Development and Comparison of Risk-Adjusted Models to Benchmark Antibiotic Use in the University Healthsystem Consortium Hospitals (original) (raw)
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Benchmarking Inpatient Antimicrobial Use: A Comparison of Risk-Adjusted Observed-to-Expected Ratios
Clinical infectious diseases : an official publication of the Infectious Diseases Society of America, 2018
Increasing antibiotic resistance has made benchmarking appropriate inpatient antibiotic use a worldwide priority supported by expert societies and regulatory bodies, however standard risk-adjustment for fair inter-facility comparison has been elusive. We describe a risk-adjusted antibiotic exposure ratio that may help facilitate assessment of antimicrobial use. Retrospective cohort study of 2.7 million admissions evaluating a wide array of potential explanatory variables for correlation with expected antibiotic consumption in a two-step approach using recursive partitioning and Poisson regression. Observed-to-expected ratios of risk-adjusted antibiotic use were calculated. Three models of varying complexity were compared: (a) a Complex Ratio consisting of all available antibiotic use risk factors in a hierarchical model; (b) a Simplified ASP Ratio using common facility and encounter factors in a single level model; and (c) a Facility Ratio using only broad hospital characteristics. ...
Benchmarking Risk-Adjusted Adult Antibacterial Drug Use in 70 US Academic Medical Center Hospitals
Clinical Infectious Diseases, 2011
Background. Antimicrobial stewardship programs are advised to measure and risk-adjust antimicrobial use to facilitate interhospital comparisons, a process called benchmarking. The purpose of this investigation was to evaluate a new benchmarking strategy for antibacterials. Methods. Hospital-wide adult antibacterial drug use in 2009 was measured as days of therapy (DOT) and length of therapy (LOT) from billing records in 70 US academic medical centers (AMCs). Patients were assigned to 1 of 35 clinical service lines (CSL) based on their Medicare Severity Diagnosis Related Group. Expected (E) use was determined by indirect standardization and compared with observed (O) use. Results. Of 1 791 180 discharged adults, 63.7% received antibacterial drugs; the range by CSL was 14.3% (psychiatry) to 99.7% (lung transplant). Mean 6 SD hospital-wide use was 839 6 106 DOTs (range, 594-1109) and 536 6 53.0 LOT (range, 427-684) per 1000 patient-days. The ventilator support CSL had the most DOT per discharge, 39.4 6 9.4 days; the LOT was 21.5 6 4.5 days. The hospital-wide O/E ratio range was 0.7-1.45; in 5 AMCs the ratio exceeded the 90% confidence interval (CI) and was below the 90% CI in 6. Variability in use was explained by the proportion of treated patients within each CSL and mean LOT and DOT per discharge. Conclusions. Adult antibacterial drug use was benchmarked to expected use adjusted for patient mix, and outlier hospitals were identified. Differences between expected and observed use reflect usage patterns that were benchmarked and are targets for evaluation and intervention.
Clinical infectious diseases : an official publication of the Infectious Diseases Society of America, 2018
To provide a standardized, risk-adjusted method for summarizing antibiotic use (AU) and to enable hospitals to track their AU over time and compare their AU data to national benchmarks, CDC developed a new metric, the Standardized Antimicrobial Administration Ratio (SAAR). Hospitals reporting to the National Healthcare Safety Network (NHSN) AU Option collect and submit aggregated AU data electronically as antimicrobial days of therapy per patient days present. SAARs were developed for specific NHSN adult and pediatric patient care locations and cover five antimicrobial agent categories: (1) broad-spectrum agents predominantly used for hospital-onset/multi-drug resistant bacteria, (2) broad-spectrum agents predominantly used for community-acquired infections, (3) anti-MRSA agents, (4) agents predominantly used for surgical site infection prophylaxis, and (5) all antibiotic agents. The SAAR is an observed-to-predicted use ratio in which the predicted use is estimated from a statistica...
Antimicrobial resistance and infection control, 2014
Surveillance data of antibiotic use are increasingly being used for benchmarking purposes, but there is a lack of studies dealing with how hospital- and patient-related factors affect antibiotic utilization in hospitals. Our objective was to identify factors that may contribute to differences in antibiotic use. Based on pharmacy sales data (2006-2011), use of all antibiotics, all penicillins, and broad-spectrum antibiotics was analysed in 22 Health Enterprises (HEs). Antibiotic utilization was measured in World Health Organisation defined daily doses (DDDs) and hospital-adjusted (ha)DDDs, each related to the number of bed days (BDs) and the number of discharges. For each HE, all clinical specialties were included and the aggregated data at the HE level constituted the basis for the analyses. Fourteen variables potentially associated with the observed antibiotic use - extracted from validated national databases - were examined in 12 multiple linear regression models, with four differ...
Journal of Antimicrobial Chemotherapy, 2010
Our objective was to develop and test standardized methods for collection and statistical analysis of longitudinal data on hospital antibacterial use from different countries. Methods: We collected data on monthly supply of antibiotics from pharmacies in one hospital from each of 18 European countries. We applied a standardized method to classify drugs, measure use in defined daily doses and compare the effect of using occupied bed-days (OBDs) or admissions as denominators for longitudinal analysis. Results: Antibiotic use increased in 14 (78%) hospitals and decreased in 4 hospitals. For 16 (89%) hospitals, adjustment of antibiotic use with OBDs resulted in larger changes over time than adjustment with admissions. Inclusion of all hospital clinical activity variables (admissions, length of stay and OBDs) in multivariate time series analysis identified distinct hospital groups. Nine (50%) hospitals had statistically significant changes in antibiotic use (six increasing and three decreasing) that were not explained (n¼ 3) or only partially explained (n¼ 6) by change in clinical activity. Three (17%) hospitals had no significant change in antibiotic use. In the remaining six hospitals, apparent changes in antibiotic use were largely explained by changes in clinical activity. Conclusions: This is the first study to use a standardized method for data collection and longitudinal analysis of antibiotic use in different hospitals. These data suggest that determination of changes in antibiotic exposure of hospital patients over a period of time is unreliable if only one clinical activity variable (such as OBDs) is used as the denominator. We recommend inclusion of admissions, OBDs and length of stay in statistical, time series analysis of antibiotic use. This model is also relevant to longitudinal analysis of infections in hospitals.
Validating hospital antibiotic purchasing data as a metric of inpatient antibiotic use
The Journal of antimicrobial chemotherapy, 2015
Antibiotic purchasing data are a widely used, but unsubstantiated, measure of antibiotic consumption. To validate this source, we compared purchasing data from hospitals and external medical databases with patient-level dispensing data. Antibiotic purchasing and dispensing data from internal hospital records and purchasing data from IMS Health were obtained for two hospitals between May 2013 and April 2015. Internal purchasing data were validated against dispensing data, and IMS data were compared with both internal metrics. Scatterplots of individual antimicrobial data points were generated; Pearson's correlation and linear regression coefficients were computed. A secondary analysis re-examined these correlations over shorter calendar periods. Internal purchasing data were strongly correlated with dispensing data, with correlation coefficients of 0.90 (95% CI = 0.83-0.95) and 0.98 (95% CI = 0.95-0.99) at hospitals A and B, respectively. Although dispensing data were consistentl...
Clinical Microbiology and Infection, 2010
Hospitals in France are encouraged to monitor antibiotic consumption (AbC) and it is known that this differs among hospitals. The aim of the current study was to identify relevant and easily available adjustment criteria for the purpose of benchmarking. We analysed data from 34 public non-teaching hospitals and 43 private hospitals located in southwestern France and overseas departments using retrospective data from 2005. This study investigated the relationship between AbC expressed as defined daily doses per 1000 patient-days (DDD/1000 PDs) or per 100 admissions (DDD/100 admissions) and the number of venous central lines, the number of episodes of bacteraemia and various hospital characteristics. The relationship was tested using multiple linear analyses. The median total AbC in public hospitals was 395 DDD/1000 PDs (range, 196-737) and 341 DDD/100 admissions (range, 180-792). In private hospitals this was 422 DDD/1000 PDs (range, 113-717) and 212 DDD/100 admissions (range, 38-510). The best model for public hospitals included the proportion of PDs in surgery, intensive care and medical wards and explained 84% of the variability in AbC expressed as DDD/1000 PDs. For private hospitals, the mean length of stay and the proportion of PDs in surgery and medical wards explained 68% of the variability in AbC expressed as DDD/100 admissions. Overall, this French experience shows that relevant adjustment criteria for the comparison among hospitals are easily available. It is important that each country establish its own model considering the intrinsic peculiarities of the hospital system and taking into account both indicators (DDD/1000 PDs or DDD/100 admissions) to design the best model.
Analysis of antimicrobial consumption and cost in a teaching hospital
Journal of Infection and Public Health, 2014
Background: The aim of this study is to compare the periods before and after the intervention applied using the ATC/DDD method in order to ascertain the rational use of antibiotics in a newly established hospital. Method: The appropriateness of the hospital's antibiotic use, consumption rates and the costs were calculated and compared with other hospitals. Based on these data, an intervention has been planned in order to raise the quality of antibiotic use. The periods before and after the intervention were compared. Between 16 May 2011 and 23 May 2012, data were collected from all hospital units by the infectious diseases specialists and a point prevalence survey was conducted. Anatomical therapeutic chemical classification and the defined daily dose (DDD) methodology were used to calculate the antibiotic consumption. Results: On two specific days in 2011 and 2012, 194 out of 307 patients (63.2%) and 224 out of 412 patients (54.4%) received antibiotic treatment, respectively. In 2011 and 2012, the percentage of appropriate antibiotic use was 51% and 64.3%, respectively. Both in 2011 and 2012, inappropriate antibiotic use was found to be significantly higher in surgical clinics in comparison to the internal diseases clinics and the ICU. This was caused by the high rates of inappropriate perioperative antimicrobial prophylaxis observed in surgical clinics. During both years, approximately one-third of the antibiotics were prescribed for the purposes of perioperative prophylaxis, while 88.5% and 43.7% of these, respectively, were inappropriate and unnecessary. Cephalosporins, fluoroquinolones, combinations of penicillins
Clinical Infectious Diseases, 2003
Several findings from Argentina provide compelling evidence of the need for more rational use of antimicrobial agents. Thus, a multidisciplinary antimicrobial treatment committee for the development of a hospital-wide intervention program was formed to optimize the quality of antibiotic use in hospitals. Four successive steps were developed during 6-month periods: baseline data collection, introduction of a prescription form, education, and prescribing control. Sustained reduction of drug consumption was shown during the study ( ; ). Total cost savings was US$913,236. To estimate the consumption of cefepime and 2 R p 0.6885 P p .01 aminopenicillin-sulbactam in relation to that of the third-generation cephalosporins, 2 indices were calculated: Icfp and Iams, respectively. Decreasing resistance to ceftriaxone by Proteus mirabilis and Enterobacter cloacae proved to be associated with increasing Icfp. Decreasing rates of methicillin-resistant Staphylococcus aureus were related to increasing Iams. The present study indicates that a systematic program performed by a multidisciplinary team is a cost-effective strategy for optimizing antibiotic prescribing.