Health Alliance for prudent antibiotic prescribing in patients with respiratory tract infections (HAPPY AUDIT) -impact of a non-randomised multifaceted intervention programme

  • Lars Bjerrum1, 2Email author,

    Affiliated with

    • Anders Munck2,

      Affiliated with

      • Bente Gahrn-Hansen2,

        Affiliated with

        • Malene Plejdrup Hansen2,

          Affiliated with

          • Dorte Ejg Jarbol2,

            Affiliated with

            • Gloria Cordoba2,

              Affiliated with

              • Carl Llor3,

                Affiliated with

                • Josep Maria Cots3,

                  Affiliated with

                  • Silvia Hernández3,

                    Affiliated with

                    • Beatriz González López-Valcárcel4,

                      Affiliated with

                      • Antonia Pérez4,

                        Affiliated with

                        • Lidia Caballero5,

                          Affiliated with

                          • Walter von der Heyde5,

                            Affiliated with

                            • Ruta Radzeviciene6,

                              Affiliated with

                              • Arnoldas Jurgutis6,

                                Affiliated with

                                • Anatoliy Reutskiy7,

                                  Affiliated with

                                  • Elena Egorova7,

                                    Affiliated with

                                    • Eva Lena Strandberg8,

                                      Affiliated with

                                      • Ingvar Ovhed8,

                                        Affiliated with

                                        • Sigvard Mölstad8,

                                          Affiliated with

                                          • Vander Robert Stichele9,

                                            Affiliated with

                                            • Ria Benko9,

                                              Affiliated with

                                              • Vera Vlahovic-Palcevski9,

                                                Affiliated with

                                                • Christos Lionis10 and

                                                  Affiliated with

                                                  • Marit Rønning11

                                                    Affiliated with

                                                    BMC Family Practice201112:52

                                                    DOI: 10.1186/1471-2296-12-52

                                                    Received: 25 February 2011

                                                    Accepted: 20 June 2011

                                                    Published: 20 June 2011

                                                    Abstract

                                                    Background

                                                    Excessive use of antibiotics is worldwide the most important reason for development of antimicrobial resistance. As antibiotic resistance may spread across borders, high prevalence countries may serve as a source of bacterial resistance for countries with a low prevalence. Therefore, bacterial resistance is an important issue with a potential serious impact on all countries. Initiatives have been taken to improve the quality of antibiotic prescribing in primary care, but only few studies have been designed to determine the effectiveness of multifaceted strategies across countries with different practice setting. The aim of this study was to evaluate the impact of a multifaceted intervention targeting general practitioners (GPs) and patients in six countries with different health organization and different prevalence of antibiotic resistance.

                                                    Methods

                                                    GPs from two Nordic countries, two Baltic Countries and two Hispano-American countries registered patients with respiratory tract infections (RTIs) in 2008 and 2009. After first registration they received individual prescriber feedback and they were offered an intervention programme that included training courses, clinical guidelines, posters for waiting rooms, patient brochures and access to point of care tests (Strep A and C-Reactive Protein). Antibiotic prescribing rates were compared before and after the intervention.

                                                    Results

                                                    A total of 440 GPs registered 47011 consultations; 24436 before the intervention (2008) and 22575 after the intervention (2009). After the intervention, the GPs significantly reduced the percentage of consultations resulting in an antibiotic prescription. In patients with lower RTI the GPs in Lithuania reduced the prescribing rate by 42%, in Russia by 25%, in Spain by 25%, and in Argentina by 9%. In patients with upper RTIs, the corresponding reductions in the antibiotic prescribing rates were in Lithania 20%, in Russia 15%, in Spain 9%, and in Argentina 5%.

                                                    Conclusion

                                                    A multifaceted intervention programme targeting GPs and patients and focusing on improving diagnostic procedures in patients with RTIs may lead to a marked reduction in antibiotic prescribing. The pragmatic before-after design used may suffer from some limitations and the reduction in antibiotic prescribing could be influenced by factors not related to the intervention.

                                                    Background

                                                    Excessive and inappropriate use of antibiotics is an important reason for development of bacterial resistance [[13]]. Countries with a high use of antibiotics have a higher rate of resistance than countries with a low use [4]. As antibiotic resistance may spread across borders, high prevalence countries may serve as a source of bacterial resistance for countries with a low prevalence. Therefore, bacterial resistance is an important issue with a potentially serious impact on all countries.

                                                    Infections caused by resistant bacteria lead to increased mortality, prolonged hospital stay and increased costs [5, 6]. A cornerstone of efforts to control antibiotic resistance is to improve the quality of antibiotic prescribing in primary health care, as more than 90% of antibiotics are prescribed by GPs. Approximately 70% of antibiotics prescribed in general practice are for respiratory tract infections (RTIs) [7, 8]. However, the majority of RTIs (90%) are caused by virus and in these cases antibiotics are unlikely to have any clinical benefit. Studies of the management of RTIs show that a considerable number of antibiotic prescriptions are neither necessary nor appropriate [9, 10]. Most RTIs are harmless and self-limiting and nearly all patients recover without any specific treatment. Antibiotic treatment may thus be superfluous, and in some cases it may be directly harmful due to adverse effects. Even if the aetiology is bacterial, antibiotics only slightly modify RTIs, particular in patients with upper RTIs [11, 12].

                                                    Studies comparing bacterial resistance in various European countries have clearly documented that the prevalence of resistant strains is correlated with the consumption of antibiotics [4, 13]. Until recently, the rates of antibiotic resistance in the northern European countries have remained low. However, the rates of resistance in the southern European countries are reaching alarming levels. The different antibiotic prescribing rates between countries may be due to discrepancies in national recommendations, different health care systems, different treatment traditions, different culture, different patient expectations or different impact of marketing by pharmacies and pharmaceutical companies. Several initiatives have been taken to reduce the inappropriate use of antibiotics in primary health care, but only few have achieved positive results. According to a review from the Cochrane Library, multifaceted interventions seem to be more effective than singular interventions [14]. However, only a few multifaceted interventions targeting treatment of RTIs have been performed, and we need information about the effect of multifaceted interventions in countries with different practice settings.

                                                    The aim of this study was to evaluate the impact of a multifaceted intervention programme focusing on appropriate antibiotic treatment of RTIs and targeting general practitioners and patients in general practice. The project was performed in six countries with different primary health care settings of and different prevalence of antibiotic resistance.

                                                    Methods

                                                    Detailed information about the study method and the intervention can be found in the study protocol, published in BMC Family practice[15]. Briefly, data were obtained from GPs in two Nordic countries (Denmark and Sweden), two Baltic Countries (Lithuania and Russia) and two Hispano-American countries (Spain and Argentina). Symptoms, signs, investigations, diagnosis, assumed etiology and choice of treatment were registered for all patients with RTI during 3 weeks in the winter months of 2008 and 2009. Patients were registered using a prospective self-registry methodology based on a chart filled by the GP during the consultation [16].

                                                    Shortly after the first registration the GPs were invited to follow-up meetings where they received individual prescriber feedback and identified potential quality problems. Afterwards, they were offered an intervention programme that included the following elements:

                                                    • Training course on appropriate use of antibiotics for RTIs

                                                    • Clinical guidelines with recommendations for diagnosis and treatment of RTIs.

                                                    • Posters for waiting rooms, focusing on the appropriate use of antibiotics

                                                    • Brochures and handouts to patients about prudent use of antibiotics

                                                    • Access to Point of care (POC) tests: Strep A and C-Reactive Protein (CRP)

                                                    • Training in use and interpretation of POC tests

                                                    After the intervention, the GPs performed the second registration during a 3-week winter period one year after the first registration. For each of the involved countries we compared the antibiotic prescribing for upper and lower RTIs before and after the intervention. Furthermore, we investigated if the intervention had any influence on the choice of antibiotic.

                                                    All patient registration data were treated confidentially according to the law on protection of sensitive data and the project was conducted in accordance with the EU Directive of good clinical practice (EU Directive 2001/20/EC).

                                                    Patients registered during the study were informed about the objective of the project and they were told that specific clinical information related to the consultation was entered into a multinational database. However, no electronic patient identifier was used; patients were registered by age and sex only. The database did not contain any person-identifier or other information that could be used to identify individual registry patients. The study did not involve any randomization of patients. The protocol was submitted to a legally constituted ethics committee and deemed exempt from review (The Scientific Ethical Committee for the County of Vejle and Funen, Denmark)

                                                    Data were analyzed by the statistical program Stata, version 11. We used 95% confidence intervals (CI), adjusted for clustering to GPs.

                                                    Results

                                                    General practitoners

                                                    National coordinators from each of the participating countries invited local GPs to participate by e-mail, telephone or personal contact. The results presented in this paper are based on data from GPs (n = 440) participating in both registration periods (2008 and 2009). The GPs came from the following countries: Argentina (n = 48), Denmark (n = 78), Lithuania (n = 28), Russia (n = 37), Spain (210) and Sweden (39).

                                                    Table 1 shows the characteristics of the GPs participating in the study. Median age of the GPs ranged from 41 years (Argentina) to 55 years (Denmark and Sweden). In all countries, except Denmark and Sweden, the majority of GPs were women. There was a great discrepancy in the median number of years the GPs had worked in practice, ranging from 2 years (Russia) to 18 years (Spain). The majority of GPs worked in group practices comprising more than four GPs. The median number of patients listed per GP ranged from 1229 (Argentina) to 2272 (Russia). Workload, expressed by the number of consultations per day, ranged from 10 (Sweden) to 40 (Spain) and correspondingly the median number of minutes per consultation ranged from 6 minutes (Spain) to 20 minutes (Sweden).
                                                    Table 1

                                                    Characteristics of the GPs

                                                    Country

                                                    No of GPs

                                                    No of women (%)

                                                    Median age (iqr)

                                                    Median number of years (iqr) working in general practice

                                                    Number of GPs (%) working in single handed practice

                                                    Median number of GPs (iqr) working in group practices

                                                    Median number of patients (iqr) listed per GP

                                                    Median number of working hours per day (iqr)

                                                    Median number of minutes per cons (iqr)

                                                    Median number of cons per day (iqr)

                                                    Argentina

                                                    48

                                                    32 (66)

                                                    41 (34-47)

                                                    9 (4-25)

                                                    24 (53)

                                                    3 (2-4)

                                                    1229 (450-3416)

                                                    6 (4-8)

                                                    15 (10-20)

                                                    20 (15-30)

                                                    Denmark

                                                    78

                                                    38 (49)

                                                    55 (45-59)

                                                    14 (5-22)

                                                    30 (38)

                                                    3 (2-4)

                                                    1300 (1229-1450)

                                                    8 (8-8)

                                                    15 (10-15)

                                                    25 (22-28)

                                                    Lithuania

                                                    28

                                                    23 (82)

                                                    48 (43-53)

                                                    7 (6-11)

                                                    3 (11)

                                                    4 (3-6)

                                                    1480 (893-1500)

                                                    6 (5-7)

                                                    15 (13-16)

                                                    25 (20-30)

                                                    Russia

                                                    37

                                                    32 (86)

                                                    52 (45-55)

                                                    2 (1-4)

                                                    12 (43)

                                                    4 (4-6)

                                                    2272 (1557-2916)

                                                    7 (7-8)

                                                    15 (12-18)

                                                    24 (20-25)

                                                    Spain

                                                    210

                                                    127 (62)

                                                    49 (44-52

                                                    18 (12-21)

                                                    12 (6)

                                                    13 (10-17)

                                                    1694 (1500-1923)

                                                    6 (5-7)

                                                    6 (5-7)

                                                    40 (35-45)

                                                    Sweden

                                                    39

                                                    18 (46)

                                                    55 (47-60)

                                                    17 (9-22)

                                                    0 (0)

                                                    6 (4-8)

                                                    1708 (1467-2098)

                                                    8 (7-8)

                                                    20 (20-20)

                                                    10 (9-12)

                                                    Total

                                                    440

                                                    270 (62)

                                                    50 (43-54)

                                                    15 (7-20)

                                                    81 (19)

                                                    8 (4-24)

                                                    1627 (1385-1886)

                                                    7 (5-8)

                                                    10 (6-15)

                                                    30 (21-40)

                                                    Patients

                                                    A total of 47011 patients were registered; 24436 before the intervention (2008) and 22575 after the intervention (2009) (Table 2). The majority of patients were women. The number of days with symptoms before contact to the GPs ranged from 2 days (Argentina and Russia) to 6 days (Sweden).
                                                    Table 2

                                                    Characteristics of patients

                                                    Country

                                                    2008

                                                    2009

                                                     

                                                    Number of patients registered

                                                    Percentage of women (95% CI)

                                                    Median age (iqr)

                                                    Median number of days with symptoms before first consultation (iqr)

                                                    Number of patients registered

                                                    Percentage of women (95% CI)

                                                    Median age (iqr)

                                                    Median number of days with symptoms before first consultation (iqr)

                                                    Argentina

                                                    3499

                                                    53 (51-55)

                                                    11 (3-29)

                                                    2 (2-3)

                                                    3641

                                                    53 (52-55)

                                                    20 (9-36)

                                                    2 (1-3)

                                                    Denmark

                                                    2881

                                                    59 (57-60)

                                                    25 (4-46)

                                                    4 (2-7)

                                                    3706

                                                    57 (56-59)

                                                    25 (4-47)

                                                    4 (3-7)

                                                    Lithuania

                                                    2517

                                                    54 (52-55)

                                                    14 (6-30)

                                                    3 (2-4)

                                                    1976

                                                    54 (52-56)

                                                    13 (4-26)

                                                    3 (2-4)

                                                    Russia

                                                    3591

                                                    54 (52-55)

                                                    25 (12-43)

                                                    2 (1-3)

                                                    3284

                                                    53 (52-55)

                                                    26 (13-46)

                                                    2 (2-3)

                                                    Spain

                                                    10909

                                                    59 (58-60)

                                                    43 (30-62)

                                                    3 (2-5)

                                                    9073

                                                    59 (58-60)

                                                    43 (29-62)

                                                    3 (2-5)

                                                    Sweden

                                                    1039

                                                    55 (52-58)

                                                    17 (4-47)

                                                    5 (3-10)

                                                    895

                                                    56 (53-59)

                                                    20 (3-47)

                                                    6 (3-10)

                                                    All

                                                    24436

                                                    57 (56-57)

                                                    32 (15-52)

                                                    3 (2-5)

                                                    22575

                                                    56 (56-57)

                                                    31 (15-52)

                                                    3 (2-5)

                                                    Prescribing rates before and after intervention

                                                    Figure 1 shows the distribution of upper and lower RTIs before and after the intervention. In all countries, patients with upper RTIs represented the majority of consultations. The rate of antibiotic prescribing was highest for lower RTIs, but there were big differences in prescribing rates between GPs from different countries (Figures 2 and 3). Before the intervention, the highest prescribing rates for lower RTIs were found in Lithuania, where about nine out of ten consultations resulted in an antibiotic prescription.
                                                    http://static-content.springer.com/image/art%3A10.1186%2F1471-2296-12-52/MediaObjects/12875_2011_588_Fig1_HTML.jpg
                                                    Figure 1

                                                    Level of infection in patients with respiratory tract infections (RTIs) in general practice before and after intervention.

                                                    http://static-content.springer.com/image/art%3A10.1186%2F1471-2296-12-52/MediaObjects/12875_2011_588_Fig2_HTML.jpg
                                                    Figure 2

                                                    Prescription rate of antibiotics (% of consultations resulting in an antibiotic prescription) in patients with upper respiratory tract infections before and after the intervention.

                                                    http://static-content.springer.com/image/art%3A10.1186%2F1471-2296-12-52/MediaObjects/12875_2011_588_Fig3_HTML.jpg
                                                    Figure 3

                                                    Prescription rate of antibiotics (% of consultations resulting in an antibiotic prescription) in patients with lower respiratory tract infections before and after the intervention.

                                                    A significant reduction in the antibiotic prescribing rate was found in the Baltic countries and Hispano-America, while no significant change was seen in the Nordic countries. For patients with lower RTIs, GPs from Lithuania reduced their prescribing rate by 42% (CI: 36%-47%), GPs from Russia by 25% (CI: 19%-30%), GPs from Spain by 25% (CI: 22%-28%), and GPs from Argentina by 9% (CI: 4%-14%). For patients with upper RTIs, the antibiotic prescribing in Lithania was reduced by 20% (CI: 17%-23%), in Russia by 15% (CI: 13%-17%), in Spain by 9% (CI: 7%-10%) and in Argentina by 5% (CI: 3%-8%).

                                                    There were huge discrepancies between countries in the choice of antibiotics for RTIs (Tables 3 and 4). In patients with upper RTIs, GPs in the Nordic countries preferred penicillin-V while GPs in Argentina, Lithuania, Russia and Spain preferred amoxicillin. However, after the intervention a considerable increase in the prescribing rate of penicillin-V for all patients with upper RTIs was registered. In patients with lower RTIs, GPs in the Nordic countries preferred penicillin-V while GPs in Argentina, Lithuania, Russia and Spain preferred amoxicillin or amoxicillin with clavulanic acid. The prescribing rate of tetracycline, quinolone, and cephalosporin was generally low. However, in Sweden a considerable part of patients with RTIs were treated with tetracycline, in Spain with quinolone, and in Russia with cephalosporin. In Denmark, many RTIs were treated with macrolide, but a marked reduction was found after the intervention.
                                                    Table 3

                                                    Choice of antibiotic (%) in patients with upper respiratory tract infections before and after the intervention

                                                     

                                                    Before intervention (95% CI)*

                                                     

                                                    Penicillin-V

                                                    Amoxicillin

                                                    Amoxicillin-Clavulanic acid

                                                    Macrolide

                                                    Quinolone

                                                    Tetracycline

                                                    Cephalosporin

                                                    Other

                                                    Argentina

                                                    15.3 (8.2-22.4)

                                                    54.7 (38.3-71.1)

                                                    16.9 (5.0-28.8)

                                                    2.3 (0.7-4.5)

                                                    1.5 (0-3.0)

                                                    0.1 (0-0.4)

                                                    4.1 (0-8.5)

                                                    10.0 (0-21.1)

                                                    Denmark

                                                    79.6 (74.0-85.3)

                                                    9.2 (5.9-12.6)

                                                    0.2 (0-0.5)

                                                    7.2 (4.7-9.8)

                                                    0.2 (0-0.5)

                                                    0.2 (0-0.5)

                                                    0 (0-0)

                                                    3.9 (0.3-7.5)

                                                    Lithuania

                                                    24.2 (16.7-31.8)

                                                    37.6 (26.0-49.1)

                                                    18.1 (13.3-22.8)

                                                    6.5 (4.2-8.9)

                                                    0 (0-0)

                                                    1.8 (0-3.8)

                                                    10.9 (4.5-17.4)

                                                    0.8 (0-1.6)

                                                    Russia

                                                    9.0 (3.4-14.6)

                                                    42.5 (31.3-53.8)

                                                    29.2 (18.6-39.8)

                                                    14.1 (5.8-22.3)

                                                    1.9 (0-4.0)

                                                    1.4 (0-4.0)

                                                    1.8 (0.6-2.9)

                                                    0.5 (0-1.0)

                                                    Spain

                                                    10.1 (7.1-13.2)

                                                    34.8 (30.2-39.4)

                                                    32.2 (27.6-36.7)

                                                    9.0 (6.2-11.9)

                                                    1.8 (0.9-2.8)

                                                    0.1 (0-0.2)

                                                    3.8 (2.6-5.1)

                                                    8.8 (3.3-14.4)

                                                    Sweden

                                                    78.1 (70.6-85.5)

                                                    6.8 (3.5-10.2)

                                                    0 (0-0)

                                                    2.9 (0.7-5.1)

                                                    0 (0-0)

                                                    6.8 (0.3-11.0)

                                                    2.1 (0.1-4.2)

                                                    3.2 (0.9-5.6)

                                                     

                                                    After intervention (95% CI)*

                                                    Argentina

                                                    31.2 (22.6-39.8)

                                                    40.1 (26.6-53.6)

                                                    8.1 (3.5-12.7)

                                                    2.0 (0-4.2)

                                                    0.5 (0-1.2)

                                                    0.3 (0-1.0)

                                                    0.5 (0-1.2)

                                                    22.4 (7.2-37.7)

                                                    Denmark

                                                    83.7 (79.4-87.9)

                                                    10.0 (6.2-13.9)

                                                    2.0 (0.2-3.9)

                                                    3.0 (1.7-4.5)

                                                    0.3 (0-0.8)

                                                    0 (0-0)

                                                    0 (0-0)

                                                    1.2 (0.1-2.2)

                                                    Lithuania

                                                    68.5 (58.5-78.6)

                                                    17.6 (8.4-26.8)

                                                    2.8 (1.2-4.3)

                                                    7.9 (4.0-11.7)

                                                    0 (0-0)

                                                    0.5 (0-1.4)

                                                    0.5 (0-1.4)

                                                    2.3 (0-6.1)

                                                    Russia

                                                    19.4 (8.8-30.1)

                                                    55.0 (43.5-66.4)

                                                    12.8 (5.2-20.4)

                                                    5.7 (0-12.5)

                                                    0 (0-0)

                                                    0.9 (0-2.1)

                                                    4.3 (0.7-7.8)

                                                    1.9 (0-4.5)

                                                    Spain

                                                    31.0 (26.2-35.9)

                                                    29.8 (25.0-34.5)

                                                    26.4 (22.0-30.7)

                                                    4.7 (2.9-6.4)

                                                    1.7 (0.7-2.6)

                                                    0 (0-0)

                                                    2.7 (1.3-4.1)

                                                    4.1 (1.1-7.2)

                                                    Sweden

                                                    75.9 (70.2-81.7)

                                                    7.1 (3.7-10.7)

                                                    1.2 (0-2.7)

                                                    3.8 (1.3-6.3)

                                                    0 (0-0)

                                                    6.7 (3.4-10.1)

                                                    2.5 (0.5-4.6)

                                                    2.9 (1.1-4.8)

                                                    *: Adjusted for clustering to GPs

                                                    Table 4

                                                    Choice of antibiotic (%) in patients with lower respiratory tract infections before and after the intervention

                                                     

                                                    Before intervention (95% CI)*

                                                     

                                                    Penicillin-V

                                                    Amoxicillin

                                                    Amoxicillin-Clavulanic acid

                                                    Macrolide

                                                    Quinolone

                                                    Tetracycline

                                                    Cephalosporin

                                                    Other

                                                    Argentina

                                                    4.2 (1.6-6.9)

                                                    52.6 (38.6-66.7)

                                                    24.5 (13.8-35.2)

                                                    9.7 (5.5-14.0)

                                                    1.6 (0-3.5)

                                                    0 (0-0)

                                                    4.6 (1.1-8.2)

                                                    10.3 (1.3-19.3)

                                                    Denmark

                                                    60.0 (55.3-65.7)

                                                    13.6 (10.0-17.2)

                                                    1.3 (0-2.9)

                                                    23.1 (17.6-28.5)

                                                    0.8 (0-1.8)

                                                    1.0 (0-2.4)

                                                    0 (0-0)

                                                    0.8 (0-1.6)

                                                    Lithuania

                                                    6.9 (1.7-12.2)

                                                    33.4 (21.9-44.9)

                                                    25.4 (17.3-33.5)

                                                    19.7 (14.8-24.7)

                                                    1.7 (0.3-3.1)

                                                    1.8 (0.3-3.5)

                                                    10.7 (3.6-17.9)

                                                    1.3 (0-2.6)

                                                    Russia

                                                    4.7 (0.4-9.1)

                                                    33.7 (24.1-43.4)

                                                    28.0 (17.1-38.9)

                                                    13.8 (5.8-21.7)

                                                    4.7 (0-9.5)

                                                    0.4 (0-1.0)

                                                    20.2 (13.1-27.2)

                                                    0.8 (0-1.7)

                                                    Spain

                                                    0.2 (0-0.5)

                                                    19.3 (15.8-22.8)

                                                    44.9 (40.7-49.1)

                                                    13.5 (10.6-16.4)

                                                    16.0 (12.9-19.1)

                                                    0.4 (0-0.9)

                                                    3.6 (2.3-5.0)

                                                    2.5 (0.6-4.3)

                                                    Sweden

                                                    30.1 (19.2-40.9)

                                                    14.2 (8.0-20.3)

                                                    0 (0-0)

                                                    6.2 (1.9-10.4)

                                                    0 (0-0)

                                                    48.7 (39.1-58.3)

                                                    1.8 (0-4.1)

                                                    0 (0-0)

                                                     

                                                    After intervention (95% CI)*

                                                    Argentina

                                                    3.3 (0.5-6.2)

                                                    35.5 (26.3-44.6)

                                                    34.6 (25.4-43.8)

                                                    19.4 (9.8-29.0)

                                                    2.4 (0-5.3)

                                                    0.9 (0-1.8)

                                                    4.9 (0.4-9.4)

                                                    21.4 (2.0-40.9)

                                                    Denmark

                                                    70.7 (65.7-75.8)

                                                    10.8 (6.7-14.9)

                                                    6.2 (3.4-9.0)

                                                    11.1 (8.2-14.1)

                                                    0 (0-0)

                                                    0.2 (0-0.5)

                                                    0 (0-0)

                                                    0.9 (0-1.8)

                                                    Lithuania

                                                    38.1 (25.1-51.0)

                                                    22.9 (13.8-32.1)

                                                    6.1 (0.2-12.0)

                                                    22.1 (14.3-29.9)

                                                    0 (0-0)

                                                    3.0 (0.9-5.2)

                                                    5.2 (2.0-8.4)

                                                    3.4 (0-7.7)

                                                    Russia

                                                    10.7 (1.8-19.4)

                                                    47.9 (35.0-60.7)

                                                    17.9 (8.1-27.8)

                                                    6.4 (1.9-10.9)

                                                    2.5 (0-5.2)

                                                    0 (0-0)

                                                    15.8 (6.7-24.9)

                                                    0.4 (0-1.3)

                                                    Spain

                                                    0.5 (0-1.0)

                                                    22.5 (18.0-27.0)

                                                    42.8 (37.7-48.0)

                                                    12.9 (9.7-16.0)

                                                    16.1 (12.7-19.4)

                                                    0 (0-0)

                                                    3.9 (2.0-5.9)

                                                    1.8 (0.9-2.8)

                                                    Sweden

                                                    43.5 (29.8-57.3)

                                                    10.6 (3.3-17.9)

                                                    0 (0-0)

                                                    5.9 (1.5-10.2)

                                                    0 (0-0)

                                                    37.6 (23.5-51.8)

                                                    0 (0-0)

                                                    2.3 (0-5.6)

                                                    *: Adjusted for clustering to GPs

                                                    Discussion

                                                    This study showed that a combined intervention programme targeting GPs and patients and focusing on improving diagnostic procedure and treatment in patients with RTIs led to a marked reduction in antibiotic prescribing and a significant change in the choice of antibiotics. A considerable reduction in antibiotic prescribing was found in Argentina, Lithuania, Russia and Spain. In Denmark and Sweden we found no significant changes in the overall use of antibiotics, but marked changes were found related to the choice of antibiotics.

                                                    The intervention aimed to help GPs to distinguish between viral and bacterial aetiology. All practices were offered access to POC tests (StrepA and CRP) and the practice staff was instructed how to interpret the results. GPs were encouraged to employ a rational use of antibiotics according to the HAPPY AUDIT guidelines[15], and they were requested only to prescribe antibiotics to patients with a suspected bacterial aetiology.

                                                    All GPs were exposed to the multifaceted intervention activities, and based on the results in this study it is not possible to identify the elements that had the highest impact on the prescibing pattern. The majority of GPs (GPs from Argentina, Spain, Russia amd Lithuania) did not have access to POC test before the intervention, while most GPs from the Nordic countries used POC tests routinely. The marked effect of the intervention found outside the Nordic countries may to a certain extent be due to the introduction of POC tests in practice.

                                                    Our data must, however, be interpreted with caution due to a number of limitations. GPs participated on a voluntary basis and probably their prescribing habits may not represent the average use of antibiotics in their country [17]. GPs that were willing to register their antibiotic prescribing may have been more interested in quality development and research than GPs in general. Furthermore, they were willing to dedicate sufficient time to complete patient reports without economic incentives. The amount of time involved in this project could be considered to be a prominent barrier to participation, as GPs might find it difficult to dedicate the time in their daily work. However, earlier studies using the same type of data registration did not find it very time-consuming. Each registration takes less than 2 minutes, but the GPs also needed to allocate sufficient time for the subsequent courses and other activities planned during the intervention period.

                                                    Another limitation which should be taken into account is the fact that performing a registration on antibiotic use may in itself influence the prescribing habits. However, studies have shown that the reliability of this methodology applied in different countries is high and findings are correlated with the real prescribing in practice [16].

                                                    In our study, we asked the GPs to register what happened during the consultation, but patients were not followed after the consultation and thus we have no knowledge about the consequence of reducing antibiotic prescribing for the patients involved. From a theoretical point of view, the decision to treat should be taken after a diagnosis has been established. In general practice, however, the diagnostic procedures and the decision to treat are intricately linked. The GP may decide whether or not to prescribe an antibiotic at the same time, or even before, he classifies a specific diagnosis to the patient. After making the decision to prescribe the GP may thus adjust the diagnosis to fit the decision about treatment. This may lead to a diagnostic misclassification bias. However, this potential bias will affect the validity of the diagnosis both before and after the intervention and it only has a small likelihood of influencing the effect of the intervention.

                                                    Due to the limited time allocated for the registration process in practice only the typical signs and symptoms of RTIs according to the medical literature were recorded. This may lead to some limitations. The before-after design without a control group suffers from some limitations due to the fact that changes in antibiotic prescribing could be due to factors other than the intervention performed by the investigators. Non-biomedical factors that might represent powerful predictors of antibiotic prescription such as market regulation and socio-economic factors were not taken into account in this study.

                                                    This is a pragmatic study where registration of patients was performed in a natural practice setting. Patients were not informed about the project prior to the consultations. GPs participating in the audit were not allocated extra time for consultations, and they were not able to make considerable changes in their practice activities during the 3 weeks of registration. Thus, they attended the same patients as if they were not participating in the study. Therefore, it is most likely that our results can be extrapolated to other areas and practices with similar settings.

                                                    Conclusion

                                                    We found that a combined intervention programme targeting GPs and patients and focusing on improving diagnostic procedures in patients with RTIs led to a marked reduction in antibiotic prescribing. The pragmatic before-after design without control group suffers from some limitations due to the fact that changes in antibiotic prescribing could be influenced by factors not related to the intervention. All GPs were exposed to the multifaceted intervtention activities, and it is not possible to identify which of the elements that had highest impact on the prescribing pattern.

                                                    Declarations

                                                    Acknowledgements

                                                    The project is a Specific Targeted Research Project (STREP) funded by The European Commission: DG SANCO under the Frame Program 6 (SP5A-CT-2007-044154).

                                                    Contract Number 044154

                                                    Authors’ Affiliations

                                                    (1)
                                                    Research Unit for General Practice and Section of General Practice, Department of Public Health, University of Copenhagen
                                                    (2)
                                                    Research Unit of General Practice, Institute of Public Health, University of Southern Denmark
                                                    (3)
                                                    Spanish Society of Family Medicine
                                                    (4)
                                                    University of Las Palmas
                                                    (5)
                                                    Misiones Association of General Family Medicine
                                                    (6)
                                                    Public Health Department, Faculty of Health Sciences, Klaipeda University
                                                    (7)
                                                    Association of Family Doctors
                                                    (8)
                                                    Department of Clinical Sciences, Lund University
                                                    (9)
                                                    European Drug Utilisation Research Group
                                                    (10)
                                                    World Organisation of Family Doctors (WONCA) Europe
                                                    (11)
                                                    World Health Organisation, Collaborating Centre for Drug Statistics Methodology

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                                                    18. Pre-publication history

                                                      1. The pre-publication history for this paper can be accessed here:http://​www.​biomedcentral.​com/​1471-2296/​12/​52/​prepub

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                                                    © Bjerrum et al; licensee BioMed Central Ltd. 2011

                                                    This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://​creativecommons.​org/​licenses/​by/​2.​0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.