Long-term central venous catheter-related candidemia: A new approach towards diagnosis and management

A case-series analysis of approximately 811 cancer patients who developed Candidemia between 1989 and 1998 and seen at M. D. Anderson Cancer Center, was studied to assess the impact and timing of central venous catheter (CVC) removal on the outcome of fungal bloodstream infections in cancer patients with primary catheter-related Candidemia as well as secondary infections. ^ This study explored the diagnosis and the management of vascular catheter-associated fungemia in patients with cancer. The microbiologic and clinical factors were determined to predict catheter-related Candidemia. Those factors included, in addition to basic demographics, the underlying malignancy, chemotherapy, neutropenia, and other salient data. Statistical analyses included univariate and multivariate logistic regression to determine the outcome of Candidemia in relation to the timing of catheter removal, type of species, and to identify predictors of catheter-related infections. ^ The conclusions of the study aim at enhancing our mastery of issues involving CVC removal and potentially will have an impact on the management of nosocomial bloodstream infections related to timing of CVC removal and the optimal duration of treatment of catheter-related Candidemia. ^

A comparison of healthcare access, healthcare utilization and asthma self-management for Hispanic children in border and non-border regions of Texas

The purpose of this culminating experience was to investigate the relationships between healthcare utilization, insurance coverage, and socioeconomic characteristics of children with asthma along the Texas-Mexico Border. A secondary data analysis was conducted on cross-sectional data from the Texas Child Asthma Call-back Survey, a follow-up survey to the random digit dialed Behavior Risk Factor Surveillance Study (BRFSS) conducted between 2006-2009 ( n = 556 adults living in households with a child with asthma).^ The proportion of Hispanic children with asthma in Border areas of Texas was more than twice that of non-Border areas (84.8% vs. 28.8%). Parents in Border areas were less likely to have their own health insurance (OR = 0.251, 95% C.I. = 0.117-0.540) and less likely to complete the survey in English than Spanish (OR = 0.251 95% C.I. = 0.117-0.540) than parents in non-Border areas. No significant socio-economic or health care utilization differences were noted between Hispanic children living in Border areas compared to Hispanic children living in non-Border areas. Children with asthma along the Texas-Mexico Border, regardless of ethnicity and language, have insurance coverage rates, reported cost barriers to care, symptom management, and medication usage patterns similar to those in non-Border areas. When compared to English-speakers, Spanish-speaking parents in Texas as a whole are far less likely to be taught what to do during an asthma attack (50.2% vs. 78.6%).^ Language preference, rather than ethnicity or geographical residence, played a larger role on childhood asthma-related health disparities for children in Texas. Spanish-speaking parents in are less likely to receive adequate asthma self-management education. Investigating the effects of Hispanic acculturation rates and incongruent parent-child health insurance coverage may provide better insight into the health disparities of children along the Texas-Mexico Border.^

Effect of primary care availability and health insurance coverage on risk and cost of Preventable Hospitalizations in Harris County

Preventable Hospitalizations (PHs) are hospitalizations that can be avoided with appropriate and timely care in the ambulatory setting and hence are closely associated with primary care access in a community. Increased primary care availability and health insurance coverage may increase primary care access, and consequently may be significantly associated with risks and costs of PHs. Objective. To estimate the risk and cost of preventable hospitalizations (PHs); to determine the association of primary care availability and health insurance coverage with the risk and costs of PHs, first alone and then simultaneously; and finally, to estimate the impact of expansions in primary care availability and health insurance coverage on the burden of PHs among non-elderly adult residents of Harris County. Methods. The study population was residents of Harris County, age 18 to 64, who had at least one hospital discharge in a Texas hospital in 2008. The primary independent variables were availability of primary care physicians, availability of primary care safety net clinics and health insurance coverage. The primary dependent variables were PHs and associated hospitalization costs. The Texas Health Care Information Collection (THCIC) Inpatient Discharge data was used to obtain information on the number and costs of PHs in the study population. Risk of PHs in the study population, as well as average and total costs of PHs were calculated. Multivariable logistic regression models and two-step Heckman regression models with log-transformed costs were used to determine the association of primary care availability and health insurance coverage with the risk and costs of PHs respectively, while controlling for individual predisposing, enabling and need characteristics. Predicted PH risk and cost were used to calculate the predicted burden of PHs in the study population and the impact of expansions in primary care availability and health insurance coverage on the predicted burden. Results. In 2008, hospitalized non-elderly adults in Harris County had 11,313 PHs and a corresponding PH risk of 8.02%. Congestive heart failure was the most common PH. PHs imposed a total economic burden of $84 billion at an average of $7,449 per PH. Higher primary care safety net availability was significantly associated with the lower risk of PHs in the final risk model, but only in the uninsured. A unit increase in safety net availability led to a 23% decline in PH odds in the uninsured, compared to only a 4% decline in the insured. Higher primary care physician availability was associated with increased PH costs in the final cost model (β=0.0020; p<0.05). Lack of health insurance coverage increased the risk of PH, with the uninsured having 30% higher odds of PHs (OR=1.299; p<0.05), but reduced the cost of a PH by 7% (β=-0.0668; p<0.05). Expansions in primary care availability and health insurance coverage were associated with a reduction of about $1.6 million in PH burden at the highest level of expansion. Conclusions. Availability of primary care resources and health insurance coverage in hospitalized non-elderly adults in Harris County are significantly associated with the risk and costs of PHs. Expansions in these primary care access factors can be expected to produce significant reductions in the burden of PHs in Harris County.^

The number and timing of time -dependent covariate measurements for the Cox regression model

The problem of analyzing data with updated measurements in the time-dependent proportional hazards model arises frequently in practice. One available option is to reduce the number of intervals (or updated measurements) to be included in the Cox regression model. We empirically investigated the bias of the estimator of the time-dependent covariate while varying the effect of failure rate, sample size, true values of the parameters and the number of intervals. We also evaluated how often a time-dependent covariate needs to be collected and assessed the effect of sample size and failure rate on the power of testing a time-dependent effect.^ A time-dependent proportional hazards model with two binary covariates was considered. The time axis was partitioned into k intervals. The baseline hazard was assumed to be 1 so that the failure times were exponentially distributed in the ith interval. A type II censoring model was adopted to characterize the failure rate. The factors of interest were sample size (500, 1000), type II censoring with failure rates of 0.05, 0.10, and 0.20, and three values for each of the non-time-dependent and time-dependent covariates (1/4,1/2,3/4).^ The mean of the bias of the estimator of the coefficient of the time-dependent covariate decreased as sample size and number of intervals increased whereas the mean of the bias increased as failure rate and true values of the covariates increased. The mean of the bias of the estimator of the coefficient was smallest when all of the updated measurements were used in the model compared with two models that used selected measurements of the time-dependent covariate. For the model that included all the measurements, the coverage rates of the estimator of the coefficient of the time-dependent covariate was in most cases 90% or more except when the failure rate was high (0.20). The power associated with testing a time-dependent effect was highest when all of the measurements of the time-dependent covariate were used. An example from the Systolic Hypertension in the Elderly Program Cooperative Research Group is presented. ^