Amy L. Pakyz

Trends in Antibacterial Use in US Academic Health Centers: 2002 to 2006

BACKGROUND Antibacterial drug use is a major risk factor for bacterial resistance, but little is known about antibacterial use in US hospitals. The objectives of this study were to characterize trends in antibacterial use in a sample of US hospitals and to identify predictors of use. METHODS We measured systemic antibacterial use from validated claims data at 22 university teaching hospitals from January 1, 2002, through December 31, 2006, and we examined potential predictors of use in 2006, including hospital and patient demographics and antibacterial stewardship policies. RESULTS A total of 775,731 adult patients were discharged in 35 hospitals during 2006, and 492,721 (63.5%) received an antibacterial drug. The mean (SD) total antibacterial use increased from 798 (113) days of therapy per 1000 patient days in 2002 to 855 (153) in 2006 (P < .001). Fluoroquinolones were the most commonly used antibacterial class from 2002 through 2006, and use remained stable. Piperacillin sodium-tazobactam sodium and carbapenem use increased significantly, and aminoglycoside use declined. Cefazolin sodium was the most commonly used antibacterial drug in 2002 and 2003 but was eclipsed by vancomycin hydrochloride in 2004. The strongest predictor of broad-spectrum antibacterial use was explained by differences across hospitals in the mean durations of therapy. CONCLUSIONS Total antibacterial use in adults increased significantly from 2002 through 2006 in this sample of academic health centers, driven by increases in the use of broad-spectrum agents and vancomycin. These developments have important implications for acquired resistance among nosocomial pathogens, particularly for methicillin-resistant Staphylococcus aureus (MRSA).

Relationship of Carbapenem Restriction in 22 University Teaching Hospitals to Carbapenem Use and Carbapenem-Resistant Pseudomonas aeruginosa

ABSTRACT Many hospital antimicrobial stewardship programs restrict the availability of selected drugs by requiring prior approval. Carbapenems may be among the restricted drugs, but it is unclear if hospitals that restrict availability actually use fewer carbapenems than hospitals that do not restrict use. Nor is it clear if restriction is related to resistance. We evaluated the relationship between carbapenem restriction and the volume of carbapenem use and both the incidence rate and proportion of carbapenem-resistant Pseudomonas aeruginosa isolates from 2002 through 2006 in a retrospective, longitudinal, multicenter analysis among a consortium of academic health centers. Carbapenem use was measured from billing records as days of therapy per 1,000 patient days. Hospital antibiograms were used to determine both the incidence rate and proportion of carbapenem-resistant P. aeruginosa isolates. A survey inquired about restriction policies for antibiotics, including carbapenems. General linear mixed models were used to examine study outcomes. Among 22 hospitals with sufficient data for analysis, overall carbapenem use increased significantly over the 5 years of study (P < 0.0001), although overall carbapenem resistance in P. aeruginosa did not change. Hospitals that restricted carbapenems (n = 8; 36%) used significantly fewer carbapenems (P = 0.04) and reported lower incidence rates of carbapenem-resistant P. aeruginosa (P = 0.01) for all study years. Fluoroquinolone use was a potential confounder of these relationships, but hospitals that restricted carbapenems actually used fewer fluoroquinolones than those that did not. Restriction of carbapenems is associated with both lower use and lower incidence rates of carbapenem resistance in P. aeruginosa.

Use of international classification of diseases, ninth revision, clinical modification codes and medication use data to identify nosocomial clostridium difficile infection

OBJECTIVE The International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) code for Clostridium difficile infection (CDI) is used for surveillance of CDI. However, the ICD-9-CM code alone cannot separate nosocomial cases from cases acquired outside the institution. The purpose of this study was to determine whether combining the ICD-9-CM code with medication treatment data for CDI in hospitalized patients could enable us to distinguish between patients with nosocomial CDI and patients who were admitted with CDI. The primary objective was to compare the sensitivity, specificity, and predictive value of using the combination of ICD-9-CM code for CDI and CDI treatment records to identify cases of nosocomial CDI with the sensitivity, specificity, and predictive value of using the ICD-9-CM code alone. DESIGN Validation sample cross-sectional study. SETTING Academic health center. METHODS Administrative claims data from July 1, 2004, to June 30, 2005, were queried to identify adults discharged with an ICD-9-CM code for CDI and to find documentation of CDI therapy with oral vancomycin or metronidazole. Laboratory and medical records were queried to identify symptomatic CDI toxin-positive adult patients with nosocomial CDI and were compared with records of patients whose cases were predicted to be nosocomial by means of ICD-9-CM code and CDI therapy data. RESULTS Of 23,920 adult patients discharged from the hospital, 62 had nosocomial CDI according to symptoms and toxin assay. The sensitivity of the ICD-9-CM code alone for identifying nosocomial CDI was 96.8%, the specificity was 99.6%, the positive predictive value was 40.8%, and the negative predictive value was 100%. When CDI drug therapy was included with the ICD-9-CM code, the sensitivity ranged from 58.1% to 85.5%, specificity was virtually unchanged, and the range in positive predictive value was 37.9%-80.0%. CONCLUSION Combining the ICD-9-CM code for CDI with drug therapy information increased the positive predictive value for nosocomial CDI but decreased the sensitivity.

Trends in Antibacterial Use in Hospitalized Pediatric Patients in United States Academic Health Centers

Trends in pediatric antibacterial use were examined in 20 academic health centers during the period 2002-2007. There was a significant increase in the use of linezolid (P < .001) and of macrolides (P = .001) and a significant decrease in the use of aminoglycosides (P < .001) and of first-generation cephalosporins (P < .001).

Variability in activity of hepatic CYP3A4 in patients infected with HIV.

Study Objectives. To evaluate hepatic cytochrome P450 (CYP) 3A4 activity in patients infected with the human immunodeficiency virus (HIV) using the erythromycin breath test (ERMBT), and to examine the relationship of the ERMBT to plasma concentrations of indinavir and nelfinavir.

Medication risk factors associated with healthcare-associated Clostridium difficile infection: a multilevel model case–control study among 64 US academic medical centres

OBJECTIVES The main objective of this study was to determine patient- and hospital-level medication risk factors associated with Clostridium difficile infection (CDI) occurrence among patients clustered within hospitals using a multilevel model. METHODS Patients with healthcare-associated (HA)-CDI were identified from among 64 academic medical centres in 2009. A frequency match was conducted; for each case, up to two controls were selected, matched on similar pre-infection length of stay and clinical service line. Patient- and hospital-level medication use, including antibacterial and gastric acid-suppressant agents, was assessed using a two-level logistic regression model. RESULTS A total of 5967 CDI cases and 8167 controls were included in the analysis. The odds of acquiring HA-CDI increased with the following medications [OR (95% CI)]: anti-methicillin-resistant Staphylococcus aureus agents [1.38 (1.22-1.56)]; third- or fourth-generation cephalosporins [1.75 (1.62-1.89)]; carbapenems [1.60 (1.44-1.79)]; β-lactam/β-lactamase inhibitor combinations [1.49 (1.36-1.64)]; vancomycin [1.73 (1.57-1.89)]; and proton pump inhibitors [1.43 (1.30-1.57)]. The odds of acquiring HA-CDI decreased with the following medications: clindamycin [0.74 (0.63-0.87)]; and macrolides [0.88 (0.77-0.99)]. Controlling for patient-level covariates, no hospital-level medication covariates that we analysed had statistically significant effects on HA-CDI. The odds of acquiring HA-CDI increased with the hospital proportion of patients aged ≥ 65 years [1.01 (1.00-1.02)]. CONCLUSIONS We found several medications that were associated with the risk of patients developing HA-CDI, including β-lactam/β-lactamase inhibitor combinations, third- or fourth-generation cephalosporins, carbapenems, vancomycin, proton pump inhibitors and anti-methicillin-resistant S. aureus agents. There were no medication effects significant at the hospital level.

Economic impact of Clostridium difficile infection in a multihospital cohort of academic health centers.

Study Objective. To assess the economic impact of Clostridium difficile infection (CDI) in a large multihospital cohort.

The Utility of Hospital Antibiograms as Tools for Guiding Empiric Therapy and Tracking Resistance: Insights from the Society of Infectious Diseases Pharmacists

Hospital antibiograms are commonly used to help guide empiric antimicrobial treatment and are an important component of detecting and monitoring trends in antimicrobial resistance. To serve these purposes, antibiograms must be constructed using standardized methods that allow inter‐ and intrahospital comparisons. Antibiograms that include surveillance cultures and duplicate bacterial isolates can overestimate rates of resistance. In 2002, the National Committee for Clinical Laboratory Standards (now known as the Clinical and Laboratory Standards Institute [CLSI]) published standards for constructing antibiograms. According to national surveys, many of the recommended elements of the CLSI document have not been fully adopted. In lieu of full compliance with CLSI standards, it is necessary that the methods used to construct antibiograms are clearly delineated. Antibiograms have several limitations, such as their inability to track emergence of resistance during therapy. The antibiogram can serve as a valuable tool in guiding antimicrobial therapy, but other patient factors, such as previous infection history and antibiotic use, also need to be considered. Additional data are needed for specialized applications of resistance analyses.

Facilitators and barriers to implementing antimicrobial stewardship strategies: Results from a qualitative study

BACKGROUND Many hospitals have implemented antimicrobial stewardship programs (ASPs) and have included in their programs strategies such as prior authorization and audit and feedback. However there are few data concerning the facilitators and barriers that ASPs face when implementing their strategies. We conducted a qualitative study to discern factors that lead to successful uptake of ASP strategies. METHODS Semistructured telephone interviews were conducted from June-July 2013 with 15 ASP member pharmacists and 6 physicians representing 21 unique academic medical centers. RESULTS Successful implementation of ASP strategies was found to be related to communication style, types of relationships formed between the ASP and non-ASP personnel, and conflict management. Success was also influenced by the availability of resources in the form of adequate personnel, health information technology personnel and infrastructure, and the ability to generate and analyze ASP-specific data. Types of effective strategies commonly cited included audit and feedback; prior authorization, especially with an educative component; and use of real-time alert technology and guidelines. CONCLUSIONS Several factors may influence ASP success in the implementation of their strategies. ASP members may use these findings to improve upon the success of their programs.

Diversity of antimicrobial use and resistance in 42 hospitals in the United States.

Study Objective. To measure diversity (or heterogeneity) of antibiotic use in a sample of hospitals in the United States and to assess an association with bacterial resistance.