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To estimate the burden of Clostridium difficile infections (CDIs) due to interfacility patient sharing at regional and hospital levels.
Retrospective observational study.
We used data from the Healthcare Cost and Utilization Project California State Inpatient Database (2005–2011) to identify 26,878,498 admissions and 532,925 patient transfers. We constructed a weighted, directed network among the hospitals by defining an edge between 2 hospitals to be the monthly average number of patients discharged from one hospital and admitted to another on the same day. We then used a network autocorrelation model to study the effect of the patient sharing network on the monthly average number of CDI cases per hospital, and we estimated the proportion of CDI cases attributable to the network.
We found that 13% (95% confidence interval [CI], 7.6%–18%) of CDI cases were due to diffusion through the patient-sharing network. The network autocorrelation parameter was estimated at 5.0 (95% CI, 3.0–6.9). An increase in the number of patients transferred into and/or an increased CDI rate at the hospitals from which those patients originated led to an increase in the number of CDIs in the receiving hospital.
A minority but substantial burden of CDI infections are attributable to hospital transfers. A hospital’s infection control may thus be nontrivially influenced by its neighboring hospitals. This work adds to the growing body of evidence that intervention strategies designed to minimize HAIs should be done at the regional rather than local level.
To determine the effect of interhospital patient sharing via transfers on the rate of Clostridium difficile infections in a hospital.
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.
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