela (1,86 DHD, +282%). El mayor aumento del consumo de macrólidos, lincosamidas y estreptograminas se observó en Perú (0,76 DHD, +82,1%), seguido de Brasil, Argentina y Chile. CONCLUSIONES: El análisis del consumo de antibióticos en América Latina plantea una serie de retos. Es preciso obtener datos probatorios sobre las pautas de consumo de fármacos antimicrobianos que sean pertinentes para la formulación de políticas con objeto de fomentar las que estén orientadas hacia un uso más apropiado de los antibióticos en la Región.
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Antimicrobial Drug Use and Resistance in Europe
For the past 60 years, antimicrobial chemotherapy has been the mainstay of medical intervention against infectious diseases caused by bacterial pathogens. The continuous decline of therapeutic effectiveness as a result of extensive use of antimicrobial chemotherapy has been long predicted and seems inescapable ( 1 ). Many surveillance efforts have over the last decade (1997–2007) drawn attention to this phenomenon ( 2 – 5 ). At the same time, the once-abundant supply of new and improved antimicrobial compounds has worn thin, as drug development becomes increasingly challenging and pharmaceutical companies invest in more lucrative markets ( 6 ). It is therefore critical to realize that antimicrobial drug effectiveness, widely accepted as a common good, cannot be taken for granted and that such substances are increasingly attaining the status of nonrenewable resources. Our study confronts the population-adjusted use of antimicrobial agents in ambulatory care with the resistance trends of 3 compound pathogen combinations in 21 European countries over a period of 6 years (2000–2005). This initial study was made possible by combining data from the 2 most comprehensive European surveillance systems on antimicrobial drug consumption and resistance, the European Surveillance of Antimicrobial Consumption (ESAC) ( 7 ) and the European Antimicrobial Resistance Surveillance System (EARSS) ( 8 ). We present an authoritative joint analysis of these 2 comprehensive databases. At this highly aggregated level, data are not sensitive enough to unravel the complex interaction between prescribing and resistance. The goal of this study is to give an overview of the situation in the European region and explore whether a relationship between antimicrobial drug use and resistance can be supported by empirical data pooled at national levels. Materials and Methods Consumption of Antimicrobial Agents ESAC collects data on antimicrobial drug use in ambulatory care and hospital care in Europe. Currently, 24 countries report data on ambulatory care consumption to ESAC ( 9 ). Prescribed drugs are grouped by the active substance as the number of defined daily doses (DDD) per 1,000 inhabitants (DID) according to the World Health Organization definition of Anatomical Therapeutic Chemical Classification (ATC) defined daily dose (ATC-DDD version 2005 ( 10 ). A complete description of the data providers and details of the methods used by ESAC have been published ( 7 , 11 , 12 ). The performance and methodologic approach of the ESAC system, which aimed to collect comparable and reliable data on antimicrobial drug use, were studied by Vander Stichele et al. ( 7 ). The collected data were screened for bias caused by errors in assigning medicinal product packages to the ATC; errors in calculations of DDD per package; bias by over-the-counter sales and parallel trade; and bias in ambulatory care/hospital care mix. The study indicated that of the 31 participating countries, 21 delivered ambulatory care data suitable for cross-national comparison ( 7 ). For the present study, the total country-specific antimicrobial drug use in ambulatory care and a breakdown into the following major antimicrobial classes were extracted from the ESAC database: penicillins (J01C); other β-lactam antimicrobial agents (cephalosporins, monobactams and carbapenems, J01D); macrolides, lincosamines, and streptogramins (MLS-class, J01F); and fluoroquinolones (J01MA). Resistance to Antimicrobial Agents EARSS performs continuous surveillance of antimicrobial drug susceptibility for 7 major bacterial pathogens that cause invasive infections. Data are provided by >900 microbiologic laboratories that serve ≈1,400 hospitals from 32 countries with an overall hospital catchment population estimated to include >100 million inhabitants ( 13 ). All EARSS participating laboratories perform routine antimicrobial drug susceptibility tests according to standard protocols ( 14 ) and interpret their susceptibility results according to harmonized national and international guidelines as sensitive, intermediately resistant, and resistant ( 15 ). More details about the data acquisition and analysis have been published elsewhere ( 13 , 16 , 17 ). The antimicrobial susceptibility test (AST) results reported by the laboratories are collected by using standardized protocols as described in the EARSS manual (www.rivm.nl/earss). Data that do not meet the requirements of these species-specific protocols are not accepted. To assess the comparability of results between laboratories participating in EARSS, an external quality assessment exercise is organized every year. A set of 6 strains is provided to each laboratory in collaboration with the UK National External Quality Assurance Scheme. These exercises illustrate that routinely reported results, as collected by EARSS, have sufficient accuracy to provide good estimates of overall resistance prevalences and trends ( 18 ). For the present study, AST results of primary blood culture isolates of Escherichia coli and Streptococcus pneumoniae were extracted from the EARSS database to determine the proportions of penicillin- and erythromycin-nonsusceptible S. pneumoniae (PNSP and ENSP, respectively) and proportions of fluoroquinolone-resistant Escherichia coli (FQRE) bacteria. Nonsusceptible isolates included both intermediate resistant and resistant isolates. A country-specific resistance score was calculated as the sum of the quartile ranks of resistance against all 3 compound pathogen combinations (PNSP, ENSP, and FQRE). For trend analysis of resistance proportions per country over time, the Cochrane-Armitage trend test was used. Ecologic Analysis The strength of association between antimicrobial drug use and resistance was determined by univariate and multiple linear regression analysis. The proportion of resistance (R) in a country was transformed to the natural logarithm of the odds of resistance (ln[R/1–R]), to get a range from –∞ to +∞. The log odds of resistance (as the dependent variable) can then be expressed as a simple linear function of the independent variable (consumption) ( 19 , 20 ). To give equal weight to small countries with flawless data collection and not give the unequal weight to larger countries with sometimes less-optimal data, the linear regression analysis was not weighed. To determine the delay between antimicrobial use and resistance, proportions of PNSP, ENSP, and FQRE for 2002–2005 were correlated with the consumption of different antimicrobial drug classes in the same year and the 2 years before. This resulted in 11 different exposure-outcome intervals for each compound–pathogen combination. For further multivariate analysis, the interval with the median correlation coefficient was regarded as representative for the association found in the overall study period. Only the countries that reported volumes of antimicrobial drug prescriptions in ambulatory care from 2000 through 2004 and susceptibility data for the selected compound–pathogen combinations from 2002 through 2005 were included for linear regression analysis. Countries that provided yearly susceptibility data for 15% increase >15% decrease Total use (J01) 33.4(GR) 9.7 (NL) 3.4 HU, DK, GR, IE BG, CZ, DE, FR Penicillins (J01C) 12.8 (FR) 3.4 (DE) 3.8 HU, DK CZ, FR, DE, SK Cephalosporins, monobactams, carbapenems (J01D) 7.2 (GR) 0.05 (NL) >100 SI BE, BG, CZ, FR, IS NL, ES, SE Macrolides, lincosamines, streptogramins (J01F) 9.9 (GR) 0.8 (BG) 12.4 BG, HR, GR, IE, NL BE, FR, DE, LU, ES Fluoroquinolones (J01MA) 3.04 (PT) 0.28 (DK) 10.9 AT, BG, CZ, DK, FI, DE, HU, IE, LU, UK SI *DID, defined daily dose/1,000 inhabitants; ATC, Anatomic Therapeutic Chemical classification; fd, factor difference.
†Country designations: AT, Austria; BE, Belgium; BG, Bulgaria; CZ, Czech Republic; DE, Germany; DK, Denmark; ES, Spain; FI, Finland; FR, France; GR, Greece; HR, Croatia; HU, Hungary; IE, Ireland; LU, Luxembourg; NL, the Netherlands; PT, Portugal; SE, Sweden; SI, Slovenia; SK, Slovakia; UK, United Kingdom. During the observation period (2000–2004), antimicrobial drug use decreased (>15%) in Bulgaria, Czech Republic, France, and Germany and increased (>15%) in Croatia, Denmark, Greece, and Ireland. Penicillins (including broad-spectrum penicillins, ATC category J01C) represented the most widely used antimicrobial class in Europe. This class showed consumption patterns similar to the total outpatient antimicrobial drug use, as did the second most widely used category, which consists mainly of macrolides but also includes lincosamines and streptogramins (MLS class, ATC category J01F). The third most widely used ATC category (J01D, other β-lactams) consists of cephalosporins, monobactams, and carbapenems. Cephalosporins make up the bulk of the antimicrobial agents included in this group. Antimicrobial agents belonging to this category are more commonly used in hospitals; however, in some countries they are also extensively prescribed in ambulatory care. For this reason, use rates in Europe varied >100-fold between countries. The use of this ATC category decreased by >15% in 8 countries but increased in Slovenia. Fluoroquinolones hold the fourth position in the European market but showed the most dynamic increase, with growth rates of >15% in almost half of all countries (10/21). In terms of overall control of antimicrobial drug consumption, France most consistently reduced its use of 3 of the 4 most frequently prescribed antimicrobial drug classes (Figure 1, Table 1). Resistance to Antimicrobial Agents Large differences in the proportions of resistance were reported for the same countries. The highest antimicrobial drug resistance was found in Spain, Hungary, and France and the lowest in Sweden and the Netherlands in 2005 (Figure 2). Resistance proportions in 2005 differed by a factor of 27.7 for PNSP between France (36%) and the Netherlands (1.3%), by 20.5 for ENSP between France (41%) and the Czech Republic (2%), and by 9.7 for fluoroquinolone resistance in E. coli between Portugal (29%) and Iceland (3%). From 2001 through 2005, resistance levels remained relatively stable for PNSP but increased for the other 2 compound pathogen combinations (Table 2). Spain and the United Kingdom were the only countries that reported any significant decrease in antimicrobial drug resistance rates. In Spain, penicillin nonsusceptibility fell from 37% to 25% and in the United Kingdom, from 5% to 3.8%. For ENSP a significant increase was observed in Hungary (from 19% to 37%), Finland (from 12% to 20%), and the Netherlands (5% to 11%). The most consistent trend was observed for fluoroquinolone resistance in E. coli, which increased in most European countries (Table 2). Figure 2 Proportion of penicillin-nonsusceptible Streptococcus pneumoniae (PNSP), erythromycin-nonsusceptible S. pneumoniae (ENSP), and fluoroquinolone-resistant Escherichia coli (FQRE) in 2005, ranked in descending order by country-specific resistance score indicated above bars. *For Greece and Slovakia, data on S. pneumoniae resistance were not available. Country (total no. of S. pneumoniae isolates reported/ total no. of E. coli isolates reported): ES (740/2993); HU (86/468); FR (632/6028); LU (43/188); PT (202/1086); BE (1539/1461); BG (43/196); DE (119/957); HR (129/637); IE (397/1411); AT (290/2049); FI (525/1743); SI (208/657); CZ (194/2233); UK (1373/2359); IS (23/46); DK (1081/1283); NL (802/2140); SE (1017/3035); GR (0/1136); SK (0/132). See Table 1 footnote for country designations. Table 2 Differences in the proportion of antimicrobial drug resistance in 21 European countries, 2005, and significant trends, 2001–2005 Compound-pathogen† Antimicrobial drug resistance Europe, %, 2005 Trends, 2001–2005* Maximum (country) Minimum (country) fd‡ Increase (p<0.05) Decrease (p<0.05) PNSP 36 (FR) 1.3 (NL) 27.7 BG ES, UK ENSP 41 (FR) 2 (CZ) 20.5 FI, HU, NL FQRE 29 (PT) 3 (IS) 9.7 AT, BE, BG, CZ, DE, ES, FI, HR, HU, LU, NL, PT, SE *No trend analysis was performed for Denmark and France, and for Ireland and the United Kingdom for proportion of Escherichia coli resistant to fluoroquinolones (FQRE), because data were not available for all years of the study period (2001–2005). See Table 1 footnote for country designations.
†PNSP, proportion of Streptococcus pneumoniae not susceptible to penicillin; ENSP, erythromycin-nonsusceptible S. pneumoniae.
‡fd, factor difference. Combining Antimicrobial Drug Use with Susceptibility Data Greece (33.0 DID), France (27.1 DID), Luxembourg (24.2 DID), Portugal (23.8 DID), Croatia (23.0 DID), and Belgium (22.9 DID) were the countries that reported the highest use of antimicrobial agents in ambulatory care. Four of these high-consumer countries—France, Luxemburg, Belgium, and Portugal—were also among the 6 countries with the highest resistance proportions. Croatia occupied an intermediate resistance rank, owing to more modest levels in fluoroquinolone resistance. For Greece, susceptibility data for S. pneumoniae were not available, which precluded a meaningful ranking. Although Spain (18.7 DID) and Hungary (18.6 DID) were not among the countries with the highest use of antimicrobial agents, both countries did have the highest antimicrobial drug resistance proportions in 2005. The United Kingdom (15.2 DID), Sweden (15 DID), Denmark (14.1 DID), Austria (12.5 DID), Germany (11 DID), and the Netherlands (10 DID) reported the lowest antimicrobial drug use in outpatient settings. Of these, Sweden, the Netherlands, Denmark, and the United Kingdom also were among the 6 countries with the lowest resistance proportions. Germany and Austria reported medium to high rates especially for ENSP (17% and 15%, respectively) and FQRE (23% and 19%, respectively) (Figures 1, 2). Because inspection of the data suggested a relation between antimicrobial drug consumption and resistance, this assumption was formally tested by using simple linear regression. Because little is known about the delay that can be expected between the change in antimicrobial drug exposure and its effect on antimicrobial resistance at a population level, different intervals were chosen to explore the potential association between use and resistance. Intervals were explored for same-year data, a 1-year delay, and a 2-year delay between exposure and outcome. Thus, the consumption data available for 2000 through 2004 and resistance data for 2002–2005 provided the means to explore the correlation coefficients of 11 exposure-outcome intervals. Only the 17 countries that provided data for all years were included in the linear regression analysis. Table 3 shows the range and median correlation coefficient for all exposure-outcome intervals. Since no statistically significant time dependence was observed, the median correlation coefficient was regarded as representative for the association found for the entire study period (Table 3). Table 3 Range and median correlation between the occurrence (logodds) of PNSP, ENSP, and FQRE in 2002–2005 and antimicrobial drug consumption, Europe, 2000–2004* E consumption O-resistance phenotype No. E–O intervals with significant association† Correlation coefficients (r) Median Minimum Maximum r (CI) E–O year r (CI) E–O year r (CI) E–O year Total use (J01) PNSP 11 0.68
(0.30–0.87) 2003–2003 0.61
(0.17–0.84) 2001–2003 0.73
(0.39–0.90) 2002–2002 ENSP 9 0.55
(0.07–0.82) 2001–2003 0.37
(–0.11 to 0.75) 2004–2005 0.71
(0.33–0.89) 2003–2003 Penicillins (J01C) PNSP 11 0.78
(0.48–0.92) 2003–2004 0.69
(0.28–0.87) 2003–2005 0.82
(0.55–0.93) 2004–2004 ENSP 3 0.37
(–0.15 to 0.74) 2003–2005 0.26
(–0.29 to 0.66) 2001–2002 0.60
(0.15–0.84) 2003–2003 Cephalosporins, monobactams, carbapenems (J01D) PNSP 8 0.57
(0.13–0.83) 2002–2003 0.41
(–0.07 to 0.74) 2002–2004 0.64
(0.23–0.86) 2000–2002 ENSP 11 0.69
(0.30–0.88) 2001–2002 0.50
(0.00–0.79) 2003–2005 0.79
(0.48–0.92) 2004–2004 Macrolides, lincosamides, streptogramins (MLS class J01F) PNSP 4 0.42
(–0.08 to 0.75) 2004–2004 0.26
(–0.22 to 0.67) 2004–2005 0.53
(0.07–0.81) 2002–2002 ENSP 9 0.56
(0.08–0.82) 2001–2002 0.35
(–0.19 to 0.71) 2004–2004 0.67
(0.27–0.88) 2003–2004 Fluoroquinolones (JO1MA) PNSP 9 0.51
(0.04–0.80) 2004–2004 0.36
(–0.10 to 0.74) 2003–2005 0.57
(0.12–0.82) 2002–2002 ENSP 10 0.62
(0.18–0.85) 2001–2002 0.48
(–0.04 to 0.78) 2004–2005 0.69
(0.29–0.89) 2004–2004 FQRE‡ 9 0.60
(0.17–0.84) 2004–2004 0.44
(–0.05 to 0.76) 2003–2005 0.70
(0.33–0.88) 2001–2002 *PNSP, penicillin-nonsusceptible Streptococcus pneumoniae; ENSP, erythromycin-nonsusceptible S. pneumoniae; FQRE, fluoroquinolone-resistant Escherichia coli; E, exposure; O, outcome; CI, 95% confidence interval; MLS, macrolides, lincosamines, and streptogramins.
†Exposure outcome intervals include all 11 possible time windows, considering the data for consumption (exposure) and resistance (outcome) for the same year as well as for intervals of 1 to 2 y between exposure and outcome. p<0.05 was significant.
‡Significant correlations of fluoroquinolone consumption were found only with FQRE. Other correlations were therefore not shown. The occurrence of PNSP in European countries correlated with the country-specific use of penicillins, which explained 61% of the observed variance (p<0.01) (Figure 3). The second best correlation was provided by the total antimicrobial drug use in ambulatory care, which explained 46% of the observed variance (p<0.01). Both associations were robust and remained significant, regardless of the interval between the ascertainment of antimicrobial drug use and the recording of antimicrobial resistance. A notably less consistent association was found when we correlated the use of MLS-class antimicrobial agents or fluoroquinolones with the occurrence of PNSP (Table 3). ENSP occurrence in Europe correlated most compellingly with the country-specific use rate of ATC category J01D (other β-lactams), which explained 48% of the observed variance (p<0.01) (Table 3). However, this effect appeared to be confounded by the use of MLS-class antimicrobial agents and fluoroquinolones. By fitting use data for these antimicrobial agents into the model, the effect estimates for the former decreased by 40% (Table 4), indicating that part of the effect attributed to the use of other β-lactam antimicrobial agents appeared to be exerted by MLS-class antimicrobial agents and fluoroquinolones. Figure 3 Occurrence of penicillin-nonsusceptible Streptococcus pneumoniae (PNSP) plotted against outpatient use of penicillins in 17 European countries including 95% confidence intervals. DID, defined daily doses per 1,000 inhabitants. See Table 1 footnote for country designations. Table 4 Results of multiple linear regression for the occurrence of PNSP and ENSP* Models Outcome variable: logodds PNSP Exposure Parameter estimate p value R 2 Model 1 Intercept –4.75 Gradient Penicillins 0.29 0.0002 0.61 Model 2 Intercept –4.8 Gradient Penicillins 0.33 0.002 Other β-lactams –0.05 0.808 Fluoroquinolones –0.11 0.73 0.62 Outcome variable: logodds ENSP Model 1 Intercept –2.82 Gradient Other β-lactams 0.41 0.003 0.48 Model 2 Intercept –3.26 Gradient Other β-lactams 0.25 0.14 MLS class 0.15 0.39 Fluoroquinolones 0.30 0.35 0.56 *PNSP, penicillin-nonsusceptible Streptococcus pneumoniae; ENSP, erythromycin-nonsusceptible S. pneumoniae; MLS, macrolides, lincosamines, and streptogramins. Proportions of FQRE in European countries were best explained by the country-specific use data for fluoroquinolones. Fluoroquinolone consumption as reported to the ESAC network explained 36% of the variance observed in EARSS data (p<0.01; Figure 4). This effect appeared to be specific and was not associated or confounded by consumption of the other antimicrobial classes. Figure 4 Occurrence of fluoroquinolone-resistant Escherichia coli (FQRE) plotted against outpatient use of fluoroquinolone antimicrobial agents in 17 European countries including 95% confidence intervals. DID, defined daily doses per 1,000 inhabitants. See Table 1 footnote for country designations. Discussion We compared the trends in antimicrobial drug consumption patterns and the antimicrobial drug resistance proportions for 2 major pathogens, S. pneumoniae and E. coli, in Europe from 2000 through 2005. Antimicrobial drug use in outpatient settings was ascertained by the most comprehensive network for European surveillance of antimicrobial consumption (ESAC), and antimicrobial resistance data were obtained from the European surveillance system EARSS). The data suggested that in Europe the variation of consumption coincides with the occurrence of resistance at country level. Using simple linear regression analysis, we formally explored whether a relation between country-specific antimicrobial drug use and antimicrobial resistance can be inferred at national aggregation levels and found that the association between antimicrobial drug use and resistance was specific and robust for 2 of the 3 compound pathogen combinations under study, stable over time, but not sensitive enough to explain all of the observed variation. There was a high degree of consistency between penicillin use and penicillin nonsusceptibility in pneumococci as well as for fluoroquinolone use and an increase in fluoroquinolone resistance in E. coli. Simple linear regression showed that these effects were highly specific and robust, as inclusion of the use of other antimicrobial substances did not improve correlation or was not confounding the overall effect estimates (Tables 3, 4; Figures 3, 4). The mechanisms for acquiring resistance against both substances have some features in common. These include successive alterations of chromosomally located genes by either homologous recombination or point mutations, resulting in a stepwise modification of the molecular targets, which first leads to reduced susceptibility and eventually to complete resistance ( 21 , 22 ). In contrast to many other resistance mechanisms, no mobile genetic elements are involved, and a physical linkage to other resistance determinants is unlikely. It is therefore expected that before phenotypes with stable combined resistance evolve, antimicrobial drug selection will specifically favor homologous resistance. A nonhomologous effect was observed in the case of ENSP, since the variance in ENSP occurrence was best explained by the country-specific use rates of the ATC category of other β-lactams, consisting mainly of cephalosporins. This observation could be either causal, coincidental, or both. In fact, the results of multiple regression models indicate a degree of confounding, as part of the effect attributed to other β-lactams could be explained by MLS-class antimicrobial agents and fluoroquinolones (Table 4). This confounding effect implies that the effect of other β-lactams is mixed with the effect of MLS-class antimicrobial agents and fluoroquinolones used. Data recorded by ESAC suggest that most countries with high use of other β-lactams also have a high consumption of MLS-class antimicrobial agents (r = 0.78, p<0.01) as well as fluoroquinolones (r = 0.65, p<0.01). Moreover, countries with the highest levels of other β-lactam use—such as Luxembourg, Croatia, Portugal, Belgium, and France—and high levels of ENSP (23%, 19%, 20%, 31%, and 41%) also reported high levels of combined nonsusceptibility to both erythromycin and penicillin (12%, 9%, 10%, 9%, and 32%). Any increase in selection pressure exerted by β-lactams would also co-select for ENSP under these conditions of combined nonsusceptibility, which could also explain the absence of a direct relationship between use of MLS-class antimicrobial agents and ENSP. For all compound pathogen combinations that showed significant correlations, the association between the volume of antimicrobial agents used and proportions of resistance was for the most part stable, i.e., independent of the time lag between recording of consumption and the recording of resistance (Table 3). This is not surprising because in the absence of nationwide interventions that would abruptly change the use pattern for an entire country, no major trend changes would be expected, or as other authors have already stated, it is likely that a country with more use or resistance than others in one year, will also have more use or resistance in the next ( 19 ). Likewise, the steady decline in the consumption in some of the antimicrobial drug classes such as penicillins, as happened in the Czech Republic, France, Germany, and Slovakia, was not reflected by a concomitant decline of penicillin resistance in the pathogens under selective pressure. Mathematical models as well as empirical data suggest that after a reduction in prescribing, resistance will take longer to decline than it took to rise ( 23 ). In the same way, no decline in resistance against co-trimoxazole was observed in the United Kingdom even 10 years after it abandoned its prescribing, which in this instance was attributed to the co-selection of genetically linked resistance determinants by alternative antimicrobial pressure ( 24 ). EARSS data show a significant reduction of penicillin resistance in Spain ( 25 ) and the United Kingdom over the past 5 years (2001–2005), however, no corresponding decline in penicillin use has become apparent that could explain this favorable development (Tables 1, 2). Alternatively, data aggregated at country level by established surveillance networks may not be sensitive enough to identify subtle changes in the complex interaction between antimicrobial drug prescribing and resistance. EARSS data consist of antimicrobial drug resistance proportions of bacteria that cause invasive bloodstream infections but do not include information from other potentially relevant patient materials. This omission limits the wealth of data but improves the comparability between participating laboratories because it reduces bias introduced by differential case ascertainment. S. pneumoniae is the main cause of community-acquired bacteremic pneumonia ( 26 ), and invasive E. coli infections are mainly caused by the translocation of intestinal colonizing strains ( 27 ). Thus, we believe that resistance among S. pneumoniae and E. coli blood culture isolates would sufficiently reflect the ecological pressure exerted by the antimicrobial drug use in outpatient settings. There is little doubt that antimicrobial drug consumption is important in the dissemination of antimicrobial drug resistance. However, additional or alternative factors need to be taken into account ( 28 ). We could not control for country-specific differences in hygiene, diagnostic habits, community infection control, and vaccination policies that could provide alternative explanations for some of the observed differences. Moreover, inconsistencies in the sampling population covered by the 2 surveillance systems may introduce inaccuracies that hamper the internal validity of this type of analysis ( 29 ). In general, data at this high aggregation level are probably not sensitive enough to reflect subtle changes in the complex interaction between antimicrobial drug prescribing and resistance. In this respect, increasing the geographic resolution of data collection by addressing antimicrobial drug use and resistance at the level of health districts would improve the analysis and degree of causal inference that these studies could provide. A higher geographic resolution could also foster interventions by making local extremes of use apparent. However, despite these drawbacks, the data suggest that a specific, robust, and stable association exists between antimicrobial drug use and the occurrence of resistance at country level in the European Union. Our results therefore support interventions that encourage healthcare professionals and healthcare authorities to take firm steps toward promoting prudent use and careful restriction of antimicrobial drug prescription and to monitor the effect of these interventions toward the restoration of the antiinfective activity essential to the success of modern medicine.
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Significant Reduction of Antibiotic Use in the Community after a Nationwide Campaign in France, 2002–2007
Elifsu Sabuncu, Julie David, Claire Bernede-Bauduin … (2009)
Introduction The emergence and the dissemination of drug-resistant bacterial strains make treatment decisions challenging and may be associated with treatment failures. This phenomenon has become a major public health issue. Streptococcus pneumoniae is the most commonly identified bacterial cause of community-acquired invasive infections and pneumonia [1],[2]. Multidrug-resistant pneumococci (MRP) are now ubiquitous, despite the recent availability and now wide use of 7-valent pneumococcal conjugate vaccine (7-PCV) in developed countries, with more infections being caused by nonvaccine serotypes [3]. Very few new antimicrobial drugs are expected to become available in the near future, and several studies support the notion that antibiotic consumption is a key driving force in the rate (number of resistant isolates/total number of isolates) of beta-lactam–resistant pneumococci [4] and in the dissemination of MRP [5]–[7]. Furthermore, there is some evidence that decreasing antibiotic use can lower MRP rates [8]. For instance, the highest MRP rates are reported in southern Europe [9], southeastern Asia [10], and North America [11], where antibiotic consumption is generally higher than in northern Europe [12]. Thus, many countries have undertaken public health programs to optimize antibiotic prescriptions in the community [13]. In the early 2000s, France, a country with nearly 62,000,000 inhabitants and nearly 54,000 general practitioners, faced growing problems with MRP, with >50% of strains showing decreased penicillin G susceptibility. France was also identified as the country with the highest antibiotic consumption in Europe [12] and one of the highest antimicrobial users worldwide. Thus, the French government initiated a long-term nationwide campaign to reduce antibiotic overuse and control the dissemination of resistant bacteria in the community. The national program, named “Keep Antibiotics Working,” was launched in 2001, targeting both the general public and health care professionals, to encourage surveillance of antibiotic use and resistance and to promote better-targeted antibiotic use. Since 2002, a public service campaign entitled “Les antibiotiques c'est pas automatique” (“Antibiotics are not automatic”) is launched each winter with the primary goal of decreasing prescriptions, particularly during the viral respiratory infection (VRI) epidemic season and among children, for whom >40% of the prescriptions are written [14]–[16]. In this article we evaluate the effectiveness of these campaigns by analyzing the evolution of outpatient antibiotic use in France from 2000 to 2007, for each therapeutic class, as well as by geographic and age-group patterns. We performed a time-series analysis and accounted for flu-like syndrome (FLS) variations. Methods The Campaign (“Antibiotics Are Not Automatic”) In 2002 the French National Health Insurance (NHI) launched a long-term nationwide campaign in the community. From its conception, the aim of the campaign was to decrease total antibiotic use in the community by 25%, targeting predominantly VRIs in young children. An extensive information dissemination campaign was developed with the central theme “Antibiotics are not automatic.” Each winter (October–March) it is relaunched, as higher levels of infections and prescriptions occur during this period. A description of the campaign is detailed in Text S1. Definitions and Data Sources The NHI program covers all medical care provided by physicians in private practice, community clinics, and hospitals. Patients pay health service fees, which are refunded by the NHI. In France, everyone, even those with low or no income, are covered by the NHI program. We used anonymous computerized individual data from two main NHI agencies (General Scheme and Social Scheme), which cover salaried workers and the self-employed (≥91% of the French population), to access all antibiotics prescribed, dispensed by outpatient pharmacies, and reimbursed by NHI from 2000 to 2007 (beginning week 27 [July] 2000, ending week 13 [March] 2007). Each drug approved by the French Drug Agency is assigned a unique seven-digit code that enables identification of a particular product and its specific dosage, package size, formulation, and manufacturer. Each file contains this drug-related information, prescription date, patient's sex, year of birth, and region of residence. Weekly FLS incidence was provided by the French Sentinel Network [17] (see http://sentiweb.org/). According to the French Sentinel Network, FLS is defined as the combination of the following clinical symptoms: sudden onset fever ≥39°C, myalgia, and respiratory symptoms such as dyspnea and/or cough. Demographic data were obtained from the French National Institute for Statistics and Economic Studies (INSEE, http://www.insee.fr). We included the European part of France (henceforth referred to as France), which accounts for 83% of French territory and 96% of its population. For each of France's 22 administrative regions, reimbursement data were extrapolated to 100% of the regional population by dividing the number of prescriptions by the corresponding region's NHI coverage rate. The results are presented as the weekly rate of antibiotic prescriptions per 100 inhabitants. The study concerns antibiotics for systemic use (anatomical therapeutic class [ATC] code J01) in the community. Antibiotics were divided into six categories according to the ATC classification: penicillins, cephalosporins, macrolides, quinolones, cyclines, and “other.” Statistical Analysis Our analysis describes the crude number of antibiotic prescriptions and FLS incidence over time, overall, and by region, antibiotic class, and age group (0–5, 6–15, >15 y). We focused on the period targeted by the public service campaign (October–March); more specifically, we examined the truncated series corresponding to a 26-wk period starting at week 40 of year n and finishing at week 13 of year n+1. We conducted time-series analyses to quantitatively evaluate the impact of the successive, annual campaigns on antibiotic consumption. We used intervention models [18]–[20] that allowed us to estimate crude and FLS-adjusted effects of the campaign. The intervention models were built in two steps. For the first step, we chose the 2000–2002 period preceding the first campaign, i.e., starting at week 27 in 2000 and ending at week 40 in 2002, as the baseline and fitted a model to the series of antibiotic prescriptions accounting for seasonal variations and underlying autoregressive and moving average processes. As in other southern and eastern European countries [21], antibiotic consumption in France shows marked yearly seasonal fluctuations; therefore we first estimated a periodic trigonometric function and removed it from the truncated series so that the residual series was in stationary mode. We then fitted an autoregressive and moving average (ARMA) model [22] on the residual series, leaving white noise residual series. For the second step, we assumed that observations before and after the campaign were drawn from the same ARMA model with changes only in the mean. Following this assumption, we removed the previously estimated periodic trigonometric function from the whole antibiotic prescription series (2000–2007) and added five dummy variables, one for each annual campaign, to the ARMA model identified in step 1 so that only the mean could change. We quantified the impact of each campaign as the average relative change for the period (from winter 2002–2003 to winter 2006–2007) compared with baseline (2000–2002); that is, the ratio of the observed change over the expected change predicted from the model had there been no campaign. The same procedure was repeated after dividing the population into three age categories ( 15 y) as well as considering data of the summer period (April–September) and data of the entire year (October–September). Finally, we further adjusted the intervention model for the whole population for FLS incidence. We tested the hypothesis of a different link between antibiotic consumption and FLS incidence before and after the start of the 2002 campaign by introducing an interaction term in the model. Analyses were performed using SAS version 9.1 (SAS Institute, http://www.sas.com/). All statistical tests were two-tailed; a p-value of less than 0.05 was considered significant. Results Description of the Data Between July 2000 and March 2007, a total of 453,407,458 individual antibiotic prescriptions were reimbursed by the NHI; all files were processed for analysis. Because prescription numbers were similar for men and women (unpublished data), we combined their data. Antibiotic prescriptions and FLS fluctuated seasonally, with higher incidence rates during winter months (Figure 1). Maximal values differed from one year to another. The number of antibiotic prescriptions varied between 585,524 (week 33 of 2006) and 2,196,942 (week 3 of 2002) (amplitude ratio 3.8). FLS peaks varied between 396 (winter 2002–2003) and 939 (winter 2004–2005) cases per 100,000 inhabitants (amplitude ratio 2.3). The FLS epidemic began as early as week 45 (third week of November) in the 2003–2004 season and as late as week 4 (fourth week of January) in the 2001–2002 season. All epidemics occurred between week 40 (beginning of October) and week 13 (end of March). 10.1371/journal.pmed.1000084.g001 Figure 1 Antibiotic use and flu-like syndromes in France, from July 2000 to March 2007. Weekly totals of antibiotic prescriptions and FLS cases per 100 inhabitants plotted against time. The mean number of prescriptions per 100 inhabitants for the general population was 72.4 for the 2000–2001 and 2001–2002 winters; this figure gradually decreased to 56.6 during the 2006–2007 season (Table 1). 10.1371/journal.pmed.1000084.t001 Table 1 Mean number of prescriptions between October and March, per 100 inhabitants (percent change compared to 2000–2002). Antibiotic Class 2000–2002 2002–2003 2003–2004 2004–2005 2005–2006 2006–2007 Penicillins 27.0 21.7 (−19.6) 21.5 (−20.4) 20.7 (−23.6) 20.8 (−23.2) 20.2 (−25.3) Cephalosporins 16.3 13.6 (−17.0) 14.7 (−10.2) 14.6 (−10.7) 12.5 (−23.7) 12.3 (−24.6) Macrolides 16.4 14.2 (−13.7) 14.2 (−13.8) 13.9 (−15.3) 12.4 (−24.4) 11.5 (−30.1) Quinolones 4.2 4.3 (3.2) 4.3 (2.8) 4.8 (14.2) 4.6 (8.6) 4.7 (12.8) Cyclines 3.1 3.1 (1.0) 3.2 (3.7) 3.2 (3.2) 3.1 (1.1) 3.0 (−3.7) Other 5.3 8.1 (55.0) 8.5 (62.0) 7.4 (40.6) 5.1 (−3.8) 4.8 (−8.0) All 72.4 65.1 (−10.1) 66.4 (−8.3) 64.5 (−10.8) 58.4 (−19.3) 56.6 (−21.9) Variations in antibiotic use were observed among France's 22 administrative regions. Antibiotic consumption declined in all regions between 2001–2002 and 2006–2007 (Figure 2). In 2000–2001, 15/22 regions had >70 prescriptions per 100 inhabitants, but none exceeded this level in 2006–2007. The most important reduction was observed in the Centre Region (−28.4%). Among the six administrative regions with the highest average number of prescriptions per 100 inhabitants in 2001–2002 (Nord 91.8, Picardie 83.3, Haute Normandie 80.3, Lorraine 78.7, Champagne-Ardenne 78.7, and Poitou-Charentes 77.3), the decrease in antibiotic use was among the seven highest, with values of −25.2%, −26.1%, −25.6%, −25.2%, −27.1%, and −27.30%, respectively. Antibiotic prescription differences among regions persisted after the campaign but were less dramatic. 10.1371/journal.pmed.1000084.g002 Figure 2 Winter antibiotic prescriptions in France by region, from October 2000 to March 2007. The number of October–March prescriptions is divided by the number of regional inhabitants for the respective year in each of 22 France's regions: Al (Alsace), Aq (Aquitaine), Auv (Auvergne), BN (Basse Normandie), Bou (Bourgogne), Br (Bretagne), CA (Champagne-Ardenne), Ce (Centre), Co (Corse), HN (Haute Normandie), Li (Limousin), Lo (Lorraine), LR (Languedoc-Roussillon), IDF (Ile de France), FC (Franche-Conté), MP (Midi-Pyrénées), NPDC (Nord-Pas de Calais), PACA (Provence-Alpes-Cote d'Azur), PDL (Pays de Loire), PC (Poitou-Charente), Pi (Picardie), RA (Rhones Alpes). Penicillins, cephalosporins, and macrolides were the three most used antibiotic classes at baseline, with 27.0, 16.3, and 16.4 prescriptions per 100 inhabitants; their use also declined the most (changes of −25.3%, −24.6%, and −30.1%, respectively) among all antibiotic classes. Quinolones, which remain a less frequently prescribed antibiotic class (4.2 prescriptions per 100 inhabitants at baseline), was the only class whose use increased (+12.8%) (Table 1). For children 15 y old (−9.8% [95% CI −14.9% to −4.7%] and –12.5% [95% CI −16.8% to −8.1%], respectively). The evolution of this change differed according to age group. Nevertheless, by 2006–2007, the campaign had achieved significantly fewer antibiotic prescriptions: rates were −27.0% (95% CI −33.5% to −20.5%) versus baseline for the whole population, −30.1% (95% CI −40.7% to −19.6%) for the youngest children, −35.8% (95% CI −48.3% to −23.2%) for 6- to 15-y-olds, and −20.5% (95% CI −25.6% to −15.4%) for those >15 y (Table 2). 10.1371/journal.pmed.1000084.g004 Figure 4 One step ahead forecasts of the interrupted ARMA model and observed antibiotic prescriptions data. October–March horizontal lines indicate the estimated average level by the interrupted ARMA model (in red) and the observed average level without any campaign effect (in black) each winter. The percentages listed above the peaks denote the ratio of change. 10.1371/journal.pmed.1000084.t002 Table 2 Estimated mean percent reduction of antibiotic use [95% CI] and associated p-values, compared to 2000–2002 baseline values. Period Age Group 2002–2003 2003–2004 2004–2005 2005–2006 2006–2007 October–March (winter) 0–5 y (FLS unadjusted) −1.2 [−7.7 to 5.3] −2.4 [−10.8 to 5.9] −14.9 [−24.2 to −5.6] −26.9 [−36.9 to −17.0] −30.1 [−40.7 to −19.6] p-value 0.71 0.87 0.002 15 y (FLS unadjusted) −12.5 [−16.8 to −8.1] −11.3 [−16.2 to −6.5] −13.4 [−18.4 to −8.5] −19.0 [−23.9 to −14.0] −20.5 [−25.6 to −15.4] p-value 15% of antimicrobial drug use for penicillins, cephalosporins, and macrolides (similarly, no reduction was noted for quinolones) during the 2000–2004 period [4]. The overall decline we observed can be compared to those observed in three other national studies for which comparable data are available: Belgium, Sweden, and Australia. In Belgium, a significant decrease (after controlling for FLS variation) was obtained after the first year but not after the second [37]; a longer follow-up might show a more pronounced and long-term decrease [43]. In Sweden, a country that had one of the lowest antibiotic consumption rates in Europe [23], an intervention was launched in 1995 [44]. This intervention did not involve a public campaign and was reported as having led to a −20% change in overall antibiotic sales between 1995 and 2004 [38]. The Australian investigation focused mainly on consumer awareness and physician behavior changes [39]. In France, comprehensive coverage of the population by the NHI and drug reimbursement for outpatient care offer a unique opportunity for in-depth analysis of drug use data, in particular use of antibiotics among outpatients for almost the entire population. To the best of our knowledge, this is the largest body of data—with nearly half a billion data entries and the longest time-series of individual and weekly data on antibiotic prescriptions—to evaluate antibiotic use in the community ever analyzed. Our data show that the primary objective of the French national campaign was largely achieved, with a 30.1% decrease in antibiotic use in children <6 y old. This result is very encouraging, because a substantial proportion of antibiotic prescriptions for young children are unnecessary because of the viral origins of their infection [26]. The most important decrease in antibiotic use for children <5 y was noted after the second campaign. There is no clear explanation for this change, but it suggests that repeated campaigns may be necessary to overcome initial resistance by parents and physicians to reduced antibiotic prescription. In addition, children aged 6–15 y also had significantly lower antibiotic use (a −35.8% change over the study period). This change may be due to the use of rapid tests to diagnose group A streptococci tonsillitis, which was promoted by the campaign in this age group, which is at a higher risk of group A streptococci throat infections. Antibiotic consumption changed by −24.1% among young adults (26–35 y), who were initially the biggest antibiotic consumers among adults. Demographic characteristics of this population suggest that most parents of young children fall within this age category; as a result, it is likely that young adults have been specifically affected by the campaign. Finally, prescriptions in the 21–25 y age group remained stable from 2000 to 2007 (as compared to decreases observed in older and younger age groups). Two hypotheses may explain this observation. First, 21- to 25-y-old adults are less likely to live in or interact with collective institutions (daycares, schools, etc.) or be in close contact with children than other age groups; as a result, they are less likely to be exposed to VRIs, which are typically spread by young children. Second, it may be difficult to further decrease antibiotic use in this age group, as they already represent the age group with the lowest antibiotic prescription rate before the campaign. While crude results did not differ markedly from those adjusted for FLS fluctuations, accounting for the latter was crucial to the interpretation of the changes recorded. Indeed, in many countries, VRIs account for a high share of unnecessary antibiotic prescriptions. Our intervention model highlighted a significant weakening of the association between FLS incidence rates and antibiotic prescriptions after the second yearly campaign. This observation suggests that the fraction of antibiotics prescribed for viral illnesses has significantly decreased, which is a highly encouraging result, as one of the campaign's main objectives was to reduce VRI-associated antibiotic overuse. However, the association between FLS and antibiotic prescriptions persists, at a low level, even after the campaign. Several limitations of this study should be noted. First, due to the quasiexperimental design (i.e., absence of a control group) and limited preintervention data, a cause–effect relationship between the campaign “Antibiotics are not automatic” and decreased antibiotic use cannot be proved. For example, the influence of the antibiotic campaigns in other geographically proximate European countries such as Belgium cannot be excluded. Some southern European countries also conducted campaigns during the 2002–2007 period (Greece: mass media campaign in 2001–2003; Spain: mass media campaign since 2006; Portugal: radio campaign in 2004–2007) and observed evolution of outpatient antibiotic use [23]. Thus, effects of targeted campaigns versus the spontaneous decrease of antibiotic use should be evaluated in Europe. Very few new antibiotics have been launched in the past decade; as a result, the promotion of antibiotic prescription by the pharmaceutical industry has probably decreased. This might be a confounding factor for the observed reduction of antibiotic use. Second, we did not have access to information about the pathology for which antibiotics had been prescribed. In France, no information system exists that provides easy access to data linking drug use to a clinical condition. Third, we did not account for the introduction of the 7-PCV in our analysis. The 7-PCV initially received marketing authorization in France in 2002, specifically for children presenting specific risk factors. It became widely used only at the end of 2006, once it had been recommended for all children <2 y old (unpublished data). It is thus unlikely that its market introduction could explain much of the decreased antibiotic use observed over the 5-year investigation period. Fourth, FLS surveillance data do not account for other VRIs such as infections due to respiratory syncytial virus, which generally occur several weeks before a flu outbreak. It was not feasible to account for these viral infections, as surveillance data of these infections are not available in France. As a result, it is likely that we underestimated the association between community viral infection and antibiotic prescription. Fifth, other local initiatives were promoted in France since 2000, such as the campaign “Antibiotics Only When Necessary” promoted in a county in southeastern France (see http://www.gepie.org/). The added value of such initiatives was not specifically investigated. Sixth, some authors have reported that antibiotics may substantially reduce the risk of pneumonia after chest infection [45]. Therefore, adverse effects of reduced antibiotic use (e.g., increase in certain severe infections) is questionable. We do not address this question here, which remains to be investigated. Reasons for reduced antibiotic prescriptions, e.g., fewer consultations or improved prescribing, were not evaluated here, the data did not provide the necessary information to address this question. It has been reported that mass media campaigns play a role in influencing antimicrobial prescription practice in the UK [46]. Due to the multifaceted approach and targeting of the general public and physicians in parallel, the individual effect of each approach could not be evaluated. We believe that the success of the intervention was in fact a result of the combined approach, e.g., face-to-face peer education and widespread public campaigns, allowing both the practitioner not to prescribe and the patient not to ask for antibiotic therapy. The results of the present report are highly promising in terms of bacterial resistance control. A recent European study confirms the ecological relationship between antibiotic consumption and rate of MRP at the national level [4]. This study strongly underlines the responsibility of countries with higher levels of antibiotic use and recommends that they urgently undertake campaigns devoted to the control of MRP, including the promotion of prudent antibiotic use. In France from 2001 to 2006, a decreasing trend was observed in the rate of pneumococci resistant to penicillin (47% to 32% of isolates) and the rate of pneumococci resistant to macrolides (49% to 36%) in France (see http://www.rivm.nl/earss). Because our campaign did not target any specific therapeutic class, it may have prevented interclass switching. Nevertheless, a slight increase of quinolone prescriptions occurred. Although this was a moderate increase compared to large decreases recorded for all other classes, this trends points to the need for careful monitoring of quinolone-resistant bacteria in the community [47]. Despite the sharp reduction of antibiotic prescriptions observed, France remains a high user of antibiotics [23]. Nevertheless, the impact of the decrease in antibiotic use on the prevalence of infections caused by antimicrobial-susceptible and antimicrobial-resistant strains must be investigated. Future studies should combine the assessment of 7-PCV vaccination and antibiotic-reduction policies, and evaluate their respective role in the evolution of S. pneumoniae invasive infections, according to strain susceptibility. Supporting Information Text S1 Description of the public health campaign “Antibiotics are not automatic” between 2002 and 2007. (0.04 MB DOC) Click here for additional data file.
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Medicine access and utilization in a population covered by primary health care in Brazil.
To describe medicine utilization and access in a population covered by the Family Health Program (PSF) in Brazil. Cross-sectional study with a random sample of 2988 individuals living in areas covered by 45 PSF clinics. Medicine utilization in the 15 days prior to the interview was assessed, as well as lack of access to medicines (proportion of people with medicines needed but not used), and lack of free access through the PSF (proportion of medicines used which had to be purchased). Overall, 54.5% (95% CI 50.6; 58.4) of individuals used at least one medicine in the 15-day period and 3.6% reported failing to use a needed medicine. Of all medicines used, 41.5% were paid for out-of-pocket (25.5% among the poorest families), and 51.0% were obtained for free from the PSF. Almost 90% of the medicines prescribed by PSF physicians were provided for free by the PSF. Although medicine access was high, individuals paid out-of-pocket for a substantial proportion of the medicines used. Lack of availability in PSF facilities and prescribing by non-PSF providers seem to contribute to the need for out-of-pocket purchases, and thus can be targeted for improvement through PSF policies.
Author and article information
Journal
Journal ID (publisher-id): rpsp
Title:
Revista Panamericana de Salud Pública
Abbreviated Title:
Rev Panam Salud Publica
Publisher:
Organización Panamericana de la Salud
(Washington, Washington, United States
)
ISSN
(Print):
1020-4989
ISSN
(Electronic):
1680-5348
Publication date
(Print and electronic):
March
2010
Volume: 27
Issue: 3
Pages: 219-225
Affiliations
[01]
Cuernavaca
orgnameNational Institute of Public Health
orgdiv1Health Systems Research Centre
Mexico
vwirtz@
123456correo.insp.mx
Article
Publisher ID: S1020-49892010000300009 Publisher ID: S1020-4989(10)02700309DOI: 10.1590/s1020-49892010000300009
PubMed ID: 20209226
SO-VID: be7bf601-f5d0-4722-bc91-696893df3523
License:
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
History
Date
received
: 21
October
2009
Date
accepted
: 06
January
2010
Page count
Figures: 0,
Tables: 0,
Equations: 0,
References: 33,
Pages: 7
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Subject:
Articles
Data availability: