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Infectious Diseases and Therapy logoLink to Infectious Diseases and Therapy
. 2021 Nov 9;11(1):617–628. doi: 10.1007/s40121-021-00552-1

Antimicrobial Stewardship with and without Infectious Diseases Specialist Services to Improve Quality-of-Care in Secondary and Tertiary Care Hospitals in Germany: Study Protocol of the ID ROLL OUT Study

Nicole Zimmermann 1,#, Rebekka Allen 1,✉,#, Geertje Fink 2, Gesche Först 2, Winfried V Kern 2, Erik Farin-Glattacker 1,#, Siegbert Rieg 2,#; the ID ROLL OUT Study group
PMCID: PMC8576457  PMID: 34751941

Abstract

Background

Antimicrobial stewardship (AMS) programs aim to secure the rational prescription of antibiotics through implementing department- or hospital-level activities. Infectious disease (ID) specialists improve the quality of care and outcomes in infection patients predominantly by individual consultations and patient-level interventions. While hospital AMS programs are established to various extents in Germany, ID specialist services are rarely available in this country. In the ID ROLL OUT study, we will implement and evaluate hospital-level AMS tools with and without ID specialist services in secondary and tertiary care hospitals. We aim to identify means to comprehensively and sustainably improve the quality of care of patients with infectious diseases.

Methods

This project is a clustered, two-armed intervention study, which will be conducted in ten secondary and tertiary (non-university) care hospitals in Germany. The intervention groups are stratified by key characteristics of the hospitals. We will compare two interventional strategies: implementation of AMS teams and implementation of AMS teams combined with the activities of ID specialists (AMS + IDS).

Planned Outcomes

The primary outcome is the quality of care as measured in changes in a Staphylococcus aureus bacteremia (SAB) score (as an indicator of difficult-to-treat infections) and a community-acquired pneumonia (CAP) score (as an indicator of common infections) compared to a baseline pre-interventional period. Our secondary outcomes comprise patient- and hospital-level outcomes, such as the quality and frequency of antibiotic treatment, in-hospital mortality, duration of hospitalization, and C. difficile incidence (associated diarrhea episodes). The study may provide urgently needed key information for the aspired advancement of ID care in Germany.

Trial Registration

DRKS00023710 (registered on 9th April 2021).

Supplementary Information

The online version contains supplementary material available at 10.1007/s40121-021-00552-1.

Keywords: Antibiotic stewardship (ABS), Infectious diseases specialist, Consultation, Antibiotic resistance, Community-acquired pneumonia, Staphylococcus aureus bacteremia

Key Summary Points

Infectious disease (ID) specialist services are known to improve ID patients’ quality of care, but are rarely implemented in German hospitals
The ID ROLL OUT study is a prospective clustered two-armed interventional trial with a pre-post design conducted in ten secondary and tertiary care hospitals in the Federal state of Baden-Württemberg, Germany
We will evaluate the impact of implementing Antimicrobial stewardship (AMS) teams or AMS teams combined with the activities of ID specialists by measuring patient- and hospital-level outcomes
We hypothesize that the interventions will improve adherence to diagnostic and therapeutic quality-of-care indicators, enhance rationale antibiotic prescribing without increasing in-hospital mortality, reduce costs, and shorten the hospital length of stay
The study aims to provide important data on measures to improve the quality of ID care and will delineate structural and personnel requirements that may be used to guide innovations in routine ID care in Germany

Introduction

Background

Even before the current SARS-CoV-2 pandemic, it had become evident that infectious diseases constitute a major threat to human health [1, 2], showing, once again, an optimal diagnostic and therapeutic management of infections is essential. Due to the growing numbers of patients with implanted foreign devices, or profound immunosuppression [3] and (multi)drug-resistant pathogens causing severe healthcare-associated infections [2], the management of infectious diseases (ID) will become increasingly complex [4].

Antimicrobial Stewardship (AMS) programs aim to optimize antimicrobial treatments and avoid overuse through a rational and responsible prescription of antimicrobials. It has been reported that about one third of antimicrobial prescriptions in hospitals are considered eligible for optimization [5, 6]. The proportion of inappropriate antimicrobial prescriptions in Germany is described as similar [7]. AMS programs establish strategies and measures in a systematic, i.e., hospital level, or institutional approach resulting in a shorter hospital length of stay, reduced mortality, and better patient safety [812].

The involvement of ID specialists enhances the quality of care primarily by a more patient-level approach [13, 14]. There is convincing evidence that ID specialist consultations improve adherence to diagnostic and therapeutic management standards (e.g., for community-acquired pneumonia [CAP]), which translates to improved survival, particularly in the context of severe infections, such as Staphylococcus aureus bacteremia (SAB), candidemia, or infective endocarditis [9, 1520]. Moreover, ID specialist services play a major role in the rational prescription of antimicrobials and the containment of infections by (multi)drug-resistant pathogens [21]. The Infectious Diseases Society of America and the Society for Healthcare Epidemiology of America claim that AMS programs are best led by ID specialists with additional AMS training [10, 21].

While in Germany AMS programs are established to various and often limited extents, ID specialist services are implemented mainly in university hospitals and very rarely in secondary and tertiary care hospitals. Until recently, there have been fewer than five ID specialists per million inhabitants in Germany [22]. As the number of ID specialists diverges from the steadily increasing demand [2123], the German government established an incentive program to strengthen the training of ID specialists. In spring 2021, the delegates of the German Medical Association enacted to implement an ID specialist training program with a 6-year curriculum, equivalent to other internal medicine specialist areas [24]. It has, as yet, been undetermined how and to which extent ID specialist services can be implemented in secondary and tertiary care hospitals, how collaboration with AMS teams should be organized, and at what intensity or staffing ratio this should ideally be performed.

Growing evidence reveals that AMS programs are less effective if they exclude the determining factors of the organizational, structural, personal, and psychological contexts [25, 26]. Key barriers to antimicrobial prescription behavior improvements are concerns about potentially negative patient-level outcomes, the hierarchical structures, lack of communication skills, and team dynamics [25, 27, 28]; we therefore address these determinants in our study.

Objectives

The present study aims to implement and examine the effect of AMS teams with and without ID specialist services (AMS + IDS) on patient- and hospital-level outcome measures. Besides evaluating diagnostic and therapeutic measures, we will perform a process evaluation to investigate the feasibility and intensity of the interventions’ implementation from both a medical and pharmaceutical perspective. Generated insights may provide urgently needed key information for the optimized care of patients with ID in secondary and tertiary care hospitals in Germany.

We hypothesize that (1) patient- and hospital-level outcomes of both intervention groups (AMS teams and AMS + IDS) will be significantly different (improved) compared to the baseline. Furthermore, we presume that (2) the effects in the more complex intervention AMS + IDS will be greater than for AMS teams. We assume that the interventions will be accepted and deemed beneficial (3), AMS + IDS more than AMS teams.

Methods

Study Design

We designed a 3-year multicenter, prospective, two-armed intervention study with a pre-post analysis. Ten secondary and tertiary care hospitals (accounting for ~ 10% of hospital beds in the federal state of Baden-Württemberg) will participate. The allocation to groups will be stratified by hospital key characteristics (e.g., number of hospital beds, type of departments). Structural characteristics in terms of baseline AMS activities will be described by using the ICATB2 score, a composite score for AMS framework, resources, and action [29]. During the initial baseline year (2021), we arrange project preparations and offer a test phase for data entry and a workshop with the entire study staff to assess the specific needs, while the hospitals provide care as usual. We document the primary and secondary outcomes at baseline. This study phase also includes the detailed planning of the interventions by tackling organizational, structural, personal, and psychological aspects as well as potential psychological barriers and approaching facilitators.

During the second year, which includes a wash-in phase, the interventions will be implemented in two intervention groups, resulting in five hospitals for each group. We will train the teams during the implementation of the interventions. To adapt the interventions, if necessary, we will conduct a further workshop midway through the intervention phase [30]. We perform a process evaluation with semi-structured interviews after 6 and 12 months during the intervention. Figure 1 shows the study schedule.

Fig. 1.

Fig. 1

Schedule of the study phases

Interventions

We introduce a bundle of AMS interventions in 240 all hospitals in varying degrees between the two 241 groups (AMS teams vs. AMS + IDS) (Table 1). The interventions are planned and conducted following the national AMS Guideline [31]. The bundle includes:

  • introducing formal AMS teams

  • preparation and implementation of local prescribing guidelines and dosing recommendations for antimicrobials

  • defining antimicrobial restrictions and implementation of mandatory prescription authorizations for reserve antibiotics, in agreement with the local institutional policies

  • regular prescription audits through the AMS-team members (hospital-level point-prevalence surveys)

  • regular educational events for prescribers, lectures and interactive workshops carried out by the AMS-team members, focusing on ID diagnostic, antimicrobial prescribing and case reviews, including feedback on antimicrobial use and resistance patterns

  • local AMS team visits on selected wards (intensive care units and wards with high antimicrobial use) conducted by local AMS Team members. The visits comprise the review of antimicrobial therapies (verification of the indication, review of drug, dosing, route of administration, and duration) and peer-to-peer discussion of the recommendations with the prescriber

  • local IDS visits on selected wards (intensive care units and wards with high antimicrobial use) conducted by ID specialists. The visits comprise the complex evaluation of infections (site of infection, pathogen, susceptibility), the clinical condition of the patients, the review of the antimicrobial therapies (see above), peer-to-peer discussion of the recommendations with the prescriber, and a brief written recommendation

  • availability of an ID consultation service

Table 1.

Comparison of interventions

AMS teams AMS + IDS
Antimicrobial prescribing guidelines Antimicrobial prescribing guidelines
Dosing recommendations Dosing recommendations
Educational events for prescribers (1 × 10 min lecture per department; 1–2 × 45 min. workshop/s per hospital) Educational events for prescribers (3 × 10 min lecture per department; > 3–4 × 45 min workshop per hospital)
Antimicrobial restriction and prescription authorization Antimicrobial restriction and prescription authorization
Prescription audit (hospital-level point-prevalence survey every 3 months) Prescription audit (hospital-level point-prevalence survey every 3 months)
AMS team visits (intensive care units, wards with high anti-infective prescription rate) 1–2 × weekly IDS visits (intensive care units, wards with high anti-infective prescription rate) 2–4 × weekly
ID consultation service

Sample Selection

Concerning our primary and secondary outcome variables (for further details, see Table 3), we will have two samples: sample A and sample B. Sample A comprises the primary patient-level outcome variables, diagnosed with one of the two indicator diseases (SAB or CAP). Sample B refers to the hospital-level outcome variables.

Table 3.

Overview of measurements and outcomes

Measurements Instruments Groups Data Source Data analysis
Primary outcomes
 SAB data set Questionnaire Baseline/AMS teams and AMS + IDS Anonymous patient records Quantitative analysis
 CAP data set Questionnaire Baseline/AMS teams and AMS + IDS Anonymous patient records Quantitative analysis
Secondary outcomes
 Patient levela Questionnaire Baseline/AMS teams and AMS + IDS Anonymous patient records Quantitative analysis
 Hospital levelb Questionnaire and point prevalence analysis Baseline/AMS teams and AMS + IDS Anonymous patient records, hospital records Quantitative analysis
 Claims data of insurance records Aggregated data All patients insured by the AOK Health insurance company, AOK Quantitative analysis
 Process evaluation Focus group and individual interviews Medical staff (physicians and pharmacists) Medical staff Qualitative analysis

aThe patient-level variable contains in-hospital mortality, length of hospital stay, 30-day readmission rates, C. difficile incidence, and costs

bThe hospital-level variable contains antibiotic prescription quality and density, adherence to quality indicators, cost calculations (diagnostic and anti-infective costs, hospital length of stay, personnel, and intervention costs)

Regarding those secondary outcomes that will be provided by the health insurance company, the Allgemeine Ortskrankenkasse (AOK), the sample includes all newly admitted AOK-insured patients who have been diagnosed with SAB or CAP during the specified inclusion period. The AOK covers approximately 50% of Baden-Wuerttemberg’s health insured population [32].

For the interviews within the process evaluation, we will apply the purposeful sampling technique to select the most promising sample, i.e., participants of the intervention team [33].

Inclusion and Exclusion Criteria

Inclusion criteria for sample A are either SAB or CAP (for further details, see Table 4 in the electronic supplementary material). For sample B, all inpatients of the respective hospitals are included, except for patients of the pediatric clinic and psychiatric departments. We will exclude incomplete data regarding the indicator diseases from the analysis.

Sample Size

Considering a dropout of 50%, our sample regarding CAP will contain 335 cases. Regarding the endpoint SAB, our sample will contain 110 cases in total. According to case numbers of SAB and CAP from previous years (which were reviewed by the centers involved), we assume we will be able to recruit the outlined numbers of cases, as we calculated with conservative recruitment rates, and it is highly unlikely that a significant decrease in incidence rates will occur. To prevent missing values, we plan a post-processing phase to complete the data should the maximum missing value of > 5% be exceeded. Concerning the power analysis, we assume that the effects (additional variance clarification by including group membership in our regression model) in the group AMS + IDS will be within the range of medium-high effects (f2 = 0.12) and for group AMS teams within the range of low to medium-high effects (f2 = 0.08) for our primary outcomes, SAB and CAP. We suppose, in accordance with standard conventions, a power of 0.80 and an alpha level of 5%, which was calculated by using the software "G*Power" [34, 35].

Measurements

The primary patient-level outcome is a 5-item SAB score and a 4-item CAP score (see Table 2), developed by the study staff based on current literature [36, 37]. Both dichotomous scores rate appropriate diagnostic and adequate treatment. Table 3 provides a detailed overview of the outcome measures, data source, and analysis.

Table 2.

Overview of SAB and CAP scores

Five-scale SAB score
(1 point, if applicable)
Four-scale CAP score
(1 point, if applicable)
Follow-up blood cultures drawn within 48 h after initial treatment Blood culture drawn prior to antibiotics
Antimicrobial treatment according to guidelines concerning agent and duration Adequate treatment duration (< 7 days on the regular ward)
Performance of TTE and/or TEE Initial therapy according to guidelines
Adequate search for SAB focus and metastatic manifestations Recommendation of influenza and pneumococcal vaccination
Focus eradication control

Primary Outcomes

SAB

The SAB data set comprises 171 variables, with a SAB score consisting of five variables. The variables were selected as several studies demonstrated that adherence to these diagnostic and therapeutic quality-of-care indicators are associated with improved outcomes in SAB patients [17, 36, 38].

CAP

The CAP data set is composed of 159 variables, including a CAP score composed of 4 variables, which are already used (and validated) as process indicators of quality of care in the German health care system and shown to be associated with improved survival/outcome [3943].

Secondary Outcomes

Patient Level

As secondary patient-level outcomes, we will analyze in-hospital mortality, length of hospital stay, 30-day readmission rates, C. difficile incidence, and overall costs (including anti-infective and diagnostic costs).

Hospital Level

Secondary hospital-level outcomes are antimicrobial prescription quality and density ascertained via a point prevalence survey, adherence to quality indicators, and overall cost calculations, such as diagnostic and anti-infective costs, hospital length of stay, personnel, and intervention costs.

Claims Data of Insurance Records

The health insurance company will provide aggregated data on patient mortality (number of patients who died during a 30-day follow-up period after discharge), hospital length of stay, inpatient re-admission, case mix index of the participating hospitals, patient age, and the number of patients selected during the inclusion period and C. difficile incidence.

Process Evaluation

For the process evaluation, we will conduct interviews 6 and 12 months after starting the intervention phase to analyze the implementation process and, if necessary, to optimize the interventions during the workshop. The interview will be semi-structured and conducted by our staff. The focus of the process evaluation will be the interventions’ execution, barriers, and solutions as well as feasibility and benefits. We will also consider organizational, structural, personal, and psychological aspects.

Data Collection

Study physicians and pharmacists of the ten secondary or tertiary hospitals will collect and record the primary, patient-level, and some hospital-level secondary outcomes. We will therefore provide the study staff with the REDCap online data collection tool, version 10.6.13. The hospital-level secondary outcomes will be recorded across all patients by the responsible hospital. The health insurance company will provide us with the aggregated hospital-level secondary outcomes. Due to the anonymized data collection process, an informed consent will not be required; however, all the patients will be informed about the study upon their hospital admission.

Regarding the process evaluation, we will conduct semi-structured individual and focus group interviews at two time points (intermediate and at the end of the project) with participants of the intervention team after obtaining informed consent. Semi-structured interviews are suitable for problem-based and dialogical research questions, which match our purposes [44, 45]. Focus group interviews will be applied to explore the attitudes and experiences of the different groups [46].

The data collection process for the baseline phase started in April 2021. We will collect data for the intervention phase by the end of 2022.

There is no reason to assume that our interventions might lead to unfavorable patient outcomes. Moreover, our study is neither a Medicinal Products Act study nor does it involve experimental or high-risk interventions which necessitate a Data Safety Monitoring Board sensu stricto. Nevertheless, outcomes such as antimicrobial prescription quality and density (ascertained via point prevalence surveys) and adherence to quality indicators are measured every 3 months. Thus, if a negative impact of the intervention is observed, we will be able to approach the specific hospital and study team.

Data Analysis

During the third year of the study, we will evaluate the gathered data and publish the findings.

Analysis of the Primary and Secondary Outcomes

Even with a number of just ten clusters, multilevel modeling may result in unbiased estimations for the regression coefficients and standard errors [47]. We will use a restricted maximum likelihood compared to the use of maximum likelihood estimation as this is recommended in such situations. If so, propensity score-weighted estimators for clustered data will be applied. The patients of AMS teams and AMS + IDS having similar propensity scores can be considered as comparable, even though their scores on the individual factors influencing group membership may differ [48]. Furthermore, the study will explore the proportion of outcome variance explained by hospitals (high proportions argue for hospital-specific factors of success) and conduct patient subgroup analysis.

We will apply a generalized multilevel analysis with a log link and a gamma distribution for the cost indicator analysis to account for the right skewness common in cost data as well as for the point prevalence survey. We will then correlate the outcome variables with the total costs as part of a cost-effectiveness analysis and compare the reduction of antimicrobial with hospitals of comparable size in Germany. We will conduct sensitivity analyses of the samples. The number of patients with inpatient re-admission (for any reason) includes a 95% confidence interval. We will further analyze the patients’ age (mean, standard deviation) and check for gender effects.

As the data provided by the AOK will be aggregated for data protection reasons, we will use, among others, meta-analytical techniques. These enable inferential statistics about target variables by combining statistical parameters of individual samples, although no data on individuals are available.

Analysis of the Process Evaluation

The interview data’s valuation will be based on the multi-stage qualitative content analysis procedure according to Mayring [49] and using the Max QDA Plus software.

Compliance with Ethics Guidelines

This study was approved by the Institutional Review Board of the Ethics Committee at Albert Ludwig University of Freiburg (reference no. 21-1073, 23-03-2021) as well as the Ethics Committee of the State Medical Council of Baden-Württemberg (reference no. B-F-2021-037, 12-04-2021). We confirm that the necessary steps were taken to adhere to the legislation in Germany and that the ethics committees at each site were consulted as required. The Institutional Review Board of the Albert Ludwig University of Freiburg waived the need for written informed consent. We performed all procedures in accordance with the ethical standards of the institutional or national research committee as well as the 1964 Helsinki Declaration and its later amendments or with comparable ethical standards. This study protocol adheres to the recommended SPIRIT checklist. This study is funded by the Innovation Committee of the Federal Joint Committee (G-BA) supported by the Innovation Fund (proposal-ID: NVF2_2019-062). We will report important protocol amendments to and adapted by the Ethics Committee at Albert Ludwig University of Freiburg.

Strengths and Limitations

While AMS programs are established to various extents, ID specialist services are rarely implemented in routine care in Germany. In the ID ROLL OUT study, we will implement and evaluate holistic AMS tools with and without ID specialist services in secondary and tertiary care hospitals. We aim to identify means to comprehensively and sustainably improve the quality of care of patients with infections. The results of the two-armed study will be directly transferable to secondary and tertiary care hospitals throughout Germany.

The project is also designed to assess implementation barriers and promoting factors. We hypothesize that by analyzing these factors the investigated strategies can be implemented in clinical practice of other secondary and tertiary care hospitals without major transfer efforts. To successfully and sustainably realize the holistic intervention and to achieve an effective roll-out, we will consider relevant organizational, structural, personal, and psychological aspects to capture the diversity of the study staff. The idea is to not enforce the change in behavior on the participating medical staff, but rather to develop the innovation collaboratively. Studies have demonstrated that a participatory approach when implementing change is more likely to be accepted by individuals [25, 26].

There might be limitations due to non-randomization. However, we will stratify the hospitals by their specific characteristics, which is an appropriate approach due to the relatively small number of hospitals. During the current pandemic situation, the patient population and hospital admission rates may differ from our case calculation, which might impact upon recruitment and infection rates.

Supplementary Information

Below is the link to the electronic supplementary material.

Acknowledgments

Funding

This research is funded by the Innovation Committee of the Federal Joint Committee (G-BA) supported by the Innovation Fund (proposal-ID: NVF2_2019-062). This funding source had no role in the design of this study and will not have any role during its execution, analyses, interpretation of the data, or decision to submit results. Email: info@if.g-ba.de. The Journal’s Rapid Service Fee was funded by the Baden-Wuerttemberg Ministry of Science, Research and Art and the University of Freiburg in the funding programme Open Access Publishing.

Authorship

All named authors meet the International Committee of Medical Journal Editors (ICMJE) criteria for authorship for this article, take responsibility for the integrity of the work as a whole, and have given their approval for this version to be published.

Author contributions

Nicole Zimmermann and Rebekka Allen contributed equally to this paper and wrote the manuscript with the support of Geertje Fink and Gesche Först. Erik Farin-Glattacker, Winfried V. Kern, and Siegbert R Rieg conceived and designed the study and supervised the project. All authors contributed to the refinement of the study protocol and approved the final manuscript.

Collaborators

U. Solzbach, H. Friedrich, C. van Uden, K. Meyer, H. Hebart, T. Tremmel, M. Bommer, A. Busch, A. Schmidt, S. Polk, P. La Rosée, M. Geiser, S. Mertins, C. Schuhmacher, M Götz, A. von Amlen-Mayerhofer, F. Khaleqi, K. Winter, M. Ritter, F. Wagner, S. Reinecke, Sr. Karin Johanna Haase, S. Horn, S. Lindner, B. Reistle, M. Kollum, P. Buchal, M. Schmid, S. Müller, S. Sorichter, R. Grüninger, Y. Wuwer, H. Niese, T. Iber, D. Hohenstein, U. Witten-Stephan, D. Wirth, M. Steib-Bauert, K. Kaier, M. Sehlbrede.

Disclosures

Nicole Zimmermann, Rebekka Allen, Geertje Fink, Gesche Föerst, Erik Farin-Glattacker, Winfried V. Kern, and Siegbert R Rieg all have nothing to disclose.

Compliance with Ethics Guidelines

This study was approved by the Institutional Review Board of the Ethics Committee at Albert Ludwig University of Freiburg (reference number 21-1073, 23-03-2021) as well as of the Ethics Committee of the State Medical Council of Baden-Württemberg (reference number B-F-2021-037, 12-04-2021). We confirm that the necessary steps were taken to adhere to the legislation in Germany and that the ethics committees at each site were consulted as required. The Institutional Review Board of the Albert Ludwig University of Freiburg waived the need for written informed consent. We performed all procedures in accordance with the ethical standards of the institutional or national research committee, as well as the 1964 Helsinki Declaration and its later amendments or with comparable ethical standards. This study protocol adheres to the recommended SPIRIT checklist. This study is funded by the Innovation Committee of the Federal Joint Committee (G-BA) supported by the Innovation Fund (proposal-ID: NVF2_2019-062). We will report important protocol amendments to and adapted by the Ethics Committee at Albert Ludwig University of Freiburg.

Data Availability

Data sharing is not applicable to this article as no datasets were yet generated or analyzed during the current study. The data files, statistical details and codes will be available from the corresponding authors. However, unrestricted, unreasonable data-sharing is not planned.

Dissemination

We will publish the study results in impactful peer-reviewed journals and present them at scientific conferences to provide data for health care professionals, the wider ID, and public health research communities.

Monitoring

A data monitoring committee (DMC) will not be needed as known risks are minimal.

Footnotes

The ID ROLL OUT Study Group Collaborators members are listed in the Acknowledgement section.

Nicole Zimmermann and Rebekka Allen are co-first authors.

Erik Farin-Glattacker and Siegbert Rieg are co-last authors.

Contributor Information

Rebekka Allen, Email: rebekka.allen@uniklinik-freiburg.de.

the ID ROLL OUT Study group:

U. Solzbach, H. Friedrich, C. van Uden, K. Meyer, H. Hebart, T. Tremmel, M. Bommer, A. Busch, A. Schmidt, S. Polk, P. La Rosée, M. Geiser, S. Mertins, C. Schuhmacher, M. Götz, A. A. von Ameln-Mayerhofer, F. Khaleqi, K. Winter, M. Ritter, F. Wagner, S. Reinecke, Sr. Karin Johanna Haase, S. Horn, S. Lindner, B. Reistle, M. Kollum, P. Buchal, M. Schmid, S. Müller, S. Sorichter, R. Grüninger, Y. Wuwer, H. Niese, T. Iber, D. Hohenstein, U. Witten-Stephan, D. Wirth, M. Steib-Bauert, K. Kaier, and M. Sehlbrede

References

  • 1.DART 2020—fighting antibiotic resistance for the good of both humans and animals [Internet]. Germany: Federal Ministry of Health; 2015. p. 32. https://www.bmel.de/SharedDocs/Downloads/EN/Publications/DART2020.pdf;jsessionid=44993CFA6501895070914CE60CDCC3D2.live921?__blob=publicationFile&v=3.
  • 2.WHO. Antibiotic resistance [Internet]. 2020. https://www.who.int/news-room/fact-sheets/detail/antibiotic-resistance. Accessed 29 Apr 2021.
  • 3.Souli M, Ruffin F, Choi S-H, Park LP, Gao S, Lent NC, et al. Changing characteristics of Staphylococcus aureus bacteremia: results from a 21-year, prospective longitudinal study. Clin Infect Dis. 2019;69:1868–1877. doi: 10.1093/cid/ciz112. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Rieg S, Hitzenbichler F, Hagel S, Suarez I, Kron F, Salzberger B, et al. Infectious disease services: a survey from four university hospitals in Germany. Infect Germany. 2019;47:27–33. doi: 10.1007/s15010-018-1191-8. [DOI] [PubMed] [Google Scholar]
  • 5.Marquet K, Liesenborgs A, Bergs J, Vleugels A, Claes N. Incidence and outcome of inappropriate in-hospital empiric antibiotics for severe infection: a systematic review and meta-analysis. Crit Care. 2015;19:1–12. doi: 10.1186/s13054-015-0795-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Davey P, Marwick C. Appropriate vs inappropriate antimicrobial therapy. Clin Microbiol Infect. 2008;14:15–21. doi: 10.1111/j.1469-0691.2008.01959.x. [DOI] [PubMed] [Google Scholar]
  • 7.Aghdassi SJS, Schwab F, Hansen S, Diaz LAP, Behnke M, Gastmeier P, et al. The quality of antimicrobial prescribing in acute care hospitals: results derived from a national point prevalence survey, Germany, 2016. Eurosurveillance. 2019;24:1900281. doi: 10.2807/1560-7917.ES.2019.24.46.1900281. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Stenehjem E, Hersh AL, Buckel WR, Jones P, Sheng X, Evans RS, et al. Impact of implementing antibiotic stewardship programs in 15 small hospitals: a cluster-randomized intervention. Clin Infect Dis. 2018;67:525–532. doi: 10.1093/cid/ciy155. [DOI] [PubMed] [Google Scholar]
  • 9.Schuts EC, Hulscher MEJL, Mouton JW, Verduin CM, Stuart JWTC, Overdiek HWPM, et al. Current evidence on hospital antimicrobial stewardship objectives: a systematic review and meta-analysis. Lancet Infect Dis. 2016;16:847–856. doi: 10.1016/S1473-3099(16)00065-7. [DOI] [PubMed] [Google Scholar]
  • 10.Fishman N. Policy Statement on Antimicrobial Stewardship by the Society for Healthcare Epidemiology of America (SHEA), the Infectious Diseases Society of America (IDSA), and the Pediatric Infectious Diseases Society (PIDS) Infect Control Hosp Epidemiol. 2012;33:322–327. doi: 10.1086/665010. [DOI] [PubMed] [Google Scholar]
  • 11.Karanika S, Paudel S, Grigoras C, Kalbasi A, Mylonakis E. Systematic review and meta-analysis of clinical and economic outcomes from the implementation of hospital-based antimicrobial stewardship programs. Antimicrob Agents Chemother. 2016;60:4840–4852. doi: 10.1128/AAC.00825-16. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Nathwani D, Varghese D, Stephens J, Ansari W, Martin S, Charbonneau C. Value of hospital antimicrobial stewardship programs [ASPs]: a systematic review. Antimicrobial Resist Infect Control Springer. 2019;8:1–13. doi: 10.1186/s13756-018-0426-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Bork JT, Claeys KC, Heil EL, Banoub M, Leekha S, Sorkin JD, et al. A propensity score matched study of the positive impact of infectious diseases consultation on antimicrobial appropriateness in hospitalized patients with antimicrobial stewardship oversight. Antimicrob Agents Chemother. 2020;64:e00307–20. [DOI] [PMC free article] [PubMed]
  • 14.Arensman K, Dela-Pena J, Miller JL, LaChance E, Beganovic M, Anderson M, et al. Impact of mandatory infectious diseases consultation and real-time antimicrobial stewardship pharmacist intervention on Staphylococcus aureus bacteremia bundle adherence. open forum infectious diseases [Internet]. 2020. p. 7. 10.1093/ofid/ofaa184 [DOI] [PMC free article] [PubMed]
  • 15.Bassetti M, Peghin M, Trecarichi EM, Carnelutti A, Righi E, Giacomo PD, et al. Characteristics of Staphylococcus aureus Bacteraemia and predictors of early and late mortality. PLoS ONE. 2017;2017:11. doi: 10.1371/journal.pone.0170236. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Lahey T, Shah R, Gittzus J, Schwartzman J, Kirkland K. Infectious diseases consultation lowers mortality from Staphylococcus aureus bacteremia. Medicine. 2009;88:263–267. doi: 10.1097/MD.0b013e3181b8fccb. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Vogel M, Schmitz RPH, Hagel S, Pletz MW, Gagelmann N, Scherag A, et al. Infectious disease consultation for Staphylococcus aureus bacteremia—a systematic review and meta-analysis. J Infect. 2016;72:19–28. doi: 10.1016/j.jinf.2015.09.037. [DOI] [PubMed] [Google Scholar]
  • 18.Raineri E, Pan A, Mondello P, Acquarolo A, Candiani A, Crema L. Role of the infectious diseases specialist consultant on the appropriateness of antimicrobial therapy prescription in an intensive care unit. Am J Infect Control. 2008;36:283–290. doi: 10.1016/j.ajic.2007.06.009. [DOI] [PubMed] [Google Scholar]
  • 19.Mejia-Chew C, O’Halloran JA, Olsen MA, Stwalley D, Kronen R, Lin C, et al. Effect of infectious disease consultation on mortality and treatment of patients with candida bloodstream infections: a retrospective, cohort study. Lancet Infect Dis. 2019;19:1336–1344. doi: 10.1016/S1473-3099(19)30405-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Rieg S, Küpper MF. Infectious diseases consultations can make the difference: a brief review and a plea for more infectious diseases specialists in Germany. Infect Germany. 2016;44:159–166. doi: 10.1007/s15010-016-0883-1. [DOI] [PubMed] [Google Scholar]
  • 21.Kern WV, Fätkenheuer G, Tacconelli E, Ullmann A. Übersichtsartikel: Klinische Infektiologie in Deutschland und Europa [Review article: Clinical Infectiology in Germany and Europe] Z Evid Fortbild Qual Gesundhwes. 2015;109:493–499. doi: 10.1016/j.zefq.2015.09.015. [DOI] [PubMed] [Google Scholar]
  • 22.McKendrick MW. The European Union of Medical Specialties core training curriculum in infectious diseases: overview of national systems and distribution of specialists. Clin Microbiol Infect. 2005;2005:5. doi: 10.1111/j.1469-0691.2005.01087.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Hussaini SMQ. Dearth of infectious diseases physicians as the USA faces a global pandemic. Lancet Infect Dis. 2020;20:648–649. doi: 10.1016/S1473-3099(20)30377-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Bundesärztekammer [German Medical Association]. 124. Deutscher Ärztetag (Online) [Internet]. 2021. https://www.bundesaerztekammer.de/fileadmin/user_upload/downloads/pdf-Ordner/124.DAET/Beschlussprotokoll_124_Daet_2021_Stand-06.05.2021_mit_numerischen_Lesezeichen.pdf. Accessed 7 Jul 2021.
  • 25.Perozziello A, Routelous C, Charani E, Truel A, Birgand G, Yazdanpanah Y, et al. Experiences and perspectives of implementing antimicrobial stewardship in five French hospitals: a qualitative study. Int J Antimicrob Agents. 2018;51:829–835. doi: 10.1016/j.ijantimicag.2018.01.002. [DOI] [PubMed] [Google Scholar]
  • 26.Alghamdi S, Atef-Shebl N, Aslanpour Z, Berrou I. Barriers to implementing antimicrobial stewardship programmes in three Saudi hospitals: evidence from a qualitative study. J Glob Antimicrobial Resist. 2019;18:284–290. doi: 10.1016/j.jgar.2019.01.031. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Warreman EB, Lambregts MMC, Wouters RHP, Visser LG, Staats H, van Dijk E, et al. Determinants of in-hospital antibiotic prescription behaviour: a systematic review and formation of a comprehensive framework. Clin Microbiol Infect. 2019;25:538–545. doi: 10.1016/j.cmi.2018.09.006. [DOI] [PubMed] [Google Scholar]
  • 28.Charani E, Edwards R, Sevdalis N, Alexandrou B, Sibley E, Mullett D, et al. Behavior change strategies to influence antimicrobial prescribing in acute care: a systematic review. Clin Infect Dis. 2011;53:651–662. doi: 10.1093/cid/cir445. [DOI] [PubMed] [Google Scholar]
  • 29.Haute Autorité de santé. Fiche descriptive 2018. Thème Infections Associées aux Soins (IAS) [Descriptive sheet 2018. Healthcare-associated infections (HAI) theme] [Internet]. 2018. https://www.has-sante.fr/upload/docs/application/pdf/2016-04/2016_has_fiche_descriptive_icatb_2.pdf. Accessed 10 Nov 2021.
  • 30.Donisi V, Sibani M, Carrara E, Del Piccolo L, Rimondini M, Mazzaferri F, et al. Emotional, cognitive and social factors of antimicrobial prescribing: can antimicrobial stewardship intervention be effective without addressing psycho-social factors? J Antimicrob Chemother. 2019;74:2844–2847. doi: 10.1093/jac/dkz308. [DOI] [PubMed] [Google Scholar]
  • 31.Arbeitsgemeinschaft der Wissenschaftlichen Medizinischen Fachgesellschaften (AWMF)- Ständige Kommission Leitlinien. [Working Group of Scientific Medical Societies (AWMF) - Standing Commission Guidelines]. Strategien zur Sicherung rationaler Antibiotika-Anwendung im Krankenhaus [Strategies to ensure the rational use of antibiotics in the hospital] [Internet]. Ständige Kommission „Leitlinien“ der Arbeitsgemeinschaft der Wissenschaftlichen Medizinischen Fachgesellschaften (AWMF); 2018. https://www.awmf.org/fileadmin/user_upload/Leitlinien/AWMF-Regelwerk/AWMF-Regelwerk.pdf. Accessed 10 Nov 2021.
  • 32.AOK Baden-Württemberg, editor. #AgendaGesundheit Unternehmensbericht [#AgendaHealth Company Report] [Internet]. AOK. 2020. https://aok-bw-presse.de/fileadmin/mediathek/dokumente/aok-bw_unternehmensbericht_2020_01.pdf. Accessed 6 Aug 2021.
  • 33.Marshall MN. Sampling for qualitative research. Fam Pract. 1996;13:522–526. doi: 10.1093/fampra/13.6.522. [DOI] [PubMed] [Google Scholar]
  • 34.Faul F, Erdfelder E, Lang A-G, Buchner A. G* Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav Res Methods. 2007;39:175–191. doi: 10.3758/BF03193146. [DOI] [PubMed] [Google Scholar]
  • 35.Faul F, Erdfelder E, Buchner A, Lang A-G. Statistical power analyses using G* Power 3.1: tests for correlation and regression analyses. Behavior Res Methods. 2009;41:1149–1160. doi: 10.3758/BRM.41.4.1149. [DOI] [PubMed] [Google Scholar]
  • 36.López-Cortés LE, del Toro MD, Gálvez-Acebal J, Bereciartua-Bastarrica E, Fariñas MC, Sanz-Franco M, et al. Impact of an evidence-based bundle intervention in the quality-of-care management and outcome of Staphylococcus aureus bacteremia. Clin Infect Dis. 2013;57:1225–1233. doi: 10.1093/cid/cit499. [DOI] [PubMed] [Google Scholar]
  • 37.Arbeitsgemeinschaft der Wissenschaftlichen Medizinischen Fachgesellschaften (AWMF) [Association of the Scientific Medical Societies] - Deutsche Gesellschaft für Pneumologie und Beatmungsmedizin e.V. (DGP) [German Society for Pneumology and Respiratory Medicine e.V.], editor. S3 Leitlinie: Behandlung von erwachsenen Patienten mit ambulant erworbener Pneumonie [S3 Guideline: Treatment of adult patients with community-acquired pneumonia.] [Internet]. 2021. https://www.awmf.org/uploads/tx_szleitlinien/020-020l_S3_Behandlung-von-erwachsenen-Patienten-mit-ambulant-erworbener-Pneumonie__2021-05.pdf. Accessed 4 Aug 2021.
  • 38.Goto M, Schweizer ML, Vaughan-Sarrazin MS, Perencevich EN, Livorsi DJ, Diekema DJ, et al. Association of evidence-based care processes with mortality in Staphylococcus aureus bacteremia at Veterans Health Administration hospitals, 2003–2014. JAMA Intern Med. 2017;177:1489–1497. doi: 10.1001/jamainternmed.2017.3958. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Meehan TP, Fine MJ, Krumholz HM, Scinto JD, Galusha DH, Mockalis JT, et al. Quality of care, process, and outcomes in elderly patients with pneumonia. JAMA. 1997;278:2080–2084. doi: 10.1001/jama.1997.03550230056037. [DOI] [PubMed] [Google Scholar]
  • 40.Bordon J, Aliberti S, Duvvuri P, Wiemken T, Peyrani P, Natividad I, et al. Early administration of the first antimicrobials should be considered a marker of optimal care of patients with community-acquired pneumonia rather than a predictor of outcomes. Int J Infect Dis. 2013;17:e293–e298. doi: 10.1016/j.ijid.2012.09.021. [DOI] [PubMed] [Google Scholar]
  • 41.Frei CR, Attridge RT, Mortensen EM, Restrepo MI, Yu Y, Oramasionwu CU, et al. Guideline-concordant antibiotic use and survival among patients with community-acquired pneumonia admitted to the intensive care unit. Clin Ther. 2010;32:293–299. doi: 10.1016/j.clinthera.2010.02.006. [DOI] [PubMed] [Google Scholar]
  • 42.McCabe C, Kirchner C, Zhang H, Daley J, Fisman DN. Guideline-concordant therapy and reduced mortality and length of stay in adults with community-acquired pneumonia: playing by the rules. Arch Intern Med. 2009;169:1525–1531. doi: 10.1001/archinternmed.2009.259. [DOI] [PubMed] [Google Scholar]
  • 43.Gleason PP, Meehan TP, Fine JM, Galusha DH, Fine MJ. Associations between initial antimicrobial therapy and medical outcomes for hospitalized elderly patients with pneumonia. Arch Intern Med. 1999;159:2562–2572. doi: 10.1001/archinte.159.21.2562. [DOI] [PubMed] [Google Scholar]
  • 44.Helfferich C. Die Qualität qualitativer Daten [The quality of qualitative data] Berlin: Springer; 2011. [Google Scholar]
  • 45.Newcomer KE, Hatry HP, Wholey JS. Handbook of practical program evaluation. John Wiley & Sons. 2015. p. 492.
  • 46.McLafferty I. Focus group interviews as a data collecting strategy. J Adv Nurs. 2004;48:187–194. doi: 10.1111/j.1365-2648.2004.03186.x. [DOI] [PubMed] [Google Scholar]
  • 47.Huang FL. Using cluster bootstrapping to analyze nested data with a few clusters. Educ Psychol Measur. 2018;78:297–318. doi: 10.1177/0013164416678980. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48.Guo S, Fraser MW. Propensity score analysis: statistical methods and applications. Tousand Oaks: SAGE publications; 2014. [Google Scholar]
  • 49.Mayring P. Qualitative Inhaltsanalyse—Grundlagen und Techniken [Qualitative Content Analysis—Basics and Techniques]. 10th ed. Weinheim: Beltz; 2008.

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Data Availability Statement

Data sharing is not applicable to this article as no datasets were yet generated or analyzed during the current study. The data files, statistical details and codes will be available from the corresponding authors. However, unrestricted, unreasonable data-sharing is not planned.


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