To estimate the incidence, duration and risk factors for diagnostic delays associated with pertussis.

We used longitudinal retrospective insurance claims from the Marketscan Commercial Claims and Encounters, Medicare Supplemental (2001–2020), and Multi-State Medicaid (2014–2018) databases.

Inpatient, emergency department, and outpatient visits.

The study included patients diagnosed with pertussis (International Classification of Diseases [ICD] codes) and receipt of macrolide antibiotic treatment.

We estimated the number of visits with pertussis-related symptoms before diagnosis beyond that expected in the absence of diagnostic delays. Using a bootstrapping approach, we estimated the number of visits representing a delay, the number of missed diagnostic opportunities per patient, and the duration of delays. Results were stratified by age groups. We also used a logistic regression model to evaluate potential factors associated with delay.

We identified 20,828 patients meeting inclusion criteria. On average, patients had almost 2 missed opportunities prior to diagnosis, and delay duration was 12 days. Across age groups, the percentage of patients experiencing a delay ranged from 29.7% to 37.6%. The duration of delays increased considerably with age from an average of 5.6 days for patients aged <2 years to 13.8 days for patients aged ≥18 years. Factors associated with increased risk of delays included emergency department visits, telehealth visits, and recent prescriptions for antibiotics not effective against pertussis.

Diagnostic delays for pertussis are frequent. More work is needed to decrease diagnostic delays, especially among adults. Earlier case identification may play an important role in the response to outbreaks by facilitating treatment, isolation, and improved contact tracing.

To investigate the scale of antimicrobial prescribing without a corresponding visit, and to compare the attributes of patients who received antimicrobials with a corresponding visit with those who did not have a visit.

Retrospective cohort.

We followed up 185,010 Medicare patients for 1 year after an acute myocardial infarction. For each antimicrobial prescribed, we determined whether the patient had an inpatient, outpatient, or provider claim in the 7 days prior to the antimicrobial prescription being filled. We compared the proportions of patient characteristics for those prescriptions associated with a visit and without a visit (ie, phantom prescriptions). We also compared the rates at which different antimicrobials were prescribed without a visit.

We found that of 356,545 antimicrobial prescriptions, 14.75% had no evidence of a visit in the week prior to the prescription being filled. A higher percentage of patients without a visit were identified as white (P<.001) and female (P<.001). Patients without a visit had a higher likelihood of survival and fewer additional cardiac events (acute myocardial infarction, cardiac arrest, stroke, all P<.001). Among the antimicrobials considered, amoxicillin, penicillin, and agents containing trimethoprim and methenamine were much more likely to be prescribed without a visit. In contrast, levofloxacin, metronidazole, moxifloxacin, vancomycin, and cefdinir were much less likely to be prescribed without a visit.

Among this cohort of patients with chronic conditions, phantom prescriptions of antimicrobials are relatively common and occurred more frequently among those patients who were relatively healthy.

Infect Control Hosp Epidemiol 2017;38:273–280

Inpatient length of stay (LOS) has been used as a measure of hospital quality and efficiency. Patients with Clostridium difficile infections (CDI) have longer LOS.

To describe the relationship between hospital CDI incidence and the LOS of patients without CDI.

Retrospective cohort analysis.

We predicted average LOS for patients without CDI at both the hospital and patient level using hospital CDI incidence. We also controlled for hospital characteristics (eg, bed size) and patient characteristics (eg, comorbidities, age).

Healthcare Cost and Utilization Project Nationwide Inpatient Sample, 2009–2011.

The Nationwide Inpatient Sample includes patients from a 20% sample of all nonfederal US hospitals.

Inpatient LOS was significantly longer (P<.001) at hospitals with greater CDI incidence at both the hospital and individual level. At a hospital level, a percentage point increase in the CDI incidence rate was associated with more than an additional day’s stay (between 1.19 and 1.61 days). At the individual level, controlling for all observable variables, a percentage point increase in the CDI incidence rate at their hospital was also associated with longer LOS (between 0.6 and 1.05 additional days). Hospital CDI incidence had a larger impact on LOS than many other commonly used predictors of LOS.

CDI rates are a predictor of LOS in patients without CDI at an individual and institutional level. CDI rates are easy to measure and report and thus may provide an important marker for hospital efficiency and/or quality.

Infect. Control Hosp. Epidemiol. 2016;37(4):404–410

To determine the effect of interhospital patient sharing via transfers on the rate of Clostridium difficile infections in a hospital.

Retrospective cohort.

Using data from the Healthcare Cost and Utilization Project California State Inpatient Database, 2005–2011, we identified 2,752,639 transfers. We then constructed a series of networks detailing the connections formed by hospitals. We computed 2 measures of connectivity, indegree and weighted indegree, measuring the number of hospitals from which transfers into a hospital arrive, and the total number of incoming transfers, respectively. Next, we estimated a multivariate model of C. difficile infection cases using the log-transformed network measures as well as covariates for hospital fixed effects, log median length of stay, log fraction of patients aged 65 or older, and quarter and year indicators as predictors.

We found an increase of 1 in the log indegree was associated with a 4.8% increase in incidence of C. difficile infection (95% CI, 2.3%–7.4%) and an increase of 1 in log weighted indegree was associated with a 3.3% increase in C. difficile infection incidence (1.5%–5.2%). Moreover, including measures of connectivity in our models greatly improved their fit.

Our results suggest infection control is not under the exclusive control of a given hospital but is also influenced by the connections and number of connections that hospitals have with other hospitals.

Infect. Control Hosp. Epidemiol. 2015;36(9):1031–1037

To determine whether well-child visits are a risk factor for subsequent influenza-like illness (ILI) visits within a child's family. DESIGN. Retrospective cohort.

Using data from the Medical Expenditure Panel Survey from the years 1996-2008, we identified 84,595 families. For each family, we determined those weeks in which a well-child visit or an ILI visit occurred. We identified 23,776 well-child-visit weeks and 97,250 ILI-visit weeks. We fitted a logistic regression model, where the binary dependent variable indicated an ILI clinic visit in a particular week. Independent variables included binary indicators to denote a well-child visit in the concurrent week or one of the previous 2 weeks, the occurrence of the ILI visit during the influenza season, and the presence of children in the family in each of the age groups 0–3, 4–7, and 8–17 years. Socioeconomic variables were also included. We also estimated the overall cost of well-child-exam-related ILI using data from 2008.

We found that an ILI office visit by a family member was positively associated with a well-child visit in the same or one of the previous 2 weeks (odds ratio, 1.54). This additional risk translates to potentially 778,974 excess cases of ILI per year in the United States, with a cost of $500 million annually.

Our results should encourage ambulatory clinics to strictly enforce infection control recommendations. In addition, clinics could consider time-shifting of well-child visits so as not to coincide with the peak of the influenza season.

To characterize the temporal progression of the monthly incidence of Clostridium difficile infections (CDIs) and to determine whether the incidence of CDI is related to the incidence of seasonal influenza.

A retrospective study of patients in the Nationwide Inpatient Sample during the period from 1998 through 2005.

We identified all hospitalizations with a primary or secondary diagnosis of CDI with use of International Classification of Diseases, 9th Revision, Clinical Modification codes, and we did the same for influenza. The incidence of CDI was modeled as an autoregression about a linear trend. To investigate the association of CDI with influenza, we compared national and regional CDI and influenza series data and calculated cross-correlation functions with data that had been prewhitened (filtered to remove temporal patterns common to both series). To estimate the burden of seasonal CDI, we developed a proportional measure of seasonal CDI.

Time-series analysis of the monthly number of CDI cases reveals a distinct positive linear trend and a clear pattern of seasonal variation (R2 = 0.98). The cross-correlation functions indicate that influenza activity precedes CDI activity on both a national and regional basis. The average burden of seasonal (ie, winter) CDI is 23%.

The epidemiologic characteristics of CDI follow a pattern that is seasonal and associated with influenza, which is likely due to antimicrobial use during influenza seasons. Approximately 23% of average monthly CDI during the peak 3 winter months could be eliminated if CDI remained at summer levels.

To determine the effect of a pandemic influenza preparedness drill on the rate of influenza vaccination among healthcare workers (HCWs).

Before-after intervention trial.

The University of Iowa Hospitals and Clinics (UIHC), a large, academic medical center, during 2005.

Staff members at UIHC.

UIHC conducted a pandemic influenza preparedness drill that included a goal of vaccinating a large number of HCWs in 6 days without disrupting patient care. Peer vaccination and mobile vaccination teams were used to vaccinate HCWs, educational tools were distributed to encourage HCWs to be vaccinated, and resources were allocated on the basis of daily vaccination reports. Logit models were used to compare vaccination rates achieved during the 2005 vaccination drill with the vaccination rates achieved during the 2003 vaccination campaign.

UIHC vaccinated 54% of HCWs (2,934 of 5,467) who provided direct patient care in 6 days. In 2 additional weeks, this rate increased to 66% (3,625 of 5,467). Overall, 66% of resident physicians (311 of 470) and 63% of nursing staff (1,429 of 2,255) were vaccinated. Vaccination rates in 2005 were significantly higher than the hospitalwide rate of 41% (5,741 of 14, 086) in 2003.

UIHC dramatically increased the influenza vaccination rate among HCWs by conducting a pandemic influenza preparedness drill. Additionally, the drill allowed us to conduct a bioemergency drill in a realistic scenario, use innovative methods for vaccine delivery, and secure administrative support for future influenza vaccination campaigns. Our study demonstrates how a drill can be used to improve vaccination rates significantly.

To determine the risk factors for Clostridium difficile–associated disease (CDAD) in a 25-bed rural hospital and to compare antimicrobial use ratios at the study hospital with those at a large academic medical center.

Case-control study.

A 25-bed rural hospital in Iowa during the period from August 2002 through January 2005.

A total of 17 case patients with CDAD and 34 control patients matched for age (ie, within 10 years of the case patient's age), sex, and admission date (ie, within 2 weeks of the case patient's admission date).

Retrospective medical record review was performed to obtain data on antimicrobial exposures during the 6 weeks before hospital admission for both case and control patients. Exact conditional logistic regression was used for univariable and multivariable analyses. Antimicrobial use ratios were calculated to compare the rates of antimicrobial use for case and control patients at the study hospital with the rates for patients evaluated in a study of CDAD at a nearly 700-bed teaching hospital.

Case patients had a larger cumulative number of days of antimicrobial use (P = .004), and they received a larger total number of antimicrobial agents during hospitalization (P = .001). Antimicrobial use ratios were higher for both case and control patients at the smaller hospital, compared with the larger hospital.

CDAD at a small rural hospital was not associated with exposure to the antimicrobial classes that are typically associated with CDAD, but was instead related to the total number of antimicrobials used to treat patients. The rate of antimicrobial use for case and control patients was about 40% higher at the small rural hospital, compared with the corresponding rates at a large academic medical center.