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Infection control practitioner as advocate for the antibiogram: Launching local interventions to prevent antimicrobial resistance
June 2005
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Bioterrorism/Disaster Preparation Cost-Effectiveness Device-Related Infections Healthcare Worker Safety Infection Control Programs Infections in the Immunocompromised Host Infectious Diseases Long-Term Care Other Outbreak Investigation Patient Safety Pediatrics Product Evaluation Quality/Process Improvement/Adverse Outcomes Regulatory Compliance Site-Specific Infections Surveillance
Antimicrobial Resistance Abstract ID 49735 Tuesday, June 21
Infection control practitioner as advocate for the antibiogram: Launching local interventions to prevent antimicrobial resistance I Bakunas-Kenneley Case Western Reserve University/Frances Payne Bolton School of Nursing, Cleveland, Ohio ISSUE: Antimicrobial susceptibility data are often aggregated into ‘‘antibiograms,’’ which provide a summary picture of common organisms and their susceptibility to many antimicrobial agents. Local antibiograms (e.g., by unit, hospital, or facility) provide a starting point for making decisions about empiric antimicrobial treatment. Clinicians are not making use of the antibiogram information, nor taking into account the local patterns of resistance and the further increase of resistant strains resulting from inappropriate antibiotic therapy. PROJECT: The antibiotic imipenem is used within the acute care areas as a last resort medication for the treatment of serious infections. Current surveillance systems monitoring emerging drug resistance detect susceptibility patterns for each acute care entity. In this study, four hospitals that comprise part of a network were used to compare their resistance patterns to imipenem for the organism Pseudomonas aeruginosa, using their respective antibiograms. The dependent variable is the resistance of the organism; independent variables are the hospitals themselves and the time elapsed. A full model two-way ANOVA analysis was performed, with a subsequent one-way ANOVA performed as the reduced model. RESULTS: Retrospective review of the antibiogram resistance patterns for three time periods were analyzed from each of the four hospitals. Full model: Two-way ANOVA analysis indicates that Hu Hospital has the largest average resistance. Hi Hospital has a small average, indicating a higher percentage of susceptible isolates of Pseudomonas aeruginosa. Over time, the mean value of resistance did not change very much. Resistance patterns for one of the four hospitals were quite distinctly different (p=0.012), illustrating the need to monitor local data even when working within a multisite system.
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Vol. 33 No. 5
Reduced model: One-way ANOVA results confirmed that the one hospital had substantially higher rates of resistance than the other three hospitals. LESSONS LEARNED: One of the hospitals had a different antibiogram and resistance pattern than the other three hospitals. Knowledge of local patterns of resistance contained within the antibiogram will allow the infection control nurse to be alert to significant shifts in the populations of organisms within the locale and report those findings to all stakeholders. This information can be shared via Internet and PDA for real-time clinical decisions at the bedside. Abstract ID 50629 Monday, June 20
Improving immunization rates in long-term care utilizing unit-based vaccination specialists J King Veteran’s Administration, Knoxville, Iowa ISSUE: Immunization of the elderly is a national priority; however vaccination status can be overlooked. In an effort to increase awareness and compliance with vaccination in our long-term care residents, a vaccination task force was initiated utilizing hands-on caregivers. PROJECT: This Veteran’s Administration hospital consists of outpatient clinics, inpatient/acute psychiatric, and a 200-bed long-term care facility. In prior years, our facility had been implementing two separate immunization systems. The outpatient clinics utilized a nurse-driven protocol. Inpatients required practitioner assessment, physician order, and nursing vaccine administration. Inpatient system barriers reduced compliance rates below those in the outpatient population. Utilizing a multidisciplinary team including hands-on nursing staff, a protocol was piloted. Volunteers were solicited; training sessions were preformed on every unit for nursing and medical staff. Identifying a core group of vaccination specialists lessened the training burden. Specialists developed competency in assessment skills and charting. The protocol was trailed on all long-term care units during the September 2003–March 2004 influenza season. RESULTS: The infection control practitioner generates a monthly report to assess the immunization needs of patients. At the beginning of this process, it was hard to ascertain who on each inpatient unit should receive notification of immunization needs. With the core group of vaccination specialists, communication efforts improved. Compliance rates increased for immunizations. On one unit, a comparison of compliance rates was examined. This unit is a long-term 36-bed care unit with a mix of palliative patients. In February 2002, a report indicated 12 patients were in need of pneumococcal immunization. Under this system, the report was sent to the practitioner. By the time she received the message and assessed, several patients were no longer on the unit. In early November 2003, the same unit report was generated. Of the 36 patients, 4 were in need of the pneumococcal immunization. Two of these had been offered the immunization and refused. This report continues to show improvement of compliance rates for immunizations. LESSONS LEARNED: An immunization protocol is evidence-based prudent practice. Developing a cadre of unitbased vaccination specialists successfully increased vaccination rates. Frontline staff was essential. Abstract ID 51389 Tuesday, June 21
Emergence of resistant Acinetobacter baumannii in critically ill patients within an acute care teaching hospital and a long-term acute care facility P Wells C Stephens J DiPersio
E29
Bioterrorism/Disaster Preparation Cost-Effectiveness Device-Related Infections Healthcare Worker Safety Infection Control Programs Infections in the Immunocompromised Host Infectious Diseases Long-Term Care Other Outbreak Investigation Patient Safety Pediatrics Product Evaluation Quality/Process Improvement/Adverse Outcomes Regulatory Compliance Site-Specific Infections Surveillance
Antimicrobial Resistance Abstract ID 49735 Tuesday, June 21
Infection control practitioner as advocate for the antibiogram: Launching local interventions to prevent antimicrobial resistance I Bakunas-Kenneley Case Western Reserve University/Frances Payne Bolton School of Nursing, Cleveland, Ohio ISSUE: Antimicrobial susceptibility data are often aggregated into ‘‘antibiograms,’’ which provide a summary picture of common organisms and their susceptibility to many antimicrobial agents. Local antibiograms (e.g., by unit, hospital, or facility) provide a starting point for making decisions about empiric antimicrobial treatment. Clinicians are not making use of the antibiogram information, nor taking into account the local patterns of resistance and the further increase of resistant strains resulting from inappropriate antibiotic therapy. PROJECT: The antibiotic imipenem is used within the acute care areas as a last resort medication for the treatment of serious infections. Current surveillance systems monitoring emerging drug resistance detect susceptibility patterns for each acute care entity. In this study, four hospitals that comprise part of a network were used to compare their resistance patterns to imipenem for the organism Pseudomonas aeruginosa, using their respective antibiograms. The dependent variable is the resistance of the organism; independent variables are the hospitals themselves and the time elapsed. A full model two-way ANOVA analysis was performed, with a subsequent one-way ANOVA performed as the reduced model. RESULTS: Retrospective review of the antibiogram resistance patterns for three time periods were analyzed from each of the four hospitals. Full model: Two-way ANOVA analysis indicates that Hu Hospital has the largest average resistance. Hi Hospital has a small average, indicating a higher percentage of susceptible isolates of Pseudomonas aeruginosa. Over time, the mean value of resistance did not change very much. Resistance patterns for one of the four hospitals were quite distinctly different (p=0.012), illustrating the need to monitor local data even when working within a multisite system.
E30
Vol. 33 No. 5
Reduced model: One-way ANOVA results confirmed that the one hospital had substantially higher rates of resistance than the other three hospitals. LESSONS LEARNED: One of the hospitals had a different antibiogram and resistance pattern than the other three hospitals. Knowledge of local patterns of resistance contained within the antibiogram will allow the infection control nurse to be alert to significant shifts in the populations of organisms within the locale and report those findings to all stakeholders. This information can be shared via Internet and PDA for real-time clinical decisions at the bedside. Abstract ID 50629 Monday, June 20
Improving immunization rates in long-term care utilizing unit-based vaccination specialists J King Veteran’s Administration, Knoxville, Iowa ISSUE: Immunization of the elderly is a national priority; however vaccination status can be overlooked. In an effort to increase awareness and compliance with vaccination in our long-term care residents, a vaccination task force was initiated utilizing hands-on caregivers. PROJECT: This Veteran’s Administration hospital consists of outpatient clinics, inpatient/acute psychiatric, and a 200-bed long-term care facility. In prior years, our facility had been implementing two separate immunization systems. The outpatient clinics utilized a nurse-driven protocol. Inpatients required practitioner assessment, physician order, and nursing vaccine administration. Inpatient system barriers reduced compliance rates below those in the outpatient population. Utilizing a multidisciplinary team including hands-on nursing staff, a protocol was piloted. Volunteers were solicited; training sessions were preformed on every unit for nursing and medical staff. Identifying a core group of vaccination specialists lessened the training burden. Specialists developed competency in assessment skills and charting. The protocol was trailed on all long-term care units during the September 2003–March 2004 influenza season. RESULTS: The infection control practitioner generates a monthly report to assess the immunization needs of patients. At the beginning of this process, it was hard to ascertain who on each inpatient unit should receive notification of immunization needs. With the core group of vaccination specialists, communication efforts improved. Compliance rates increased for immunizations. On one unit, a comparison of compliance rates was examined. This unit is a long-term 36-bed care unit with a mix of palliative patients. In February 2002, a report indicated 12 patients were in need of pneumococcal immunization. Under this system, the report was sent to the practitioner. By the time she received the message and assessed, several patients were no longer on the unit. In early November 2003, the same unit report was generated. Of the 36 patients, 4 were in need of the pneumococcal immunization. Two of these had been offered the immunization and refused. This report continues to show improvement of compliance rates for immunizations. LESSONS LEARNED: An immunization protocol is evidence-based prudent practice. Developing a cadre of unitbased vaccination specialists successfully increased vaccination rates. Frontline staff was essential. Abstract ID 51389 Tuesday, June 21
Emergence of resistant Acinetobacter baumannii in critically ill patients within an acute care teaching hospital and a long-term acute care facility P Wells C Stephens J DiPersio