S. Reza Jafarzadeh

Quantifying the improvement in sepsis diagnosis, documentation, and coding: the marginal causal effect of year of hospitalization on sepsis diagnosis

PURPOSE To quantify the coinciding improvement in the clinical diagnosis of sepsis, its documentation in the electronic health records, and subsequent medical coding of sepsis for billing purposes in recent years. METHODS We examined 98,267 hospitalizations in 66,208 patients who met systemic inflammatory response syndrome criteria at a tertiary care center from 2008 to 2012. We used g-computation to estimate the causal effect of the year of hospitalization on receiving an International Classification of Diseases, Ninth Revision, Clinical Modification discharge diagnosis code for sepsis by estimating changes in the probability of getting diagnosed and coded for sepsis during the study period. RESULTS When adjusted for demographics, Charlson-Deyo comorbidity index, blood culture frequency per hospitalization, and intensive care unit admission, the causal risk difference for receiving a discharge code for sepsis per 100 hospitalizations with systemic inflammatory response syndrome, had the hospitalization occurred in 2012, was estimated to be 3.9% (95% confidence interval [CI], 3.8%-4.0%), 3.4% (95% CI, 3.3%-3.5%), 2.2% (95% CI, 2.1%-2.3%), and 0.9% (95% CI, 0.8%-1.1%) from 2008 to 2011, respectively. CONCLUSIONS Patients with similar characteristics and risk factors had a higher of probability of getting diagnosed, documented, and coded for sepsis in 2012 than in previous years, which contributed to an apparent increase in sepsis incidence.

Longitudinal study of the effects of bacteremia and sepsis on 5-year risk of cardiovascular events

BACKGROUND The long-term and cumulative effect of multiple episodes of bacteremia and sepsis across multiple hospitalizations on the development of cardiovascular (CV) events is uncertain. METHODS We conducted a longitudinal study of 156 380 hospitalizations in 47 009 patients (≥18 years old) who had at least 2 inpatient admissions at an academic tertiary care center in St Louis, Missouri, from 1 January 2008 through 31 December 2012. We used marginal structural models, estimated by inverse probability weighting (IPW) of bacteremia or sepsis and IPW of censoring, to estimate the marginal causal effects of bacteremia and sepsis on developing the first observed incident CV event, including stroke, transient ischemic attack, and myocardial infarction (MI), during the study period. RESULTS Bacteremia and sepsis occurred during 4923 (3.1%) and 5544 (3.5%) hospitalizations among 3932 (8.4%) and 4474 (9.5%) patients, respectively. CV events occurred in 414 (10.5%) and 538 (12.0%) patients with prior episodes of bacteremia or sepsis, respectively, vs 3087 (7.2%) and 2963 (7.0%) patients without prior episodes of bacteremia or sepsis. The causal odds of experiencing a CV event was 1.52-fold (95% confidence interval [CI], 1.21- to 1.90-fold) and 2.39-fold (95% CI, 1.88- to 3.03-fold) higher in patients with prior instances of bacteremia or sepsis, respectively, compared to those without. Prior instances of septic shock resulted in a 6.91-fold (95% CI, 5.34- to 8.93-fold) increase in the odds of MI. CONCLUSIONS Prior instances of bacteremia and sepsis substantially increase the 5-year risk of CV events.

Updated Estimates Suggest a Much Higher Prevalence of Arthritis in United States Adults Than Previous Ones

National estimates of arthritis prevalence rely on a single survey question about doctor‐diagnosed arthritis without using survey information on joint symptoms, even though some subjects with only the latter have been shown to have arthritis. The sensitivity of the current surveillance definition is only 53% and 69% in subjects ages 45–64 years and ages ≥65 years, respectively, resulting in misclassification of nearly one‐half and one‐third of subjects in those age groups. This study was undertaken to estimate arthritis prevalence based on an expansive surveillance definition that is adjusted for the measurement errors in the current definition.

A central line care maintenance bundle for the prevention of central line–associated bloodstream infection in non–intensive care unit settings

OBJECTIVE To evaluate a central line care maintenance bundle to reduce central line-associated bloodstream infection (CLABSI) in non-intensive care unit settings. DESIGN Before-after trial with 12-month follow-up period. SETTING A 1,250-bed teaching hospital. PARTICIPANTS Patients with central lines on 8 general medicine wards. Four wards received the intervention and 4 served as controls. INTERVENTION A multifaceted catheter care maintenance bundle consisting of educational programs for nurses, update of hospital policies, visual aids, a competency assessment, process monitoring, regular progress reports, and consolidation of supplies necessary for catheter maintenance. RESULTS Data were collected for 25,542 catheter-days including 43 CLABSI (rate, 1.68 per 1,000 catheter-days) and 4,012 catheter dressing observations. Following the intervention, a 2.5% monthly decrease in the CLABSI incidence density was observed on intervention floors but this was not statistically significant (95% CI, -5.3% to 0.4%). On control floors, there was a smaller but marginally significant decrease in CLABSI incidence during the study (change in monthly rate, -1.1%; 95% CI, -2.1% to -0.1%). Implementation of the bundle was associated with improvement in catheter dressing compliance on intervention wards (78.8% compliance before intervention vs 87.9% during intervention/follow-up; P<.001) but improvement was also observed on control wards (84.9% compliance before intervention vs 90.9% during intervention/follow-up; P=.001). CONCLUSIONS A multifaceted program to improve catheter care was associated with improvement in catheter dressing care but no change in CLABSI rates. Additional study is needed to determine strategies to prevent CLABSI in non-intensive care unit patients. Infect Control Hosp Epidemiol 2016;37:692-698.

Outpatient antibiotic prescription trends in the United States: A national cohort study

OBJECTIVETo characterize trends in outpatient antibiotic prescriptions in the United StatesDESIGNRetrospective ecological and temporal trend study evaluating outpatient antibiotic prescriptions from 2013 to 2015SETTINGNational administrative claims data from a pharmacy benefits manager PARTICIPANTS. Prescription pharmacy beneficiaries from Express Scripts Holding CompanyMEASUREMENTSAnnual and seasonal percent change in antibiotic prescriptionsRESULTSApproximately 98 million outpatient antibiotic prescriptions were filled by 39 million insurance beneficiaries during the 3-year study period. The most commonly prescribed antibiotics were azithromycin, amoxicillin, amoxicillin/clavulanate, ciprofloxacin, and cephalexin. No significant changes in individual or overall annual antibiotic prescribing rates were found during the study period. Significant seasonal variation was observed, with antibiotics being 42% more likely to be prescribed during February than September (peak-to-trough ratio [PTTR], 1.42; 95% confidence interval [CI], 1.39-1.61). Similar seasonal trends were found for azithromycin (PTTR, 2.46; 95% CI, 2.44-3.47), amoxicillin (PTTR, 1.52; 95% CI, 1.42-1.89), and amoxicillin/clavulanate (PTTR, 1.78; 95% CI, 1.68-2.29).CONCLUSIONSThis study demonstrates that annual national outpatient antibiotic prescribing practices remained unchanged during our study period. Furthermore, seasonal peaks in antibiotics generally used to treat viral upper respiratory tract infections remained unchanged during cold and influenza season. These results suggest that inappropriate prescribing of antibiotics remains widespread, despite the concurrent release of several guideline-based best practices intended to reduce inappropriate antibiotic consumption; however, further research linking national outpatient antibiotic prescriptions to associated medical conditions is needed to confirm these findings.Infect Control Hosp Epidemiol 2018;39:584-589.

Effective Antibiotic Conservation by Emergency Antimicrobial Stewardship During a Drug Shortage.

We present the first description of an antimicrobial stewardship program (ASP) used to successfully manage a multi-antimicrobial drug shortage. Without resorting to formulary restriction, meropenem utilization decreased by 69% and piperacillin-tazobactam by 73%. During the shortage period, hospital mortality decreased (P=.03), while hospital length of stay remained unchanged. Infect Control Hosp Epidemiol 2017;38:356-359.

Corrected estimates for the prevalence of self-reported doctor-diagnosed arthritis among US adults

To the Editor: Hootman et al provided updated estimates for the current and future (i.e., projected) prevalence of self-reported doctor-diagnosed arthritis in the US based on 2010–2012 National Health Interview Survey (NHIS) data (1). An individual with arthritis was identified in NHIS by an affirmative answer to the question, “Have you ever been told by a doctor or other health professional that you have some form of arthritis, rheumatoid arthritis, gout, lupus, or fibromyalgia?”. The accuracy of this surveillance-aimed self-report case definition was previously reported in a validation study (2) and has been the basis for national estimates of arthritis prevalence. The validation study showed that the sensitivity and specificity of selfreported doctor-diagnosed arthritis are 52.5% and 79.6%, respectively, for subjects ages 45–65 years and 68.8% and 81.1%, respectively, for those ages

Bayesian estimation of the accuracy of ICD‐9‐CM‐ and CPT‐4‐based algorithms to identify cholecystectomy procedures in administrative data without a reference standard

65 years. Estimates for the prevalence of self-reported doctordiagnosed arthritis are subject to misclassification bias, as these estimates are not adjusted for the imperfect (i.e., ,100%) and also variable accuracy (i.e., distinct sensitivities across age groups) of the case definition used (1). To estimate the true prevalence of arthritis in the US after adjusting for this misclassification, we used a Bayesian approach, taking estimates for the apparent prevalence (i.e., the value reported by Hootman et al) using the most recently available 2015 NHIS data for adults ages 18–64 years (we shall call this group age ,65 years) and those ages

Impact of order set design on urine culturing practices at an academic medical centre emergency department

65 years (3). We formally incorporated the imperfect accuracy of the case definition as well as the uncertainty (i.e., variability) regarding these measures (e.g., sensitivities) in our analysis. For Bayesian inference, we initially described past knowledge by specifying probability distributions (i.e., referred to as priors). We then updated the priors with observed data to obtain updated (i.e., posterior) estimates for unknown parameters (e.g., true prevalence) (4). For probabilities, such as sensitivity, specificity, or prevalence parameters, priors are commonly specified by beta distributions. A beta distribution with parameters a and b, beta(a, b), is a probability distribution that is confined to 0 and 1, where a and b define the shape of the distribution. For example, the mean and mode of beta distribution are given by a/(a 1 b) and (a 2 1)/(a 1 b 2 2), respectively. Based on the validation study, we assumed that the most likely values for the sensitivity of the case definition in the populations ages ,65 years and ages

Trends of hospitalization for serious infections in patients with rheumatoid arthritis in the US between 1993 and 2013

65 years were 52.5% and 68.8%, respectively. We further assumed 95% certainty that the sensitivity was ,68.8% for the population ages ,65 years and .52.5% for the population age