Medication Reconciliation during Transitions of Care Across Institutions: A Quantitative Analysis of Challenges and Opportunities.

OBJECTIVE: Medication discrepancies between clinical systems may pose a patient safety hazard. In this paper, we identify challenges and quantify medication discrepancies across transitions of care. METHODS: We used structured clinical data and free-text hospital discharge summaries to compare active medications' lists at four time points: preadmission (outpatient), at-admission (inpatient), at-discharge (inpatient), and postdischarge (outpatient). Medication lists were normalized to RxNorm. RxNorm identifiers were further processed using the RxNav API to identify the ingredient. The specific drugs and ingredients from inpatient and outpatient medication lists were compared. RESULTS: Using RxNorm drugs, the median percentage intersection when comparing active medication lists within the same electronic health record system ranged between 94.1 and 100% indicating substantial overlap. Similarly, when using RxNorm ingredients the median percentage intersection was 94.1 to 100%. In contrast, the median percentage intersection when comparing active medication lists across EHR systems was significantly lower (RxNorm drugs: 6.1-7.1%; RxNorm ingredients: 29.4-35.0%) indicating that the active medication lists were significantly less similar (p < 0.05).Medication lists in the same EHR system are more similar to each other (fewer discrepancies) than medication lists in different EHR systems when comparing specific RxNorm drug and the more general RxNorm ingredients at transitions of care. Transitions of care that require interoperability between two EHR systems are associated with more discrepancies than transitions where medication changes are expected (e.g., at-admission vs. at-discharge). Challenges included lack of access to structured, standardized medication data across systems, and difficulty distinguishing medications from orderable supplies such as lancets and diabetic test strips. CONCLUSION: Despite the challenges to medication normalization, there are opportunities to identify and assist with medication reconciliation across transitions of care between institutions.

The beneficial effect of providing kidney transplantation information on transplantation status differs between for-profit and nonprofit dialysis centers.

Informing end-stage kidney disease patients about kidney transplantation options increases the likelihood of kidney transplant waiting list (WL) enrollment and live donor kidney transplant (LDKT) receipt. Patients in for-profit dialysis centers have lower rates of WL enrollment and LDKT receipt. This study examined if the ownership status of dialysis centers modified the association between informing patients about transplantation options and patients' transplantation status. Multilevel analysis using mixed-effect multinomial logistic regression was performed using the United States Renal Data System (USRDS) data (January 2005 to December 2017). The study showed that informing patients improved the odds of WL enrollment and LDKT receipt. However, the effect of informing patients on transplantation status was less pronounced at for-profit as compared with nonprofit centers (Nonprofit: WL enrollment OR: 2.23 [95% CI: 2.07-2.40], and LDKT receipt OR: 3.35 [95% CI: 2.65-4.25]. For-profit: WL enrollment OR: 1.73 [95% CI: 1.66-1.79], and LDKT receipt OR: 2.35 [95% CI: 2.08-2.66]), although the odds of informing patients was higher for for-profit centers, and type of patients informed were similar across both types of centers. Information provided by for-profit centers was potentially less effective than those provided by nonprofit centers. Standardized guidelines for transplantation information provision are needed in order to ensure similar informational quality across centers.

Understanding Pediatric Surgery Cancellation: Geospatial Analysis.

BACKGROUND: Day-of-surgery cancellation (DoSC) represents a substantial wastage of hospital resources and can cause significant inconvenience to patients and families. Cancellation is reported to impact between 2% and 20% of the 50 million procedures performed annually in American hospitals. Up to 85% of cancellations may be amenable to the modification of patients' and families' behaviors. However, the factors underlying DoSC and the barriers experienced by families are not well understood. OBJECTIVE: This study aims to conduct a geospatial analysis of patient-specific variables from electronic health records (EHRs) of Cincinnati Children's Hospital Medical Center (CCHMC) and of Texas Children's Hospital (TCH), as well as linked socioeconomic factors measured at the census tract level, to understand potential underlying contributors to disparities in DoSC rates across neighborhoods. METHODS: The study population included pediatric patients who underwent scheduled surgeries at CCHMC and TCH. A 5-year data set was extracted from the CCHMC EHR, and addresses were geocoded. An equivalent set of data >5.7 years was extracted from the TCH EHR. Case-based data related to patients' health care use were aggregated at the census tract level. Community-level variables were extracted from the American Community Survey as surrogates for patients' socioeconomic and minority status as well as markers of the surrounding context. Leveraging the selected variables, we built spatial models to understand the variation in DoSC rates across census tracts. The findings were compared to those of the nonspatial regression and deep learning models. Model performance was evaluated from the root mean squared error (RMSE) using nested 10-fold cross-validation. Feature importance was evaluated by computing the increment of the RMSE when a single variable was shuffled within the data set. RESULTS: Data collection yielded sets of 463 census tracts at CCHMC (DoSC rates 1.2%-12.5%) and 1024 census tracts at TCH (DoSC rates 3%-12.2%). For CCHMC, an L2-normalized generalized linear regression model achieved the best performance in predicting all-cause DoSC rate (RMSE 1.299%, 95% CI 1.21%-1.387%); however, its improvement over others was marginal. For TCH, an L2-normalized generalized linear regression model also performed best (RMSE 1.305%, 95% CI 1.257%-1.352%). All-cause DoSC rate at CCHMC was predicted most strongly by previous no show. As for community-level data, the proportion of African American inhabitants per census tract was consistently an important predictor. In the Texas area, the proportion of overcrowded households was salient to DoSC rate. CONCLUSIONS: Our findings suggest that geospatial analysis offers potential for use in targeting interventions for census tracts at a higher risk of cancellation. Our study also demonstrates the importance of home location, socioeconomic disadvantage, and racial minority status on the DoSC of children's surgery. The success of future efforts to reduce cancellation may benefit from taking social, economic, and cultural issues into account.

Exploring the Spatial Association between Social Deprivation and Cardiovascular Disease Mortality at the Neighborhood Level.

Cardiovascular disease (CVD), the leading cause of death in the United States, is impacted by neighborhood-level factors including social deprivation. To measure the association between social deprivation and CVD mortality in Harris County, Texas, global (Ordinary Least Squares (OLS) and local (Geographically Weighted Regression (GWR)) models were built. The models explored the spatial variation in the relationship at a census-tract level while controlling for age, income by race, and education. A significant and spatially varying association (p < .01) was found between social deprivation and CVD mortality, when controlling for all other factors in the model. The GWR model provided a better model fit over the analogous OLS model (R2 = .65 vs. .57), reinforcing the importance of geography and neighborhood of residence in the relationship between social deprivation and CVD mortality. Findings from the GWR model can be used to identify neighborhoods at greatest risk for poor health outcomes and to inform the placement of community-based interventions.

Survival Benefits of Treatment Access Among Underserved Breast Cancer Patients Diagnosed Through the Texas Breast and Cervical Cancer Services Program.

PURPOSE: The Texas Breast and Cervical Cancer Services (BCCS) program was established to address socioeconomic disparities in breast and cervical cancer screening and survival. This study examined the impact of the program on treatment and survival of breast cancer patients. METHODS: A retrospective analysis was performed using the Texas Cancer Registry data linked to the BCCS program data. The sample consisted of 40- to 64-year-old women screened and diagnosed with breast cancer through the BCCS program (participants) and similar women living in low socioeconomic status census tracts and diagnosed outside the program (comparison group) during 1995-2008. Regular screeners among the participants were also compared with the comparison group. RESULTS: Participants had lower rates of breast surgery and higher rates of chemotherapy as compared with the comparison group. Participants undergoing surgery had higher rates of mastectomy (as compared with breast-conserving surgery) and lower rates of adjuvant radiation therapy. Unadjusted survival rates were similar between the participants and the comparison group, and higher among regular screeners, which was primarily driven by stage at diagnosis. Adjusted survival rates were similar between the 3 groups. CONCLUSIONS: Although there are differences in the types of treatment provided to the participants and the comparison group, there is no evidence of guideline noncompliance or stage-inappropriate treatment provision in either of the groups. Despite being diagnosed with a more advanced stage, the participants had similar unadjusted and adjusted survival rates as the comparison group. Access to timely treatment improved survival and brought the underserved participants on par with the comparison group.

The impact of potential mitigation strategies on the predicted spread of foot and mouth disease in white-tailed deer in south Texas.

The United States has been free of FMD since the 1920s. Faced with an incursion of FMD virus that might involve wildlife species, it is crucial that appropriate mitigation strategies be applied rapidly to control the disease. Disease spread models can be used to evaluate the design of optimal strategies. Using a previously developed susceptible-infected-recovered geographic automata model (Sirca) to simulate the spread of FMD through white-tailed deer populations in south Texas, we conducted a series of experiments to determine how pre-emptive mitigation strategies applied to white-tailed deer populations might impact the predicted magnitude and distribution of outbreaks following FMD virus incursion. Based on previously derived deer distributions in the two ecoregions found within the study area, simulated outbreaks were evaluated by comparing the median number of deer predicted to be infected and the median area predicted affected for a baseline scenario and 3 mitigation strategies: targeted cull, random cull and targeted depopulation buffer. Substantial differences were observed in the predicted magnitude of outbreaks both by mitigation strategy and by ecoregion: depending on the ecoregion, the creation of a targeted depopulation buffer could reduce the number of deer predicted infected by up to 52%, and the area affected by up to 31%. Results suggest that the outcome of an FMD incursion that involves wildlife species, such as white-tailed deer in south Texas, might depend on both where the incursion occurs and the type of pre-emptive mitigation strategy applied.

Modelling spread of foot-and-mouth disease in wild white-tailed deer and feral pig populations using a geographic-automata model and animal distributions.

We investigated how the size and distribution of wild deer and feral pigs - species that might act as potential foot-and-mouth disease (FMD) virus maintenance hosts - might affect the persistence and spread of FMD. We used a susceptible-latent-infected-recovered geographic-automata model and spatially referenced data from southern Texas, USA. Within this study area, 100 locations were randomly selected and FMD virus spread was simulated (50 simulations each) at each location. As expected, the predicted sizes (km(2)) of the wild deer outbreaks were highly correlated (r(SP)>0.95) with the number of deer at incursion locations, the total number of deer within 2 km of incursion locations, and the minimum and maximum deer herd size within 2 km of incursion locations. However, the predicted sizes of the feral pig outbreaks were only moderately correlated (r(SP) 0.63-0.67) with the total, maximum and variance of the number of feral pigs within 2 km of incursion locations. Lack of continuity within the feral pig herd distribution across the landscape makes predicting disease spread more difficult than for deer, a more homogenously distributed species. When assessing the potential of wild and feral animal species at a locality to act as maintenance hosts of FMD virus, estimates of the population size and distribution might serve as a useful indicator of potential outbreaks in some circumstances.

The impact of seasonal variability in wildlife populations on the predicted spread of foot and mouth disease.

Modeling potential disease spread in wildlife populations is important for predicting, responding to and recovering from a foreign animal disease incursion such as foot and mouth disease (FMD). We conducted a series of simulation experiments to determine how seasonal estimates of the spatial distribution of white-tailed deer impact the predicted magnitude and distribution of potential FMD outbreaks. Outbreaks were simulated in a study area comprising two distinct ecoregions in South Texas, USA, using a susceptible-latent-infectious-resistant geographic automata model (Sirca). Seasonal deer distributions were estimated by spatial autoregressive lag models and the normalized difference vegetation index. Significant (P < 0.0001) differences in both the median predicted number of deer infected and number of herds infected were found both between seasons and between ecoregions. Larger outbreaks occurred in winter within the higher deer-density ecoregion, whereas larger outbreaks occurred in summer and fall within the lower deer-density ecoregion. Results of this simulation study suggest that the outcome of an FMD incursion in a population of wildlife would depend on the density of the population infected and when during the year the incursion occurs. It is likely that such effects would be seen for FMD incursions in other regions and countries, and for other diseases, in cases in which a potential wildlife reservoir exists. Study findings indicate that the design of a mitigation strategy needs to take into account population and seasonal characteristics.

Simulation of foot-and-mouth disease spread within an integrated livestock system in Texas, USA.

We used a simulation study to assess the impact of an incursion of foot-and-mouth disease (FMD) virus on the livestock industries in an 8-county area of the Panhandle region of Texas, USA. The study was conducted in a high-density livestock area, with an estimated number of cattle on-feed of approximately 1.8 million. We modified an existing stochastic, spatial simulation model to simulate 64 scenarios for planning and decision-making. Our scenarios simulated four different herd types for the index herd (company feedlot, backgrounder feedlot, large beef, backyard) and variations in three mitigation strategies (time-of-detection, vaccine availability, and surveillance during disease control). Under our assumptions about availability of resources to manage an outbreak, median epidemic lengths in the scenarios with commercial feedlot, backgrounder feedlot, large beef and backyard index herd types ranged from 28 to 52, 19 to 39, 18 to 32, and 18 to 36 days, respectively, and the average number of herds depopulated ranged from 4 to 101, 2 to 29, 1 to 15 and 1 to 18, respectively. Early detection of FMD in the index herd had the largest impact on reducing ( approximately 13-21 days) the length of epidemics and the number of herds ( approximately 5-34) depopulated. Although most predicted epidemics lasted only approximately 1-2 months, and <100 herds needed to be depopulated, large outbreaks lasting approximately 8-9 months with up to 230 herds depopulated might occur.

Antibiotic and disinfectant susceptibility profiles of vancomycin-resistant Enterococcus faecium (VRE) isolated from community wastewater in Texas.

Vancomycin-resistant Enterococcus faecium (VRE) from human wastewater effluents in a nonclinical semiclosed agri-food system in Texas were characterized for susceptibility to antibiotics and disinfectants. The 50 VRE were resistant to eight fluoroquinolones and 10 of 17 antimicrobials typically active against Gram-positive organisms. The VRE were susceptible to quinupristin/dalfopristin and linezolid. Lack of the insertion element IS1251 correlated with VRE susceptibility to streptomycin and gentamicin at p < 0.0001 and p = 0.033, respectively. An association was observed between pulsed-field gel electrophoresis genotypes Ic and II and susceptibility to streptomycin at p = 0.0006. VRE susceptibility for nine disinfectants and five disinfectant components is shown. Ninety-two percent of the isolates had a minimum inhibitory concentration (MIC) for triclosan > or =2 ppm. Triclosan MICs for many of the VRE were well over expected product application levels. No association was observed between antibiotic resistance and disinfectant susceptibility in these VRE. Enterococci multiply-resistant to vancomycin and aminoglycosides were found in a non-hospital environment where one would not expect to find them.

The potential role of wild and feral animals as reservoirs of foot-and-mouth disease.

We investigated the potential role of feral pigs and wild deer as FMD reservoirs with a susceptible-latent-infected-recovered geographic-automata model, using spatially referenced data from southern Texas, USA. An uncontrolled FMD outbreak initiated in feral pigs and in wild deer might infect up to 698 (90% prediction interval 181, 1387) and 1557 (823, 2118) cattle and affect an area of 166 km(2) (53, 306) and 455 km(2) (301, 588), respectively. The predicted spread of FMD virus infection was influenced by assumptions we made regarding the number of incursion sites and the number of neighborhood interactions between herds. Our approach explicitly incorporates the spatial relationships between domesticated and non-domesticated animal populations, providing a new framework to explore the impacts, costs, and strategies for the control of foreign animal diseases with a potential wildlife reservoir.

Characteristics of an outbreak of West Nile virus encephalomyelitis in a previously uninfected population of horses.

Equine West Nile virus (WNV) encephalomyelitis cases - based on clinical signs and ELISA serology test results - reported to Texas disease control authorities during 2002 were analyzed to provide insights into the epidemiology of the disease within a previously disease-free population. The epidemic occurred between June 27 and December 17 (peaking in early October) and 1,698 cases were reported. Three distinct epidemic phases were identified, occurring mostly in southeast, northwest and then central Texas. Significant (P<0.05) disease clusters were identified in northwest and northern Texas. Most (91.1%) cases had no recent travel history, and most (68.9%) cases had not been vaccinated within the previous 12 months. One-third of cases did not survive, 71.2% of which were euthanatized. The most commonly reported presenting signs included ataxia (69%), abnormal gait (52%), muscle fasciculations (49%), depression (32%) and recumbency (28%). Vaccination status, ataxia, falling down, recumbency and lip droop best explained the risk of not surviving WNV disease. Results suggest that the peak risk period for encephalomyelitis caused by WNV may vary substantially among regions within Texas. Recumbent horses have a poor prognosis for survival. Vaccines, even if not administered sufficiently in advance of WNV infection within a district, may reduce the risk of death by at least 44%.