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Antimicrobial Stewardship

Antimicrobial Stewarship is the coordinated program designed to improve and measure the appropriate use of antimicorbials to proote patient safety and reduce microbial resistance.
This approach involves selecting the optimal antimicrobial drug regimen, dose, duration of therapy, and route of administration.
Antimicrobial stewarship programs aim to achive optimal clinical outcomes related to antimicrobial use, minimize toxicity and other adverse events, and reduce the selective pressures that drive the emergence of antimicrobial-resistant strains.

Most cited protocols related to «Antimicrobial Stewardship»

National Healthcare Safety Network (NHSN) Pathogens Report

The CLABSIs,⁷ CAUTIs,⁸ select VAEs,⁹ and SSIs¹⁰ that occurred between 2015–2017 and had been reported to the NHSN’s Patient Safety Component as of July 1, 2018, were included in this report. These HAIs were reported by acute-care hospitals, critical access hospitals, LTACHs, and IRFs from all US states and territories. Unless otherwise noted, CLABSI data included events classified as mucosal barrier injury laboratory-confirmed bloodstream infection (MBI-LCBI). VAE data were limited to events classified as possible ventilator-associated pneumonia (PVAP) because this is the only subtype of VAE for which a pathogen can be reported. Asymptomatic bacteremic urinary tract infections, CLABSIs reported from IRFs, and outpatient SSIs were excluded.
The NHSN protocols provide guidance for attributing device-associated (DA) HAIs (ie, CLABSIs, CAUTIs, and PVAPs) to a CDC-defined location type, and SSIs to a CDC operative procedure code. Due to known differences in pathogens and resistance patterns between adult and pediatric populations,^{11 ,12 (link)} this report was limited to DA HAIs attributed to adult location types, and to SSIs that occurred in patients ≥18 years old at the time of surgery. Comparable data from pediatric locations and patients are described in a companion report.^{13 (link)}Unless otherwise noted, DA HAIs were stratified into 5 mutually exclusive location categories: hospital wards (inclusive of step-down, mixed acuity, and specialty care areas), hospital intensive care units (ICUs), hospital oncology units (ie, oncology ICUs and wards), LTACHs (ie, LTACH ICUs and wards), and IRFs (ie, freestanding IRFs and CMS-certified IRF units located within a hospital). SSI data were stratified into mutually exclusive surgical categories based on the operative procedure code. Pathogen distributions were also analyzed separately for each operative procedure code and are available in the online supplement.¹⁴Up to 3 pathogens and their antimicrobial susceptibility testing (AST) results can be reported to the NHSN for each HAI. The AST results for the drugs included in this analysis were reported using the interpretive categories of “susceptible” (S), “intermediate” (I), “resistant” (R), or “not tested.” Instead of “intermediate,” cefepime had the category interpretation of “intermediate/susceptible-dose dependent” (I/S-DD), which was treated as I for this analysis. Laboratories are expected to follow current guidelines from the Clinical and Laboratory Standards Institute (CLSI) for AST.¹⁵ Naming conventions for pathogens generally adhered to the Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) Preferred Term.¹⁶ In some cases, pathogens were grouped by genus or clinically recognized group (eg, viridans group streptococci) (Appendices A2–A4 online). Results for Klebsiella spp were limited to K. pneumoniae and K. oxytoca; K. aerogenes was considered part of Enterobacter spp due to the timing of the NHSN’s adoption of its name change.^{17 (link)}Staphylococcus aureus was defined as methicillin-resistant (MRSA) if the isolate was reported as R to oxacillin, cefoxitin, or methicillin. Enterococcus spp isolates were defined as vancomycin-resistant (VRE) if they tested R to vancomycin. VRE data were analyzed for all HAIs except PVAP because Enterococcus spp are excluded from the NHSN’s PVAP surveillance definition under most scenarios. Carbapenem-resistant Enterobacteriaceae (CRE) were defined as Klebsiella spp, Escherichia coli, or Enterobacter spp that tested R to imipenem, meropenem, doripenem, or ertapenem. All other pathogen-antimicrobial combinations (phenotypes) were described using a metric for nonsusceptibility, which included pathogens that tested I or R to the applicable drugs. To be defined as nonsusceptible to extended-spectrum cephalosporins (ESCs), pathogens must have tested I or R to either ceftazidime or cefepime (Pseudomonas aeruginosa) or to ceftazidime, cefepime, ceftriaxone, or cefotaxime (Klebsiella spp and E. coli). For Enterobacter spp, evaluation of nonsusceptibility to ESCs was limited to cefepime due to Enterobacter’s inducible resistance to other ESCs. Fluoroquinolone nonsusceptibility was defined as a result of I or R to either ciprofloxacin or levofloxacin (P. aeruginosa) or to ciprofloxacin, levofloxacin, or moxifloxacin (E. coli). Carbapenem nonsusceptibility in P. aeruginosa and Acinetobacter spp was defined as a result of I or R to imipenem, meropenem, or doripenem. Nonsusceptibility to aminoglycosides was defined as a result of I or R to gentamicin, amikacin, or tobramycin. Finally, multi-drug-resistance (MDR) was approximated by adapting previously established definitions^{18 (link)} that require nonsusceptibility to at least 1 agent within 3 different drug classes. For Enterobacteriaceae and P. aeruginosa, 5 classes were considered in the criteria: ESCs (or cefepime for Enterobacter spp), fluoroquinolones, aminoglycosides, carbapenems, and piperacillin (PIP) or piperacillin/tazobactam (PIPTAZ). A sixth class, ampicillin/sulbactam, was included in the criteria for Acinetobacter spp.
Data were analyzed using SAS version 9.4 software (SAS Institute, Cary, NC). For all HAIs and pathogens, absolute frequencies and distributions were calculated by HAI, location, and surgical category. The 15 most commonly reported pathogens were identified, and their frequencies and ranks within each stratum were calculated. A pooled mean percentage nonsusceptible (%NS) was calculated for each phenotype as the sum of nonsusceptible (or resistant) pathogens, divided by the sum of pathogens tested for susceptibility, and multiplied by 100. Percentage NS was not calculated for any phenotype for which <20 pathogens were tested. Differences in the %NS across location types or surgical categories were assessed for statistical significance using a mid-P exact test, and P < .05 was considered statistically significant. The percentage of pathogens with reported susceptibility results (referred to as “percentage tested”) is defined elsewhere^{3 (link)} and was calculated for each bacterial phenotype, as well as for select Candida spp. Pathogens and susceptibility data for CLABSIs categorized as MBI-LCBI were analyzed separately and are presented in the online supplement.¹⁴“Selective reporting” occurs when laboratories suppress AST results as part of antimicrobial stewardship efforts. This practice could contribute to a higher number of pathogens reported to the NHSN as “not tested” to certain drugs. To assess the impact of selective reporting on the national %NS, we applied an alternate calculation for CRE and ESC nonsusceptibility. If a pathogen was reported as “not tested” to carbapenems, susceptibility was inferred as S if the pathogen tested susceptible to at least 2 of the following: ampicillin, ampicillin/sulbactam, amoxicillin/clavulanic acid, PIPTAZ, cefazolin, cefoxitin, or cefotetan. If a pathogen was reported as “not tested” to ESCs, susceptibility was inferred as S if the pathogen tested susceptible to at least 2 of the following: ampicillin, aztreonam, or cefazolin. Therefore, the number of tested isolates increases under the alternate calculation. Percentage NS was calculated using both the traditional (ie, strictly as reported) and alternate approaches.
Statistical analyses were not performed to test for temporal changes in the %NS; thus, this report does not convey any conclusions regarding changes in resistance over time. Due to differences in the stratification levels, inclusion criteria, and patient populations, the %NS values in this report should not be compared to those published in previous iterations of this report.

Weiner-Lastinger L.M., Abner S., Edwards J.R., Kallen A.J., Karlsson M., Magill S.S., Pollock D., See I., Soe M.M., Walters M.S, & Dudeck M.A. (2019). Antimicrobial-resistant pathogens associated with adult healthcare-associated infections: Summary of data reported to the National Healthcare Safety Network, 2015–2017. Infection control and hospital epidemiology, 41(1), 1-18.

Publication 2019

Acinetobacter Adult Amikacin Aminoglycosides Amox clav Ampicillin ampicillin-sulbactam Antimicrobial Stewardship Asymptomatic Infections Aztreonam Bacteremia Bacteria Blood Circulation Candida Carbapenem-Resistant Enterobacteriaceae Carbapenems Cefazolin Cefepime Cefotaxime Cefotetan Cefoxitin Ceftazidime Ceftriaxone Cephalosporins Ciprofloxacin Clinical Laboratory Services Conferences Dietary Supplements Doripenem Enterobacter Enterobacteriaceae Enterococcus Ertapenem Escherichia coli Fluoroquinolones Gentamicin Imipenem Injuries Klebsiella Klebsiella oxytoca Klebsiella pneumoniae Laboratory Infection Lanugo Levofloxacin Medical Devices Meropenem Methicillin Methicillin-Resistant Microbicides Moxifloxacin Mucous Membrane Multi-Drug Resistance Neoplasms Operative Surgical Procedures Outpatients Oxacillin pathogenesis Patients Patient Safety Pets Pharmaceutical Preparations Phenotype Piperacillin Piperacillin-Tazobactam Combination Product Pneumonia, Ventilator-Associated polyvinylacetate phthalate polymer Population Group Pseudomonas aeruginosa Sepsis Staphylococcus aureus Infection Streptococcus viridans Substance Abuse Detection Susceptibility, Disease Tobramycin Urinary Tract Vancomycin Vancomycin Resistance Wound Infection

CCDS for Appropriate C. difficile Testing

At a 619-bed tertiary-care hospital, we performed a quasi-experimental retrospective cohort study analyzing rates of inpatient C. difficile test ordering and National Healthcare Safety Network (NHSN)-defined hospital-onset (ie, occurring on hospital day >3) C. difficile infection (HO-CDI) laboratory-identified (LabID) events⁶ before and after the introduction of a CCDS tool with nurse and provider education along with a financial incentive for graduate medical education (GME) trainees. The CCDS tool was developed after internal auditing by antimicrobial stewardship identified that 10 of 15 HO-CDI events (67%) during a 1-month period potentially lacked an indication for testing.
The 2-part CCDS tool first displayed a duplicate-order information screen listing C. difficile test results within 28 days. Second, a series of questions designed to guide appropriate testing was presented to the ordering provider. The algorithm (Figure 1) was designed to highlight duplicate C. difficile tests that may be low yield⁷ and practice guidelines recommending testing only of symptomatic patients, while considering risk factors including antibiotic use, intra-abdominal surgery, and advanced age.⁸ A step-wise algorithm was chosen based on limitations of screen size and ease of reading (see Supplementary Material for software demonstration). A test could be ordered regardless of provider responses. According to the existing laboratory protocol, solid stool specimens were rejected for NAAT testing.FIGURE 1

Two-part clinical decision support algorithm. NOTE. NAAT, nucleic acid amplification test for Clostridium difficile; C. diff, C. difficile; PPV, positive predictive value; WBC, white blood cell count.

The CCDS tool was preceded by a series of educational efforts presented to all providers and nurses, including email, flyers, and a brief video (see Supplementary Material). These efforts explained the rationale for the CCDS, provided guidelines on appropriate C. difficile specimens, and demonstrated the tool. A representative body of GME trainees performed in-person training with house staff in each inpatient department. Education occurred over a 2-week period prior to activation of the CCDS tool with a reminder message on the day of implementation. In addition, GME trainees were provided a 0.8% bonus (jointly funded by the UVA Office of Graduate Medical Education and UVA Health System) at the end of the academic year (June 2017) if testing by GME providers fell by ≥25% compared to the preintervention period.
The CCDS tool was developed in response to a broad, multidisciplinary commitment to HO-CDI reduction endorsed by hospital leadership. Monitoring was conducted daily using an electronic C. difficile dashboard reflecting all daily tests, new positive tests, duplicate tests, and test attempts “prevented” by the CCDS, provided to hospital staff and administration with unit and service attributions. The antimicrobial stewardship team performed chart reviews of patients with positive tests, evaluating appropriate testing and other opportunities to reduce HO-CDI. In addition to CCDS implementation, peroxyacetic acid/hydrogen peroxide-based cleaner was adopted hospital-wide in May 2017 to replace quaternary ammonium and bleach for daily and terminal hospital room disinfection. In addition, a policy change on April 2017 restricted antibiotics for neurosurgical drain prophylaxis. No other major new C. difficile-related infection control interventions were implemented during the study period.
An 18-month preintervention control period (June 2014 to November 2016) was compared to a 10-month postintervention period (December 2016 to September 2017) following CCDS implementation on December 5, 2016. In this analysis, HO-CDI and test count data were normalized to monthly patient days. An order was considered prevented if providers initiated but did not complete a C. difficile NAAT order. Canceled test orders and samples not submitted to the laboratory were excluded from the analysis.
Testing rates and proportions of positive tests were compared between the intervention groups using independent sample t tests and the χ² test, respectively. Due to fewer total HO-CDI events, a quasi-Poisson model was used to assess changes in HO-CDI counts between pre- and post intervention periods, using patient days as an offset. Analyses were performed using statistical R version 3.4.1 software (R Core Team, Vienna, Austria). The University of Virginia Internal Review Board approved this study (no. 20082).

Madden G.R., German Mesner I., Cox H.L., Mathers A.J., Lyman J.A., Sifri C.D, & Enfield K.B. (2018). Reduced Clostridium difficile Tests and Laboratory-Identified Events With a Computerized Clinical Decision Support Tool and Financial Incentive. Infection Control and Hospital Epidemiology, 39(6), 737-740.

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Publication 2018

Abdominal Cavity Ammonium Antibiotics Antimicrobial Stewardship Clinical Decision Support Clostridium difficile Disinfection Education, Medical, Graduate Feces House Staff Human Body Infection Infection Control Inpatient Leukocyte Count Nucleic Acid Amplification Tests Nurses Operative Surgical Procedures Patients Peracetic Acid Peroxide, Hydrogen Personnel, Hospital Safety

Development and Validation of CSAT Instrument

Data from two different participant samples were used for the development and testing of the CSAT instrument. First, a pilot sample (N = 120) was used for the initial development of the instrument, which included item selection, preliminary psychometrics testing, and usability testing. Second, a subsequent set of early CSAT users administered the final 35-item version of the CSAT. These data were used for more in-depth psychometric testing, including subdomain analyses and structural invariance testing (see below).
The first CSAT pilot sample of participants was selected from different clinical work environments as well as from different healthcare professions. Recruitment efforts used a snowball sampling approach and included identifying and contacting stakeholders that could potentially benefit from using the tool, as well as promoting the CSAT at local and national dissemination and implementation conferences. Respondents had the option to forward the link to peers or nominate individuals to complete the CSAT. To incentivize participation, all respondents were offered an optional tailored sustainability results report and the opportunity to enter a drawing for one of five $50 gift cards. The final pilot sample size was 120 participants (Table 1).
Table 1

CSAT development participant demographic characteristics

	Pilot (N=120)		Early users (N=166)
Characteristic	N	%	N	%
Profession
Nurse	18	16	42	27
Pharmacist	37	33	11	7
Physician	29	26	34	22
Admin/research	13	12	29	19
Ancillary	7	6	18	11
Other	8	7	22	14
Position/role
Bedside provider	44	40	65	42
Unit level management	7	6	–	–
System leadership	6	5	60	38
Program leader	27	24	4	3
Other	27	24	27	17
Environment
Academic medical center	67	60	65	42
Private practice	6	5	16	10
Community hospital	21	19	19	12
Community health center	6	5	48	31
Other	12	11	8	5
Setting
Inpatient	56	55	35	25
Outpatient	26	26	79	56
Both	19	19	27	19
Patient
Pediatric	54	53	49	32
Adult	47	47	94	63
Both	–	–	6	4

Note: Frequencies add up to less than sample totals because of missing responses

The second set of early user program participants (N = 166) came from two separate research studies. The first study recruited clinical staff working on the cancer control continuum in Missouri. This included primary care environments, screening programs, and cancer care centers that are focused on the diagnosis and treatment of those with cancer. The second study recruited participants in antimicrobial stewardship teams working to implement surgical prescribing guidelines. The contact at each site forwarded the CSAT to stakeholders they identified to participate. The early user sample size was 166 participants who represented a mix of professions and roles. The early users differed from the pilot sample with more early users representing adult care and outpatient settings (Table 1).

Malone S., Prewitt K., Hackett R., Lin J.C., McKay V., Walsh-Bailey C, & Luke D.A. (2021). The Clinical Sustainability Assessment Tool: measuring organizational capacity to promote sustainability in healthcare. Implementation Science Communications, 2, 77.

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Publication 2021

Adult Antimicrobial Stewardship Conferences Diagnosis Health Personnel Malignant Neoplasms Operative Surgical Procedures Outpatients Primary Health Care Wellness Programs

COVID-19 ICU VAP Surveillance Protocol

This study was performed in the liver/general adult ICU in Addenbrooke’s Hospital, Cambridge, UK, and also included COVID-19 patients managed in the neurotrauma and dedicated COVID-19 ICUs of the hospital. Patients were reviewed at least twice daily by consultant intensive care physicians with investigation for VAP ordered by this clinician, and discussed at a daily microbiology-intensive care multi-disciplinary team/antimicrobial stewardship meeting. We had a regularly audited ventilator bundle in place, which consisted of sub-glottic suction endotracheal tubes, mandated twice daily oral hygiene with fluoride toothpaste, daily sedation holds and head of bed elevation. One to one nursing to patient ratios were maintained throughout the first wave of COVID-19, although at times this included nurses with limited critical care training as normal ICU capacity was exceded. Sessional use of personal protective equipment (full-length fluid impermeable gowns, FFP3 mask, gloves and hat) with apron and second glove change between patients was maintained from March 15th to July 31st. Patients ventilated for at least 48 h, from March 15th (date of our first COVID-19 admission) to August 30th were retrospectively reviewed for presence of VAP. VAP was defined using a modification of the European Centre for Disease Control definitions [17 (link)] for quantitative BAL culture (termed PN1) or quantitative endotracheal aspirate (ETA) or sputum culture (termed PN2) definitions of pneumonia (see Fig. 1). The modifications were to use polymerase chain reaction (PCR) positivity by TAC for BAL fluid (details below) and to use a threshold of ≥ 10⁵ Colony Forming Units (CFU)/ml for endotracheal aspirate in keeping with UK standards [18 ]. Low lung pathogenicity organisms (Enterococcus spp., Candida albicans, non-pneumococcal Streptococci and coagulase negative Staphylococci) were reported but not considered a component of VAP [19 (link)]. Herpesviridae (Herpes simplex, cytomegalovirus and Epstein-Barr virus) were reported but were considered to be reactivations and not considered a component of VAP [20 ].Fig. 1

Criteria used for the diagnosis of VAP.

Adapted from the European Centre for Disease Control definitions to meet local thresholds for quantitative culture of endotracheal aspirate and for the inclusion of molecular detection of pathogens. Ct-cycles to threshold by quantitative PCR

We also looked for evidence of invasive pulmonary aspergillosis (IPA), as there are now several case reports of this developing in patients with COVID-19 [11 (link)] and recent reports of its frequency in non-COVID VAP [21 (link)]. IPA was defined using the criteria set out in the report describing influenza associated pulmonary aspergillosis [22 (link)] modified to include diagnosis by PCR. The criteria were clinical evidence of pulmonary infection, radiological evidence of pulmonary infection and detection of aspergillus by BAL galactomannan, PCR positivity or culture positivity.

Maes M., Higginson E., Pereira-Dias J., Curran M.D., Parmar S., Khokhar F., Cuchet-Lourenço D., Lux J., Sharma-Hajela S., Ravenhill B., Hamed I., Heales L., Mahroof R., Solderholm A., Forrest S., Sridhar S., Brown N.M., Baker S., Navapurkar V., Dougan G., Bartholdson Scott J, & Conway Morris A. (2021). Ventilator-associated pneumonia in critically ill patients with COVID-19. Critical Care, 25, 25.

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Publication 2021

Adult Antimicrobial Stewardship Aspergillus Candida albicans Coagulase Consultant COVID 19 Critical Care Cytomegalovirus Diagnosis Enterococcus Epstein-Barr Virus Europeans Fluorides galactomannan Glottis Head Herpes Simplex Herpesviridae Infection Influenza Intensive Care Invasive Pulmonary Aspergillosis Liver Lung Nurses pathogenesis Pathogenicity Patients Physicians Pneumonia Polymerase Chain Reaction Pulmonary Aspergillosis Sedatives Sputum Staphylococcus Streptococcus Streptococcus pneumoniae Suction Drainage Toothpaste X-Rays, Diagnostic

Comprehensive Bibliometric Analysis of Antimicrobial Stewardship

The advanced search function was used in Scopus to allow for developing comprehensive search queries that include different Boolean operators. Before entering the search query, the authors did a literature review on articles about AMS to have a clear idea about all possible keywords used in AMS literature [32 (link)–39 (link)]. No previous bibliometric studies on AMS were previously published. Therefore, the search query was uniquely developed for the current study. The search query used in the current study utilized the keywords “antimicrobial stewardship” or “antibiotic stewardship (ABS)” in the titles or abstracts. This approach will retrieve the bulk of literature on AMS. However, there are certain publications in which the keywords AMS or ABS were not mentioned explicitly and therefore a second search scenario was added to the query. For example, the term “restrict” or “restriction” if used with the terms “antimicrobial” or “antibiotic” will retrieve certain documents on AMS. The full list of terms used in the second scenario included: preauthorization or pre-authorization or audit or feedback or stream-lining or streamlining or discontinuation or de-escalation or de-escalation or optimization or step-down or stepdown or education or program* or control or “quality assurance” or “decision support” or intervention or program or restrict*. The study period was from 1950 to 2019.

, & Sweileh W.M. (2021). Bibliometric analysis of peer-reviewed literature on antimicrobial stewardship from 1990 to 2019. Globalization and Health, 17, 1.

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Publication 2021

Antibiotics Antibiotic Stewardship Antimicrobial Stewardship Dietary Fiber Lanugo Microbicides

Most recents protocols related to «Antimicrobial Stewardship»

Multidisciplinary Approach to Monkeypox Care

Two distinct institutional task forces were established to respond to the
monkeypox epidemic. One consisted of infectious disease physicians with
expertise in epidemiology, antimicrobial stewardship, and HIV care. The
second larger task force included collaborators from urgent care and
emergency department leadership, healthcare system administration, pharmacy,
laboratory services, employee health, ambulatory clinic leadership,
information services, and corporate communications. Both groups met at least
weekly to develop and implement the care model. Barriers to implementing the
care model were identified and key stakeholders engaged to move the project
forward (see Figure
1).

Polk C., Sampson M., Fairman R.T., DeWitt M.E., Leonard M., Neelakanta A., Davidson L., Roshdy D., Branner C., McCurdy L., Ludden T., Tapp H, & Passaretti C. (2023). Evaluation of a health system’s implementation of a monkeypox care model under the RE-AIM framework. Therapeutic Advances in Infectious Disease, 10, 20499361231158463.

Publication 2023

Antimicrobial Stewardship Communicable Diseases Epidemics Physicians

Antimicrobial Stewardship Intervention in Vascular Surgery

Our antimicrobial stewardship intervention was based on the presence of at least two ID consultants in the Vascular Surgery ward twice a week (on Monday and Thursday afternoons) for about two hours per day and was continued for a 12-month period (Period B). It included two types of enabling elements:

Prospective audit and feedback. For every patient hospitalised for at least 48 h and receiving at least one antibiotic and/or antifungal drug for therapeutic purposes during the intervention activity, a revision of the antimicrobial prescription was conducted through an active discussion among the two ID consultants and a resident or a senior surgeon, resulting in a written consultation included in the medical record of the patient. Each evaluation considered the clinical picture, blood tests, radiological exams and microbiological results. Antimicrobials prescribed for surgical prophylaxis were not revised. Decisions on the prescriptions were coded as follows: Antimicrobials not recommended; Stop antimicrobials; De-escalate antimicrobials (by switching from parenteral to oral, narrowing the spectrum of activity or reducing the number of drugs administered); Change antimicrobials; Change dosage of antimicrobials; Continue antimicrobials; Start antimicrobials; Escalate antimicrobials (by switching from oral to parenteral, broadening the spectrum of activity, increasing the number of drugs administered).

Educational meetings about antimicrobial stewardship and infection control. During Period B, monthly meetings were organized by the ID consultants to increase knowledge about AMR, hospital-acquired infections and infection control. Particularly, the consultants showed both medical and non-medical healthcare workers staff (i.e., nurses and auxiliary staff), the basic principles of patient contact isolation, cohorting, hand hygiene and the use of personal protection equipment (PPE) in case of patients either colonized or infected with MDRO or Clostridioides difficile.

Vecchia M., Colaneri M., Sacchi P., Marvulli L.N., Salvaderi A., Lanza J., Boschini S., Ragni F., Marone P., Cutti S., Muzzi A., Marena C., Calvi M., Scudeller L., Marone E.M, & Bruno R. (2023). Implementation of an antimicrobial stewardship program in the Vascular Surgery ward of a university tertiary care hospital in Pavia, Northern Italy. BMC Infectious Diseases, 23, 138.

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Publication 2023

Action Spectrum Antibiotics Antifungal Agents Antimicrobial Stewardship Clostridioides Health Personnel Hematologic Tests Infection Control Infections, Hospital Microbicides Nurses Operative Surgical Procedures Parenteral Nutrition Patients Pharmaceutical Preparations Prescriptions Quarantine Surgeons Therapeutics Vascular Surgical Procedures X-Rays, Diagnostic

Interns' Prescribing Competency Improvement through Feedback

The study was conducted in southeast Queensland, Australia at a 929-bed teaching hospital (Hospital 1) and a 750-bed tertiary teaching hospital (Hospital 2). All interns in internal medicine terms were invited to participate. Both hospitals have established intern training programs, with a total 180 interns who rotate through various disciplines including internal medicine, surgery, emergency and one or two specialty areas. At both sites, like other hospitals in Australia, most inpatient prescribing occurs on the National Inpatient Medication Chart (NIMC). The interns had access to all online prescribing decision support tools through hospital networks and each medical team had the services of designated clinical pharmacists.

Table 1

Overview and timeline of study design for each Term

Phase	Timing in term	Feedback Mark 2 principles	Intervention component	Data collection
1	Start of each term	Orientation to standards of prescribing and purpose of feedback	Participants briefed on intervention and provided “Resident Prescribing Competency Evaluation and Feedback, Safety and Quality Development Tool” (Appendix 1)	n/a
1	Weeks 1 to 3	Activity 1	Interns engage in day-to-day prescribing	Prescribing outcomes (Appendix 2)
2	Weeks 4 to 5	Learner judges work	Individualised feedback session (including intern self-assessment) and generation of development plan for improving the prescribing of the learner informed by ward pharmacist assessment and prescribing outcomes audit with: • Site 1 – Clinical Pharmacologist/ Clinical Pharmacology Registrar • Site 2 – Senior clinical pharmacist (medical educator)	Intern self-assessment of prescribing practice (Not reported on in this manuscript.)
		Learner asks for specific feedback
		Others judge work
		Compare judgement
		Plan for improved work
3	Weeks 8 to 10	Activity 2	Interns engage in day-to-day prescribing	Prescribing outcomes (Appendix 2) Intern evaluation of engaging in intervention (questionnaire)
3		Evaluation of effects	Repeat of prescribing audit

In Phase 1 at the start of each of 5 sequential internal medicine terms, the interns were orientated to the purposes of feedback; that is, to generate safe and effective prescribing practices, and to the ‘standards of work’ using “Resident Prescribing Competency self and Peer Evaluation and Feedback, Safety and Quality Development Tool” which incorporates the key standards for safe prescribing (See Appendix 1). The prescribing competencies, based on National Safety and Quality Medication Safety Standards [29 ], included improving patient identification documentation, and appropriate prescription of venous thromboembolism prophylaxis, antimicrobial stewardship, medication history taking and reconciliation and ceasing medication appropriately. Also, interns were given the “Recommendations for Terminology, Abbreviations and Symbols used in the prescribing and Administration of Medicines” [30 ].
The interns then prescribed (Activity 1 in Table 1) for three weeks after which, to promote the initial component of self-regulation [21 ], they were invited to self-assess their prescribing practices by completing the Resident Prescribing Competency Evaluation and Feedback, Safety and Quality Development Tool. This tool uses a four-point Likert scale to assess 14 key prescribing competencies (see Appendix 1). During the same initial three weeks, the intern’s prescribing was observed and assessed by the ward-based pharmacist using the tool based on National inpatient medication Chart (Appendix 2). The details of the interns’ self-assessment and ward-based pharmacist assessments will not be presented here.
In Phase 2, during weeks 4 to 5 of the term, a feedback session was conducted with each intern informed by the (1) initial audit (see below), (2) their self-assessment and (3) the ward pharmacist assessment at a time convenient for both the intern and feedback facilitator.
During the feedback sessions, typically lasting 30 to 45 min, the facilitator and intern compared the audit findings presented as a summary of individuals prescribing performance along with specific examples using photocopies of medication charts. The interns’ self-assessment and the ward pharmacists’ assessment were also discussed and together a plan for improved work was generated. It was anticipated that this approach gives specific, individualised data on the ability to complete the various tasks of prescribing and engages the intern in a process of self-evaluation likely to enhance their ability to assess and then make decisions about the quality of their prescribing [31 ].
In Phase 3 - the evaluation of effects: the interns’ subsequent prescribing practice (Activity 2) was re-audited to determine the impact of the feedback on the number of errors per order and details of the prescribing error audit (see Appendix 2). The interns and ward pharmacists were asked to repeat their self-assessment during the last two weeks of the term.

Coombes I., Donovan P., Bullock B., Mitchell C, & Noble C. (2023). Can a novel constructivist theory-informed feedback intervention reduce prescribing errors ? A pre-post study. BMC Medical Education, 23, 150.

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Publication 2023

Antimicrobial Stewardship Brief Interventions Clinical Pharmacists Emergencies Inpatient Operative Surgical Procedures Patients Pharmaceutical Preparations Regulatory Sequences, Nucleic Acid Safety Self-Assessment TimeLine Training Programs Venous Thromboembolism

Surveillance of Toxigenic C. difficile Carriers

This study was conducted at a 1,048-bed university-affiliated hospital in Seoul, Republic of Korea. Since October 2019, the hospital has run an active surveillance program of toxigenic C. difficile carriers, targeted at older patients (≥ 65 years) within 48 h of their admission to the Division of Infectious Diseases, Department of Internal Medicine. As part of the pilot project, a program was implemented to strengthen the antimicrobial stewardship for the targeted population and promote the early detection of symptomatic patients with CDI. However, strict contact isolation, including private room use or cohorting, could not be implemented because of the lack of medical resources.

Lee K.B., Lee M., Suh J.W., Yang K.S., Chung Y., Kim J.Y., Kim S.B., Sohn J.W, & Yoon Y.K. (2023). Clinical prediction rule for identifying older patients with toxigenic clostridioides difficile at the time of hospital admission. BMC Geriatrics, 23, 127.

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Publication 2023

Antimicrobial Stewardship Communicable Diseases Early Diagnosis Patients Quarantine Target Population

Predictors of Toxigenic C. difficile Carriage

The following potential predictive variables for toxigenic C. difficile carriage or CDI were collected from a computerized hospital database for each patient: age, sex, comorbid conditions, history of procedures or operations over the past month, receipt of proton-pump inhibitors or immunosuppressants, exposure to a medical environment, antibiotic use for more than 3 days over the past month, diagnosis on admission, intensive care unit stay over the past month, and multidrug-resistant microorganisms isolated from clinical specimens during hospitalization. Diarrhea was defined as the passage of three or more loose or liquid stools per day. An asymptomatic carrier was defined as a person infected with C. difficile, detected by PCR, without diarrhea.
The study was approved by our hospital’s institutional review board [2022AN0356]. Since the clinical data were obtained through a routine hospital surveillance program for infection control and antimicrobial stewardship, the requirement for informed consent was waived.

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Publication 2023

Antibiotics Antimicrobial Stewardship Diagnosis Diarrhea Environmental Exposure Ethics Committees, Research Feces Hospitalization Immunosuppressive Agents Infection Control Patients Proton Pump Inhibitors

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What is Antimicrobial Stewardship?

Antimicrobial Stewardship is a coordinated program designed to improve and measure the appropriate use of antimicrobials. This approach involves selecting the optimal antimicrobial drug regimen, dose, duration of therapy, and route of administration. The goal is to achieve optimal clinical outcomes, minimize toxicity and adverse events, and reduce the emergence of antimicrobial-resistant strains.

What are the key objectives of Antimicrobial Stewardship programs?

The main objectives of Antimicrobial Stewardship programs are to promote patient safety, improve clinical outcomes, and combat the growing threat of antimicrobial resistance. These programs aim to ensure the judicious use of antimicrobials by healthcare providers, reducing unnecessary or inappropriate prescriptions and optimizing antimicrobial selection, dosing, and duration of therapy.

How can PubCompare.ai assist with Antimicrobial Stewardship?

PubCompare.ai is a powerful AI-powered platform that can help researchers and clinicians optimize their Antimicrobial Stewardship efforts. The platform allows you to efficiently screen protocol literature, leverage AI to pinpoint critical insights, and identify the most effective protocols related to Antimicrobial Stewardship for your specific research goals. The platform's AI-driven analysis can highlight key differences in protocol effectiveness, enabling you to choose the best option for reproducibility and accuracy.

What are some common challenges in Antimicrobial Stewardship?

Some of the common challenges in Antimicrobial Stewardship include educating healthcare providers on appropriate antimicrobial use, ensuring timely access to diagnostic testing, overcoming behavioral and cultural barriers to change, and balancing the need for antimicrobial access with the imperative to curb resistance. Effective Antimicrobial Stewardship programs must address these challenges through a multifaceted approach involving clinician education, data-driven decision-making, and robust monitoring and feedback mechanisms.

How does PubCompare.ai help address Antimicrobial Stewardship challenges?

PubCompare.ai's AI-powered platform can help address several key challenges in Antimicrobial Stewardship. By efficiently screening protocol literature and leveraging AI to identify the most effective antimicrobial protocols, the platform can support clinicians in making data-driven decisions and optimizing antimicrobial use. Additionally, the platform's ability to highlight critical insights and differences in protocol effectiveness can help overcome barriers to change and foster a more evidence-based approach to Antimicrobial Stewardship.

More about "Antimicrobial Stewardship"

Antimicrobial Stewardship (AS) is a coordinated, multifaceted approach to optimizing the use of antimicrobial agents and promoting patient safety.
This strategy aims to improve clinical outcomes, minimize the emergence of antimicrobial-resistant strains, and reduce adverse events associated with antimicrobial use.
Key aspects of Antimicrobial Stewardship include selecting the optimal antimicrobial drug regimen, determining the appropriate dose, duration of therapy, and route of administration.
Antimicrobial Stewardship Programs (ASPs) utilize data-driven interventions, such as prospective audit and feedback, to ensure the judicious use of antimicrobials.
Related terms and subtopics include Antibiotic Stewardship, Anti-infective Stewardship, Antimicrobial Resistance (AMR), Antibiotic Resistance, Antibiotic Utilization Review, Antimicrobial Therapy, and Therapeutic Drug Monitoring.
Statistical software like STATA v10, Stata 13, SPSS version 22.0, and NVivo 12 can be used to analyze data and inform Antimicrobial Stewardship initiatives.
Additionally, laboratory techniques like Vitek 2, MALDI-TOF MS, and MicroScan WalkAway can provide valuable insights into antimicrobial susceptibility patterns, supporting the development of effective Antimicrobial Stewardship strategies.
Research Electronic Data Capture (REDCap) can also be utilized to collect and manage data related to Antimicrobial Stewardship programs.
By leveraging a multidisciplinary approach and advanced analytical tools, Antimicrobial Stewardship aims to optimize antimicrobial use, enhance patient outcomes, and mitigate the growing threat of antimicrobial resistance.