Search

Background The Centers for Disease Control and Prevention (CDC) uses standardized antimicrobial administration ratios (SAARs)—that is, observed-to-predicted ratios—to compare antibiotic use across facilities. CDC models adjust for facility characteristics when predicting antibiotic use but do not include patient diagnoses and comorbidities that may also affect utilization. This study aimed to identify comorbidities causally related to appropriate antibiotic use and to compare models that include these comorbidities and other patient-level claims variables to a facility model for risk-adjusting inpatient antibiotic utilization. Methods The study included adults discharged from Premier Database hospitals in 2016–2017. For each admission, we extracted facility, claims, and antibiotic data. We evaluated 7 models to predict an admission's antibiotic days of therapy (DOTs): a CDC facility model, models that added patient clinical constructs in varying layers of complexity, and an external validation of a published patient-variable model. We calculated hospital-specific SAARs to quantify effects on hospital rankings. Separately, we used Delphi Consensus methodology to identify Elixhauser comorbidities associated with appropriate antibiotic use. Results The study included 11 701 326 admissions across 576 hospitals. Compared to a CDC-facility model, a model that added Delphi-selected comorbidities and a bacterial infection indicator was more accurate for all antibiotic outcomes. For total antibiotic use, it was 24% more accurate (respective mean absolute errors: 3.11 vs 2.35 DOTs), resulting in 31–33% more hospitals moving into bottom or top usage quartiles postadjustment. Conclusions Adding electronically available patient claims data to facility models consistently improved antibiotic utilization predictions and yielded substantial movement in hospitals' utilization rankings. [ABSTRACT FROM AUTHOR]

Hospitals are implementing antimicrobial stewardship programs ( ASPs) in response to national guidelines to improve the use and to extend the utility of antiinfective drugs. An often implied purpose of ASPs is to curb or reverse the emergence of resistant bacteria. Because antibiotic use causes antibiotic resistance, there is a natural tendency to link local measures of antibiotic use to local measures of bacterial resistance, and the hospital antibiogram is a readily available measure of resistance. We performed a literature review to identify published reports that used hospitalwide and unit-specific antibiograms to assess the relationship of ASP interventions to changes in resistance. Eight studies were identified and reviewed. The relationship between hospital antibiotic use and resistance is complex, and the existing literature has several limitations. Furthermore, the antibiogram itself is neither designed nor well suited to reflect changes in hospital antimicrobial drug use. The literature on the effectiveness of ASPs in reducing resistance continues to emerge, but at this time the antibiogram bears an inconsistent relationship with changes in hospital antibiotic use and cannot be recommended to reliably evaluate an ASP intervention. Interrupted time series analysis is a superior strategy to assess the effect of an ASP intervention on bacterial resistance, but it is not widely used because of its complexity and greater data requirements. Nevertheless, before ASP efforts can be convincingly demonstrated to have a favorable impact on resistance, a more sophisticated approach that links drug use to resistance should become a priority, at least for hospitals that have sufficient resources. [ABSTRACT FROM AUTHOR]

Purpose. The degree of compliance with antibiogram guidance among University HealthSystem Consortium (UHC) hospitals was analyzed. Methods. The UHC Pharmacy Council Pharmacy Practice Advancement Committee conducted a survey to evaluate hospital policies regarding the generation, reporting, and utilization of antibiograms among UHC hospitals. The survey was distributed via a UHC online survey tool to pharmacy directors at 237 UHC hospitals. Responses were collected from April 13 to May 14, 2010. Results. Of the 237 hospitals to which surveys were sent, 49 hospitals (21%) from 28 states submitted survey responses. Forty-eight hospitals reported that they routinely generated antibiograms, and 36 reported that they adopted all or most of the standards recommended by the 2009 guidelines on antibiograms published by the Clinical and Laboratory Standards Institute (CLSI). The compliance rates to the four key CLSI recommendations were as follows: 98% reported data at least annually, 89% eliminated duplicate isolates, 83% did not include surveillance isolates, and 64% required at least 30 isolates for each reported species. Thirty-eight hospitals had an antimicrobial stewardship program; 35 of them formally reviewed antibiograms and 19 implemented new programs based on the antibiogram data. In 16 hospitals, formulary changes were made as a consequence of antibiogram results. In 30 hospitals, pharmacists had significant involvement in compiling, reviewing, and reporting antibiograms. Conclusion. Among respondents from 47 UHC hospitals, the compliance rates to four key CLSI recommendations for antibiograms ranged from 64% to 98%. Respondents from 30 hospitals reported significant involvement of pharmacists in compiling, reviewing, and reporting antibiograms. [ABSTRACT FROM AUTHOR]

Background. Hospitals are advised to measure antibiotic use and monitor its relationship to resistance. The World Health Organization's recommended metric is the defined daily dose (DDD). An alternative measure is the number of days of therapy (DOT). The purpose of this study was to contrast these measures. Methods. We measured the use of 50 antibacterial drugs that were administered to adults who were discharged from 130 US hospitals during 1 August 2002-31 July 2003. Results. Of 1,795,504 patients, 1,074,174 received at least 1 dose of an antibacterial drug (59.8%). The mean (± standard deviation) of total antibacterial drug use measured by the number of DDDs per 1000 patient-days and the number of DOTs per 1000 patient-days were not significantly different (792 ± 776, and 147 ± 120 respectively; P = .137 ), although the correlation was poor (r = 0.603). For some individual drugs, such as levofloxacin and linezolid, there was no significant difference between DDDs per 1000 patient-days and DOTs per 1000 patientdays, because the administered daily dosage was nearly equivalent to the DDD. When the administered dosage exceeded the DDD, such as for ampicillin-sulbactam and cefepime, estimates of use based on DDDs per 1000 patient-days significantly exceeded those based on DOTs per 1000 patient-days (P < .001). When the administered dosage was less than the DDD, such as for piperacillin-tazobactam and ceftriaxone, estimates of use based on DDDs per 1000 patient-days were significantly lower than those based on DOTs per 1000 patient-days (P < .001). Conclusion. The measurement of aggregate hospital antibiotic use by DDDs per 1000 patient-days and DOTs per 1000 patient-days is discordant for many frequently used antibacterial drugs, because the administered dose is dissimilar from the DDD recommended by the World Health Organization. DDD methods are useful for benchmarking purposes but cannot be used to make inferences about the number of DOTs or relative use for many antibacterial drugs. [ABSTRACT FROM AUTHOR]

Background. Fluoroquinolones are widely prescribed in hospitals and the community. Previous studies have shown associations between fluoroquinolone use and isolation of fluoroquinolone-resistant Eshcerichia coli and methicillin-resistant Staphylococcus aureus (MRSA). We performed an ecologic-level study to determine whether variability in hospital percentages of fluoroquinolone-resistant E. coli and MRSA were associated with fluoroquinolone use in hospitals and their surrounding communities. Methods. We measured fluoroquinolone use in 17 US hospitals and their surrounding communities in the year 2000. Data on fluoroquinolone use in hospitals was electronically extracted from billing data. Data on fluoroquinolone use in communities was obtained from IMS health data for all prescriptions filled in pharmacies within a 1 6-km radius of each hospital. We used hospital antibiograms to determine the percentage of isolates that were fluoroquinolone-resistant E. coli and MRSA, and we performed linear regression to determine the relationship between percentage of resistant isolates and fluoroquinolone use in hospitals and their surrounding communities. Results. There was a significant association between total fluoroquinolone use within hospitals and percentage of S. aureus isolates that were MRSA (r = 0.77; P = .0003) and between total fluoroquinolone use in the community and percentage of E. coli isolates that were fluoroquinolone-resistant E. coli (r = 0.68; P = .003). Population density within the 16-km radius also correlated with MRSA percentage (r = 0.57; P = .015) and fluoroquinolone- resistant E. coli percentage (r = 0.85; P = .002), but associations between total fluoroquinolone use and resistance remained significant after adjustment for population density. Conclusions. In this ecologic analysis, we found associations between fluoroquinolone use in hospitals and methicillin resistance in S. aureus and between fluoroquinolone use in communities and fluoroquinolone resistance in E. coli in hospitals. Antimicrobial use in hospitals and communities may have different relative importance with regard to resistance in different pathogens encountered in hospitals. [ABSTRACT FROM AUTHOR]

Few long-term multicenter investigations have evaluated the relationships between aggregate antimicrobial drug use in hospitals and bacterial resistance. We measured fluoroquinolone use from 1999 through 2003 in a network of US hospitals. The percentages of fluoroquinolone-resistant Pseudomonas aeruginosa and methicillin-resistant Staphylococcus aureus (MRSA) were obtained from yearly antibiograms at each hospital, Univariate linear regression showed significant associations between a hospital's volume of fluoroquinolone use and percent resistance in most individual study years (1999-2001 for P. aeruginosa, 1999-2002 for S. aureus). When the method of generalized estimating equations was used, a population-averaged longitudinal model incorporating total fluoroquinolone use and the previous year's resistance (to account for autocorrelation) did not show a significant effect of fluoroquinolone use on percent resistance for most drug-organism combinations, except for the relationship between levofloxacin use and percent MRSA. The ecologic relationship between fluoroquinolone use and resistance is complex and requires further study. [ABSTRACT FROM AUTHOR]

Rates of fluoroquinolone resistance among Pseudomonas aeruginosa in hospitals are increasing, but inter-hospital variability is great. We sought to determine whether this variability correlated to fluoroquinolone use in hospitals and in the surrounding community; Hospital quinolone use in 1999 (24 hospitals) through 2001 (35 hospitals) was determined from billing records. The number of fluoroquinolone prescriptions within a 10-mile (∼16-km) radius of each hospital was determined for 1999 and 2000. Hospital fluoroquinolone use increased from 1999 through 2001, from 137 to 163 defined daily doses (DDD)/1000 patient-days (P = .01). The rate of community fluoroquinolone use also increased, from 2.3 to 2.8 DDD/1000 inhabitant-days (P < .001). Rates of fluoroquinolone-resistant P. aeruginosa increased from 29% in 1999 to 36% in 2001 (P = .003). Both community and hospital fluoroquinolone use were predictive of rates of fluoroquinolone-resistant P. aeruginosa. Levofloxacin was associated with resistance, but ciprofloxacin was not. Most of the variability in resistance rates is explained by volume of fluoroquinolone use, both in the hospital and the surrounding community. [ABSTRACT FROM AUTHOR]