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  • Research article
  • Open Access
  • Open Peer Review

Antibiotic prescribing behavior among general practitioners – a questionnaire-based study in Germany

  • 1, 2Email author,
  • 2,
  • 3,
  • 3,
  • 2,
  • 2, 4,
  • 2,
  • 5,
  • 6,
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  • 7 and
BMC Infectious Diseases201818:208

https://doi.org/10.1186/s12879-018-3120-y

  • Received: 16 January 2017
  • Accepted: 30 April 2018
  • Published:
Open Peer Review reports

Abstract

Background

This study investigates the barriers and facilitators of the use of antibiotics in acute respiratory tract infections by general practitioners (GPs) in Germany.

Methods

A multidisciplinary team designed and pre-tested a written questionnaire addressing the topics awareness of antimicrobial resistance (7 items), use of antibiotics (9 items), guidelines/sources of information (9 items) and sociodemographic factors (7 items), using a five-point-Likert-scale (“never” to “very often”). The questionnaire was mailed by postally to 987 GPs with registered practices in eastern Germany in May 2015.

Results

34% (340/987) of the GPs responded to this survey. Most of the participants assumed a multifactorial origin for the rise of multidrug resistant organisms. In addition, 70.2% (239/340) believed that their own prescribing behavior influenced the drug-resistance situation in their area. GPs with longer work experience (> 25 years) assumed less individual influence on drug resistance than their colleagues with less than 7 years experience as practicing physicians (Odds Ratio [OR] 0.32, 95% Confidence Interval [CI] 0.17–0.62; P < 0.001). 99.1% (337/340) of participants were familiar with the “delayed prescription” strategy to reduce antibiotic prescriptions. However, only 29.4% (74/340) answered that they apply it “often” or “very often”. GPs working in rural areas were less likely than those working in urban areas to apply delayed prescription.

Conclusion

The knowledge on factors causing antimicrobial resistance in bacteria is good among GPs in eastern Germany. However measures to improve rational prescription are not widely implemented yet. Further efforts have to be made in order to improve rational prescription of antibiotic among GPs. Nevertheless, there is a strong awareness of antimicrobial resistance among the participating GPs.

Keywords

  • Antibiotic therapy
  • Primary care
  • Antimicrobial resistance
  • Antibiotic policy

Background

Antimicrobial resistance (AMR) jeopardizes the achievements of modern medicine in Europe and worldwide [13]. The consumption of antibiotics is an important driver of AMR [4, 5]. Over the past decade the global antibiotic use increased significantly [6]. In the human sector the primary use of antibiotics in outpatient care is found among general practitioners (GPs) [7, 8]. There is a considerable difference in outpatient antibiotic use worldwide, between European countries and within countries [911]. Considering the use of antibiotics in primary care in Europe, Germany is one of the countries with a lower level of consumption of antibiotics [12, 13]. Nevertheless, it is striking that the proportion of reserve antibiotics in Germany is high [11, 14]. In Germany, the total consumption of antibiotics in human medicine is about 800 tons per year. Approximately 600 tons of this are used in outpatient care [15]. More than half of the antibiotics used in outpatient care are prescribed by GPs in Germany [16, 17]. In GP practices, the majority of antibiotics is prescribed for acute respiratory infections, most of which are caused by a virus [16, 18]. In most cases they do not require antimicrobial therapy [1922]. In Germany, antimicrobial resistance is mainly a problem in hospital care and especially in intensive care units [23]. German health care system is divided in primary and secondary care, most people are covered by statutory health insurance [24].

The present survey was carried out in the preparation of a broader intervention study, called “Rational antibiotic Use via information and communication” (RAI-project, www.rai-projekt.de). The RAI-project promotes rational antibiotic use in veterinary medicine, in particular in pig farming, as well as in human medicine, surgery and intensive care units, travel medicine, and primary care, with a focus on eastern Germany [25].

The following barriers to rational antibiotic usage have been identified from the scientific literature. But explanations of the barriers to rational antibiotic use vary widely in primary care. Some authors describe that uncertainty about pathogenesis, heavy workflow and patient’s desire for an antibiotic therapy can lead to increased prescription of antibiotics [2628] as well as knowledge and health literacy among the general population [29]. This questionnaire survey was carried out to examine whether the barriers identified in the literature can also be found in the intervention area.

Methods

Survey development

A multidisciplinary team of the RAI study group developed a questionnaire comprised of 32 questions grouped around the four issues: awareness of antimicrobial resistance (7 items), use of antibiotics (9 items), guidelines/sources of information (9 items) and socio-demographic factors (7 items). The majority of the answers were in tick-box format (see Additional file 1).

To identify factors influencing prescribing behavior of antibiotics we conducted a literature review. Based on these results, the questionnaire was developed. The inquiry of the sociodemographic data (Q1-Q4), as well as the questions Q8, Q9, Q12 and Q13 are founded on a previous study conducted among GPs in Germany in 2007 [30].

The questionnaire was pretested among scientists at the Friedrich-Schiller-University (Jena) and the Charité (Berlin). In a second step, a pilot test was conducted among 12 GPs (03/2015). After completing the questionnaire, participants were asked to explain the content of each question in their own words to increase internal validity. GPs who took part in the pilot test were not included in the survey.

Recruitment and data collection

The revised questionnaire was then mailed postally to roughly one third (987) of the GPs from the German federal states of Thuringia, Brandenburg and Berlin (2015/05).

In Berlin and Thuringia, pre-existing lists of all registered doctors could be used. In Brandenburg, a list was made available by the Brandenburg Medical Association, with doctors who had agreed to be contacted. Participants were randomly selected from the address lists. In addition to the questionnaire, the letter was accompanied by an addressed and prepaid envelope. The survey was paper based.

Statistical analysis

Differences were tested by Chi-Squared test. A p-value of 0.05 was interpreted as significantly different. For each question, linear logistic regression analysis was performed to estimate predictors for the answers. Socio-demographic factors and a variable for subjective involvement were used as predictors (see Table 1). Participants were classified as subjectively involved when they responded to “How often do you have contact to patients with multi-resistant organisms in daily work?” with “weekly or more often”. All analyses were performed using SPSS [IBM SPSS statistics, Somer, NY, USA] and SAS [SAS Institute, Cary, NC, USA].
Table 1

Demographic characteristics of the participants

Parameter

Responder

Gender, female in percent, n (%)

212 (62.4)

Mean age in years (SD)

51.9 (+/− 8.8)

Mean professional experience in years (SD)

16.7 (+/−10.8)

Medical specialist in percent, n (%)

 General Medicine

288 (84.7)

 Internal Medicine

34 (10)

 None

5 (1.5)

 Other

11 (3.2)

Population of the practice location, n (%)

  < 5,000

56 (16.5)

 5,000–19,000

92 (27.1)

 20,000–99,000

89 (26.2)

  > 100,000

103 (30.3)

Kind of practice, n (%)

 Single practice

193 (56.8)

 Joint Practice

113 (33.2)

 Practice Communities

26 (7.6)

Patient visits per quartile in percent, n (%)

  < 400

5 (1.5)

 400–800

53 (15.6)

 801–1,200

128 (37.6)

 1,201–1,600

98 (28.8)

  > 1,600

48 (14.1)

Contact with patients with MDRO, n (%)

 

 Weekly or more often

67 (19.7)

Note. All listed parameters were predictors in the multivariable analysis. MDRO multidrug-resistant organism

Results

The questionnaire was completed by 340 of 987 (34.4%) GPs. The socio-demographic factors are described in Table 1. Most of the participants were female (62.4%). The mean age was 52 (range 33–78) years and the mean work experience was 16.8 years.

Awareness of antimicrobial resistance

Most of the participants assumed a multifactorial genesis of the rise of multidrug resistant organisms. 80.9% (275/340) of the participants indicated infection control in hospitals, 80.3% (273/340) the use of antibiotics by GPs and 79.1% (261/340) the use of antibiotics in livestock as the main drivers for drug-resistance (multi selection).

The majority of participants (70.2%;239/340) believed that their own prescribing behavior influenced the drug-resistance situation in their area. GPs with longer work experience (> 25 years) assumed less individual influence on drug resistance than do their colleagues with less than 7 years experience as practicing physicians (Odds Ration [OR] 0.32, 95% Confidence Interval [CI] 0.17–0.62; P < 0.001).

Guidelines/source of information

Seven percent (23/340) of the participants stated that there is a lack of good guidelines dealing with antibiotic therapy in ambulatory care. Thirty-nine percent (133/340) of the GPs indicated that they frequently use guidelines for antibiotic therapy. Family doctors under the age of 40 made use of guidelines more often than did those older than 60 (OR 3.97, 95%CI 1.32–11.91; P = 0.001). In addition, the location of their place of work (urban vs. rural) influenced the response to this question (Table 2).
Table 2

Results of the multivariable analysis

Questions

Odds Ratio (95% CI)

Relevance of antimicrobial resistance for daily work

(Answers: strong/medium vs. little/not at all)

 

Contacts to patients with MDRO

 

Monthly or less frequently

Reference

Weekly or more frequently

5.65 (1.71–18.64)

Do you believe that your prescribing behavior influences the drug resistant organism situation in your area?

(Answer: yes vs. no or I don’t know)

 

Work experience

 0–7 years

Reference

 8–14 years

0.91 (0.44–1-91)

 14–25 years

0.44 (0.23–0.85)

  > 25 years

0.32 (0.17–0.62)

Do you use guidelines in your daily routine?

(Answers: frequently vs. sometimes, seldom or never)

 

Population of the practice location

  > 100.000

Reference

 20.000–99.000

0.93 (0.50–1.73)

 5.000–20.000

1.95 (1.07–3.56)

  < 5.000

1.08 (0.53–2.19)

Age (in years)

  > 60

Reference

 56–60

3.22 (1.42–7.31)

 51–55

1.79 (0.76–4.18)

 45–50

2.99 (1.34–6.65)

 40–44

3.17 (1.30–7.72)

< 40

3.97(1.32–11.91)

Do you use the strategy of delayed antibiotic prescription?

(Answer: very often/often vs. sometimes/seldom/unknown strategy)

 

Population of the practice location

  > 100.000

Reference

 20.000–99.000

0.49 (0.26–0.91)

 5.000–20.000

0.39 (0.21–0.75)

  < 5.000

0.57 (0.28–1.17)

Indications for me prescribing antibiotics are …

…acute infection with yellow/green sputum

(rather yes vs. rather not, to a certain degree)

 

Medical specialization

 General Medicine

Reference

 Internal Medicine

2.36 (1.08–5.17)

 No specialization

9.07 (0.85–96.99)

Work experience

 0–7 years

Reference

 8–14 years

1.85 (0.90–3.80)

 14–25 years

3.33 (1.69–6.58)

  > 25 years

6.54 (3.22–13.30)

CI confidence interval, MDRO multidrug resistant organism

Note. Predictors in the multivariable analysis are shown in Table 1

Use of antibiotics

Forty-four percent (151/340) of the GPs stated that one reason for prescribing an antibiotic without a strong indication was that it was just before a weekend when the progression of the infection was difficult to predict. Only 29.4% (74/340) answered that they often or very often apply delayed prescribing, a strategy for dealing with uncomplicated acute respiratory infections in which the use of an antibiotic is recommended to a patient only if the symptoms persist or worsen or further test results come in. 337 of the 340 participants (99.1%) were familiar with this strategy.

Thirty-six percent (123/340; Fig. 1) responded that an acute infection with yellow or green sputum is an indication for antibiotic prescription. GPs with more work experience tended to use the color of sputum more often as an indicator for an antimicrobial therapy (> 25 years of working experience vs. < 7 years; OR 6.54, 95% CI 3.22–13.30; P < 0.001).
Fig. 1
Fig. 1

Diagnostic value of the sputum color. Answers on the statement: “For me, the indications for an antibiotic prescription are the green colour of the sputum (in the context of an acute respiratory tract infection)” (n = 333)

Awareness of antimicrobial resistance and communication aspects

Sixty-eight percent (285/340) of the family doctors stated that they often or very often discuss the subject drug-resistant organisms with patients who have an infection that requires antibiotic therapy; 80.6% (274/340) discuss the subject if the patient does not need antibiotics (Fig. 2). In this survey the main reasons for not discussing this topic were a lack of time (50.6%) and the assumption that their patients were not interested in this subject (42.9%; Fig. 3).
Fig. 2
Fig. 2

AMR communication. Answers on the Question: “Do you discuss the topic of antimicrobial resistance (AMR) with patients with an acute infection?” (n = 338)

Fig. 3
Fig. 3

AMR missing communication (multiple selection). “Reasons not to talk about antibiotic resistance (AMR).” (n = 338)

Discussion

We performed a questionnaire-based survey of general practitioners on patterns of antimicrobial use, patient communication, awareness of rising drug-resistance in primary care and the source of information acquisition.

This study demonstrates different specific barriers to rational antibiotic therapy in primary care. First of all, it should be acknowledged that the awareness of antimicrobial resistance among general practitioners has risen during the past few years. In 2007/2008 the Robert Koch Institute distributed a written survey to GPs in Germany. In that survey, 35.8% of the GPs expressed the belief that their prescribing behavior influences drug-resistance in their area [31, 32]. We repeated this question in our survey and 70.2% (239/340) of the participants agreed that their behavior affected drug resistance. This rising awareness might be influenced by international, European and national reports and campaigns that deal with this topic [3336].

Second, the reliability of sputum color as an indicator for an antimicrobial therapy was overestimated by a majority of the participants. Our investigation found that over one third (36.2%) of the participants use the color as an indication, another third are uncertain (35.9%) and only 25.9% (88/340) of general practitioners do not use sputum color when deciding whether to start antibiotic therapy. Other studies support these findings [28, 37]. In selected diagnoses, especially in chronic lung diseases, the sputum color has a value for antimicrobial therapy decision [38, 39]. Nevertheless, the reproducibility of the evaluation of sputum color has poor inter-rater reliability [40] and is not recommended in the case of an acute respiratory tract infection [41].

In order to work in Germany as a family doctor a 5 year medical specialization in either internal medicine or in general medicine is required. Alternatives to practicing as a general practitioner exist, however rarely. 84.7% (288/340) of the participants have a specialization in general medicine, 10% (34/340) in internal medicine (Table 1). GPs with a specialization in internal medicine were more likely to prescribe an antibiotic based on the color of the sputum than were GPs with a specialization in general medicine (OR 2.36, 95%CI 1.08–5.17; P = 0.03). One explanation for why GPs with a specialization in internal medicine were 2.4 times more likely than participants who specialized in general or family medicine to prescribe antibiotics based on sputum color is that the recommendation not to use the color of the sputum as an indicator is very prominent in the guidelines of the German Society of General Practice and Family Medicine (Deutsche Gesellschaft für Allgemeinmedizin und Familienmedizin, DEGAM) [42]. To address the diagnostic uncertainty between a severe acute bronchitis and a starting pneumonia the biomarker as point of care tests are promising [43]. However the reimbursement for GPs in Germany is difficult. An alternative strategy to reduce antibiotic use is delayed prescription [44, 45]. The strategy is well known among the participants (337/340) while only one third (74/340) apply it “often” or “very often”. There is room for improvement in the implementation of the strategy in daily outpatient care, considering the fact that only 21.8% (74/340) use this strategy often and only 7.6% (26/340) very often.

Third, some authors emphasize that when GPs feel pressure from their patients, they are more likely to prescribe antibiotics [4649]. Accordingly, about one third of the participants (102/340) prescribe antibiotics when a patient requests some or when the patient wants to return to work quickly (97/340). However, in this survey general practitioners who felt pressure from their patients remained a minority. Unfortunately, we did not conduct patient interviews to evaluate patient requests for antibiotic therapy. Nevertheless, supported by other authors, we believe that GPs place too much importance on patient requests for antimicrobial therapy [50, 51] .

Focusing on aspects of communication, it is striking that a lack of time was the main reason not to talk about antimicrobial resistance (172/340). Some authors describe an antibiotic prescription as an effective means to avoid confrontation and to terminate a consultation [28]. Accordingly, the majority of antibiotic prescriptions are inappropriate in ambulatory care [7]. Patient leaflets could be used for this purpose but there is a lack of established German leaflets for acute respiratory tract infections. There are leaflets of the Center for Disease Control and Prevention (CDC) available in English [52].

This study has certain limitations. All answers are self-reported. Furthermore, as a questionnaire study, this survey contains the risk that respondents will give answers believed to be socially acceptable. The representativeness of the study is limited because the sample was not selected purely randomly, but was instead contacted on the basis of existing address data (self-selection bias). On the other hand, the GPs contacted represent about one third of all GPs working in the region. The response rate is comparable to other studies conducted in Germany [30, 53].

Another limitation is that the questionnaire was only distributed in eastern Germany.

This is due to the fact that this survey was performed in preparation for an intervention campaign that started in August 2016 and focused on rational antibiotic use by GPs in eastern Germany. Looking at the socio-demographic parameters of the participants, it is noticeable that they were about 2 years younger (51.9 vs. 54.3) than the GPs average in Germany and were more likely to be female (62.4% vs 41.0 female GPs). There were only minor differences in the type of workplace [54].

Conclusion

When deciding on a therapy, the diagnostic value of sputum color is often overestimated. Delayed prescription is well known but only partially applied. Nevertheless, there is a strong awareness of antimicrobial resistance among the participating GPs. Furthermore, time restrictions disturb doctor-patient communication. Implementation of change to a more rational antibiotic use should address such specific barriers as preconditions to having a sustainable effect. This survey shows clear targets for further approaches to reduce the prevalence of drug-resistant organisms.

Abbreviations

AMR: 

Antimicrobial resistance

CI: 

Confidence interval

GPs: 

General practitioners

OR: 

Odds ratio

RAI: 

Responsible antibiotic use via information and communication

Declarations

Acknowledgements

The authors would like to thank the participating general practitioners and Gerald Brennan for proof-reading the manuscript.

Members of the RAI-Study group.

Muna Abu Sin, Esther-Maria Antao, Michael Behnke, Evgeniya Boklage,

Tim Eckmanns, Christina Forstner, Petra Gastmeier, Jochen Gensichen,

Alexander Gropmann, Stefan Hagel, Regina Hanke, Wolfgang Hanke,

Anke Klingeberg, Lukas Klimmek, Ulrich Kraft, Markus Lehmkuhl, Norman.

Ludwig, Antina Lu¨bke-Becker, Oliwia Makarewicz, Anne Moeser, Inga.

Petruschke, Mathias W. Pletz, Florian Salm, Katja Schmücker, Sandra.

Schneider, Christin Schröder, Frank Schwab, Joachim Trebbe, Szilvia.

Vincze, Horst Christian Vollmar, Jan Walter, Sebastian Weis, Wibke.

Wetzker and Lothar H. Wieler.

First Results of this research were presented at the congress of the German Society of General Practice and Family Medicine (www.degam-kongress.de/2016/).

Funding

This work was supported by the German Federal Ministry of Education and Research within the consortium Infectcontrol2020 (03ZZ0804 A-C).

Availability of data and materials

The datasets used are available from the corresponding author on reasonable request.

Authors’ contributions

Study concept and design: FS, SS, KS, RH, CH, US, PG, JG. Acquisition, analysis, or interpretation of data: FS, SS, KS, RH, CH, US, PG, JG, IP. Statistical analysis: FS, SS, CS, PG. Drafting of the manuscript: FS, PG, SS, TSK, JG. Critical revision of the manuscript for important intellectual content: PG, JG, SS, TSK, IP. All authors read and approved the final manuscript.

Ethics approval and consent to participate

Ethical approval was obtained from the Ethic Committee of the Jena University Hospital (4742–03/16). All participants received a brief explanation of the aims of the questionnaire survey and were informed that the participation was voluntary and that the data analysis would be anonymous. Since no personal data, such as signatures, should be collected, the return of the questionnaire was considered as consent to participate in the study.

Competing interests

The authors declare that they have no competing interests.

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Authors’ Affiliations

(1)
Institute for Infection Prevention and Hospital Epidemiology, Medical Center – University of Freiburg, Breisacher Str. 115 B, D-79106 Freiburg, Germany
(2)
Institute of Hygiene and Environmental Medicine, Charité University Medical Center Berlin, German National Reference Center for the Surveillance of Nosocomial Infections, Hindenburgdamm 27, D-12203 Berlin, Germany
(3)
Institute of General Practice and Family Medicine, Jena University Hospital, Friedrich-Schiller-University, School of Medicine, Bachstrasse 18, D-07743 Jena, Germany
(4)
Lindgrün GmbH, Cuxhavener Strasse 12, D-10555 Berlin, Germany
(5)
Institute Institute for General Practice and Family Medicine, Charité University Medical Center Berlin, Charitéplatz 1, D-10117 Berlin, Germany
(6)
Medizinische Hochschule Brandenburg Theodor Fontane, Fehrbelliner Str. 38, D-16816 Neuruppin, Germany
(7)
Institute for General Practice, Ludwig-Maxilmilians-University/University Hospital, Pettenkofer str.8/10, D-80336 Munich, Germany

References

  1. World Health Organization. ANTIMICROBIAL RESISTANCE global report on surveillance. 2014;Google Scholar
  2. Davies SC, Fowler T, Watson J, Livermore DM, Walker D. Annual report of the chief medical officer: infection and the rise of antimicrobial resistance. Lancet. 2013;381:1606–9.View ArticlePubMedGoogle Scholar
  3. Harbarth S, Balkhy HH, Goossens H, Jarlier V, Kluytmans J, Laxminarayan R, et al. Antimicrobial resistance: one world, one fight. Antimicrob Resist Infect Control. 2015;4:49.View ArticlePubMed CentralGoogle Scholar
  4. Goossens H, Ferech M, Vander Stichele R, Elseviers M. Outpatient antibiotic use in Europe and association with resistance: a cross-national database study. Lancet. 2005;365:579–87.View ArticlePubMedGoogle Scholar
  5. Laxminarayan R, Duse A, Wattal C, Zaidi AKM, Wertheim HFL, Sumpradit N, et al. Antibiotic resistance—the need for global solutions. Lancet Infect Dis. 2013;13:1057–98.View ArticlePubMedGoogle Scholar
  6. Boeckel TPV, Gandra S, Ashok A, Caudron Q, Grenfell BT, Levin SA, et al. Global antibiotic consumption 2000 to 2010: an analysis of national pharmaceutical sales data. Lancet Infect Dis. 2014;14:742–50.View ArticlePubMedGoogle Scholar
  7. Fleming-Dutra KE, Hersh AL, Shapiro DJ, Bartoces M, Enns EA, File TM, et al. Prevalence of inappropriate antibiotic prescriptions among US ambulatory care visits, 2010-2011. JAMA. 2016;315:1864–73.View ArticlePubMedGoogle Scholar
  8. Wang J, Wang P, Wang X, Zheng Y, Xiao Y. Use and prescription of antibiotics in primary health care settings in China. JAMA Intern Med. 2014;174:1914–20.View ArticlePubMedGoogle Scholar
  9. Hersh AL, Shapiro DJ, Pavia AT, Fleming-Dutra KE, Hicks LA. Geographic variability in diagnosis and antibiotic prescribing for acute respiratory tract infections. Infect Dis Ther. 2018;7(1):171-174. https://doi.org/10.1007/s40121-017-0181-y. Epub 2017 Dec 22.
  10. Laxminarayan R, Van Boeckel TP. The value of tracking antibiotic consumption. Lancet Infect Dis. 2014;14:360–1.View ArticlePubMedGoogle Scholar
  11. Bätzing-Feigenbaum J, Schulz M, Schulz M, Hering R, Kern WV. Outpatient antibiotic prescription: a population-based study on regional age-related use of cephalosporins and fluoroquinolones in Germany. Dtsch Ärztebl Int. 2016;113:454.PubMedPubMed CentralGoogle Scholar
  12. Versporten A, Bolokhovets G, Ghazaryan L, Abilova V, Pyshnik G, Spasojevic T, et al. Antibiotic use in eastern Europe: a cross-national database study in coordination with the WHO regional Office for Europe. Lancet Infect Dis. 2014;14:381–7.View ArticlePubMedGoogle Scholar
  13. Adriaenssens N, Coenen S, Versporten A, Muller A, Minalu G, Faes C, et al. European surveillance of antimicrobial consumption (ESAC): outpatient antibiotic use in Europe (1997–2009). J Antimicrob Chemother. 2011;66:vi3–vi12.PubMedGoogle Scholar
  14. Kern WV. Entwicklung des Antibiotikaverbrauchs in der ambulanten vertragsärztlichen Versorgung. https://www.versorgungsatlas.de/fileadmin/ziva_docs/50/VA-50b-65-66-Update%20Antibiotikaverordnung-Infoblatt-V1_1.pdf
  15. Bundesamt für Verbraucherschutz und Lebensmittelsicherheit, Paul-Ehrlich-Gesellschaft für Chemotherapie e.V. GERMAP 2015–Bericht über den Antibiotikaverbrauch und die Verbreitung von Antibiotikaresistenzen in der Human-und Veterinärmedizin in Deutschland. Rheinbach: Antiinfectives Intelligence; 2016.Google Scholar
  16. Bätzing-Feigenbaum J, Schulz M, Schulz M, Hering R, Kern WV. Outpatient Antibiotic Prescription. Dtsch Arzteblatt Int. 2016;113:454–9.Google Scholar
  17. Schulz M, Kern WV, Hering R, Schulz M, Bätzing-Feigenbaum J. Antibiotikaverordnungen in der ambulanten Versorgung in Deutschland bei bestimmten Infektionserkrankungen. Teil 1 und 2. 2014;Google Scholar
  18. Polgreen PM, Yang M, Laxminarayan R, Cavanaugh JE. Respiratory fluoroquinolone use and influenza. Infect Control Hosp Epidemiol. 2011;32:706–9.View ArticlePubMedPubMed CentralGoogle Scholar
  19. Harris AM, Hicks LA, Qaseem A. Appropriate antibiotic use for acute respiratory tract infection in adults: advice for high-value care from the American College of Physicians and the centers for disease control and PreventionAppropriate antibiotic use for acute respiratory tract infection in adults. Ann Intern Med. 2016;Google Scholar
  20. Smith SM, Smucny J, Fahey T. Antibiotics for acute bronchitis. JAMA. 2014;312:2678–9.View ArticlePubMedGoogle Scholar
  21. Garbutt JM, Banister C, Spitznagel E, Piccirillo JF. Amoxicillin for acute rhinosinusitis: a randomized controlled trial. JAMA. 2012;307:685–92.View ArticlePubMedPubMed CentralGoogle Scholar
  22. Lemiengre MB, van Driel ML, Merenstein D, Young J, De Sutter AIM. Antibiotics for clinically diagnosed acute rhinosinusitis in adults. Cochrane Database Syst Rev. 2012;10:CD006089.PubMedGoogle Scholar
  23. Remschmidt C, Schneider S, Meyer E, Schroeren-Boersch B, Gastmeier P, Schwab F. Surveillance of antibiotic use and resistance in intensive care units (SARI). Dtsch Arzteblatt Int. 2017;114:858–65.Google Scholar
  24. Busse R, Riesberg A, Organization WH. Health care systems in transition: Germany. 2004;Google Scholar
  25. Salm F, Schneider S, Gastmeier P. InfectControl 2020: rational antibiotic use by information and communication-the RAl project. Umweltmed Hyg Arbeitsmedizin. 2017;22:301–4.Google Scholar
  26. Gonzales R, Anderer T, McCulloch CE, et al. A cluster randomized trial of decision support strategies for reducing antibiotic use in acute bronchitis. JAMA Intern Med. 2013;173:267–73.View ArticlePubMedPubMed CentralGoogle Scholar
  27. Murray S, Mar CD, O’Rourke P. Predictors of an antibiotic prescription by GPs for respiratory tract infections: a pilot. Fam Pract. 2000;17:386–8.View ArticlePubMedGoogle Scholar
  28. Altiner A, Wilm S, Däubener W, Bormann C, Pentzek M, Abholz H-H, et al. Sputum colour for diagnosis of a bacterial infection in patients with acute cough. Scand J Prim Health Care. 2009;27:70–3.View ArticlePubMedPubMed CentralGoogle Scholar
  29. Salm F, Ernsting C, Kuhlmey A, Kanzler M, Gastmeier P, Gellert P. Antibiotic use, knowledge and health literacy among the general population in berlin, Germany and its surrounding rural areas. PLoS One. 2018;13:e0193336.View ArticlePubMedPubMed CentralGoogle Scholar
  30. Velasco E, Ziegelmann A, Eckmanns T, Krause G. Eliciting views on antibiotic prescribing and resistance among hospital and outpatient care physicians in berlin, Germany: results of a qualitative study. BMJ Open. 2012;2:e000398.View ArticlePubMedPubMed CentralGoogle Scholar
  31. Velasco E, Espelage W, Faber M, Noll I, Ziegelmann A, Krause G, et al. A national cross-sectional study on socio-behavioural factors that influence physicians’ decisions to begin antimicrobial therapy. Infection. 2011;39:289–97.View ArticlePubMedGoogle Scholar
  32. Velasco E, Eckmanns T, Espelage W, Barger A, Krause P-DDG. Einflüsse auf die ärztliche Verschreibung von Antibiotika in Deutschland (EVA-Studie). Bundesminist Für Gesundh Berl. 2009:1–54.Google Scholar
  33. Word Health Organization. Evaluation of antibiotic awareness campaigns. 2017 [cited 2017 Feb 21]; Available from: http://www.who.int/selection_medicines/committees/expert/21/applications/antibacterials-ccps_rev/en/
  34. Earnshaw S, Monnet DL, Duncan B, O’Toole J, Ekdahl K, Goossens H, et al. European antibiotic awareness day, 2008: the first Europe-wide public information campaign on prudent antibiotic use: methods and survey of activities in participating countries. Eurosurveillance Eur Commun Dis Bull Communities Comm Communautés Eur Comm-St-Maurice. 2009;14:23–30.Google Scholar
  35. Get Smart About Antibiotics | Poster-Based Interventions | CDC [Internet]. [cited 2015 Jun 9]. Available from: http://www.cdc.gov/getsmart/community/improving-prescribing/interventions/poster-based.html
  36. ECDC E. The bacterial challenge: time to react. Stockh Eur Cent Dis Prev Control. 2009; http://www.simpios.eu/2017/02/03/ecdcemea-joint-technical-report-the-bacterial-challenge-time-to-react/
  37. Teixeira Rodrigues A, Ferreira M, Piñeiro-Lamas M, Falcão A, Figueiras A, Herdeiro MT. Determinants of physician antibiotic prescribing behavior: a 3 year cohort study in Portugal. Curr Med Res Opin. 2016;32:949–57.View ArticlePubMedGoogle Scholar
  38. Pabreja K, Gibson P, Lochrin AJ, Wood L, Baines KJ, Simpson JL. Sputum colour can identify patients with neutrophilic inflammation in asthma. BMJ Open Respir Res. 2017;4:e000236.View ArticlePubMedPubMed CentralGoogle Scholar
  39. Mackay AJ, Patel ARC, Garcha DS, Brill SE, Donnelly LE, Barnes PJ, et al. Sputum color and the detection of colonizing Bacteria by quantitative Pcr in stable COPD. Am J Respir Crit Care Med. 2014;189:A1017.Google Scholar
  40. Reychler G, Andre E, Couturiaux L, Hohenwarter K, Liistro G, Pieters T, et al. Reproducibility of the sputum color evaluation depends on the category of caregivers. Respir Care. 2016;61:936–42.View ArticlePubMedGoogle Scholar
  41. Holzinger F, Beck S, Dini L, Stöter C, Heintze C. The diagnosis and treatment of acute cough in adults. Dtsch Ärztebl Int. 2014;111:356–63.PubMedPubMed CentralGoogle Scholar
  42. German Society of General Practice and Family Medicine [Internet]. [cited 2016 Nov 8]. Available from: http://www.degam-leitlinien.de/
  43. Aabenhus R, Jensen J-US, Jørgensen KJ, Hróbjartsson A, Bjerrum L. Biomarkers as point-of-care tests to guide prescription of antibiotics in patients with acute respiratory infections in primary care. Status Date New Publ In. 2014; Cochrane Database Syst Rev. 2014;(11):CD010130. https://doi.org/10.1002/14651858.CD010130.pub2.
  44. Spurling GK, Del Mar CB, Dooley L, Foxlee R, Farley R. Delayed antibiotic prescriptions for respiratory infections. Cochrane Libr. 2017;Google Scholar
  45. de la P Abad M, Dalmau GM, Bakedano MM, AIG G, Criado YC, Anadón SH, et al. Prescription strategies in acute uncomplicated respiratory infections: a randomized clinical trial. JAMA Intern Med. 2016;176:21–9.View ArticleGoogle Scholar
  46. Watson RL, Dowell SF, Jayaraman M, Keyserling H, Kolczak M, Schwartz B. Antimicrobial use for pediatric upper respiratory infections: reported practice, actual practice, and parent beliefs. Pediatrics. 1999;104:1251–7.View ArticlePubMedGoogle Scholar
  47. Bauchner H, Pelton SI, Parents KJO. Physicians, and antibiotic use. Pediatrics. 1999;103:395–401.View ArticlePubMedGoogle Scholar
  48. Palmer DA, Parents BH. Physicians’ views on antibiotics. Pediatrics. 1997;99:e6.View ArticlePubMedGoogle Scholar
  49. Cockburn J, Pit S. Prescribing behaviour in clinical practice: patients’ expectations and doctors’ perceptions of patients’ expectations—a questionnaire study. BMJ. 1997;315:520–3.View ArticlePubMedPubMed CentralGoogle Scholar
  50. Altiner A, Knauf A, Moebes J, Sielk M, Wilm S. Acute cough: a qualitative analysis of how GPs manage the consultation when patients explicitly or implicitly expect antibiotic prescriptions. Fam Pract. 2004;21:500–6.View ArticlePubMedGoogle Scholar
  51. Broniatowski DA, Klein EY, Reyna VF. Germs are germs, and why not take a risk? Patients’ expectations for prescribing antibiotics in an Inner-City emergency department. Med Decis Mak. 2014:0272989X14553472.Google Scholar
  52. US Centers for Disease Control and Prevention. Get Smart - Know when antibiotics work [Internet]. 2017. Available from: https://www.cdc.gov/getsmart/community/index.html
  53. Faber MS, Heckenbach K, Velasco E, Eckmanns T. Antibiotics for the common cold: expectations of Germany’s general population. Euro Surveill Bull Eur Sur Mal Transm Eur Commun Dis Bull. 2010;15Google Scholar
  54. Kassenärztliche Bundesvereinigung. Ärztemonitor 2016 [Internet]. Tabellenband. Available from: http://www.kbv.de/html/aerztemonitor.php. Cited 21 Nov 2017.

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