A Time-Motion Study of Registered Nurses’ Workflow in Intensive Care Unit Remote Monitoring

Utilizing advanced information technology, Intensive Care Unit (ICU) remote monitoring allows highly trained specialists to oversee a large number of patients at multiple sites on a continuous basis. In the current research, we conducted a time-motion study of registered nurses’ work in an ICU remote monitoring facility. Data were collected on seven nurses through 40 hours of observation. The results showed that nurses’ essential tasks were centered on three themes: monitoring patients, maintaining patients’ health records, and managing technology use. In monitoring patients, nurses spent 52% of the time assimilating information embedded in a clinical information system and 15% on monitoring live vitals. System-generated alerts frequently interrupted nurses in their task performance and redirected them to manage suddenly appearing events. These findings provide insight into nurses’ workflow in a new, technology-driven critical care setting and have important implications for system design, work engineering, and personnel selection and training.

Implementation of active surveillance cultures and associated infection control practices for the reduction of methicillin resistant Staphylococcus aureus in the healthcare setting: An interrupted time series analysis

OBJECTIVE. To determine the effectiveness of active surveillance cultures and associated infection control practices on the incidence of methicillin resistant Staphylococcus aureus (MRSA) in the acute care setting. DESIGN. A historical analysis of existing clinical data utilizing an interrupted time series design. ^ SETTING AND PARTICIPANTS. Patients admitted to a 260-bed tertiary care facility in Houston, TX between January 2005 through December 2010. ^ INTERVENTION. Infection control practices, including enhanced barrier precautions, compulsive hand hygiene, disinfection and environmental cleaning, and executive ownership and education, were simultaneously introduced during a 5-month intervention implementation period culminating with the implementation of active surveillance screening. Beginning June 2007, all high risk patients were cultured for MRSA nasal carriage within 48 hours of admission. Segmented Poisson regression was used to test the significance of the difference in incidence of healthcare-associated MRSA during the 29-month pre-intervention period compared to the 43-month post-intervention period. ^ RESULTS. A total of 9,957 of 11,095 high-risk patients (89.7%) were screened for MRSA carriage during the intervention period. Active surveillance cultures identified 1,330 MRSA-positive patients (13.4%) contributing to an admission prevalence of 17.5% in high-risk patients. The mean rate of healthcare-associated MRSA infection and colonization decreased from 1.1 per 1,000 patient-days in the pre-intervention period to 0.36 per 1,000 patient-days in the post-intervention period (P<0.001). The effect of the intervention in association with the percentage of S. aureus isolates susceptible to oxicillin were shown to be statistically significantly associated with the incidence of MRSA infection and colonization (IRR = 0.50, 95% CI = 0.31-0.80 and IRR = 0.004, 95% CI = 0.00003-0.40, respectively). ^ CONCLUSIONS. It can be concluded that aggressively targeting patients at high risk for colonization of MRSA with active surveillance cultures and associated infection control practices as part of a multifaceted, hospital-wide intervention is effective in reducing the incidence of healthcare-associated MRSA.^

TIME SERIES ANALYSIS AS INPUT FOR PREDICTIVE MODELING: PREDICTING CARDIAC ARREST IN A PEDIATRIC INTENSIVE CARE UNIT

The first manuscript, entitled "Time-Series Analysis as Input for Clinical Predictive Modeling: Modeling Cardiac Arrest in a Pediatric ICU" lays out the theoretical background for the project. There are several core concepts presented in this paper. First, traditional multivariate models (where each variable is represented by only one value) provide single point-in-time snapshots of patient status: they are incapable of characterizing deterioration. Since deterioration is consistently identified as a precursor to cardiac arrests, we maintain that the traditional multivariate paradigm is insufficient for predicting arrests. We identify time series analysis as a method capable of characterizing deterioration in an objective, mathematical fashion, and describe how to build a general foundation for predictive modeling using time series analysis results as latent variables. Building a solid foundation for any given modeling task involves addressing a number of issues during the design phase. These include selecting the proper candidate features on which to base the model, and selecting the most appropriate tool to measure them. We also identified several unique design issues that are introduced when time series data elements are added to the set of candidate features. One such issue is in defining the duration and resolution of time series elements required to sufficiently characterize the time series phenomena being considered as candidate features for the predictive model. Once the duration and resolution are established, there must also be explicit mathematical or statistical operations that produce the time series analysis result to be used as a latent candidate feature. In synthesizing the comprehensive framework for building a predictive model based on time series data elements, we identified at least four classes of data that can be used in the model design. The first two classes are shared with traditional multivariate models: multivariate data and clinical latent features. Multivariate data is represented by the standard one value per variable paradigm and is widely employed in a host of clinical models and tools. These are often represented by a number present in a given cell of a table. Clinical latent features derived, rather than directly measured, data elements that more accurately represent a particular clinical phenomenon than any of the directly measured data elements in isolation. The second two classes are unique to the time series data elements. The first of these is the raw data elements. These are represented by multiple values per variable, and constitute the measured observations that are typically available to end users when they review time series data. These are often represented as dots on a graph. The final class of data results from performing time series analysis. This class of data represents the fundamental concept on which our hypothesis is based. The specific statistical or mathematical operations are up to the modeler to determine, but we generally recommend that a variety of analyses be performed in order to maximize the likelihood that a representation of the time series data elements is produced that is able to distinguish between two or more classes of outcomes. The second manuscript, entitled "Building Clinical Prediction Models Using Time Series Data: Modeling Cardiac Arrest in a Pediatric ICU" provides a detailed description, start to finish, of the methods required to prepare the data, build, and validate a predictive model that uses the time series data elements determined in the first paper. One of the fundamental tenets of the second paper is that manual implementations of time series based models are unfeasible due to the relatively large number of data elements and the complexity of preprocessing that must occur before data can be presented to the model. Each of the seventeen steps is analyzed from the perspective of how it may be automated, when necessary. We identify the general objectives and available strategies of each of the steps, and we present our rationale for choosing a specific strategy for each step in the case of predicting cardiac arrest in a pediatric intensive care unit. Another issue brought to light by the second paper is that the individual steps required to use time series data for predictive modeling are more numerous and more complex than those used for modeling with traditional multivariate data. Even after complexities attributable to the design phase (addressed in our first paper) have been accounted for, the management and manipulation of the time series elements (the preprocessing steps in particular) are issues that are not present in a traditional multivariate modeling paradigm. In our methods, we present the issues that arise from the time series data elements: defining a reference time; imputing and reducing time series data in order to conform to a predefined structure that was specified during the design phase; and normalizing variable families rather than individual variable instances. The final manuscript, entitled: "Using Time-Series Analysis to Predict Cardiac Arrest in a Pediatric Intensive Care Unit" presents the results that were obtained by applying the theoretical construct and its associated methods (detailed in the first two papers) to the case of cardiac arrest prediction in a pediatric intensive care unit. Our results showed that utilizing the trend analysis from the time series data elements reduced the number of classification errors by 73%. The area under the Receiver Operating Characteristic curve increased from a baseline of 87% to 98% by including the trend analysis. In addition to the performance measures, we were also able to demonstrate that adding raw time series data elements without their associated trend analyses improved classification accuracy as compared to the baseline multivariate model, but diminished classification accuracy as compared to when just the trend analysis features were added (ie, without adding the raw time series data elements). We believe this phenomenon was largely attributable to overfitting, which is known to increase as the ratio of candidate features to class examples rises. Furthermore, although we employed several feature reduction strategies to counteract the overfitting problem, they failed to improve the performance beyond that which was achieved by exclusion of the raw time series elements. Finally, our data demonstrated that pulse oximetry and systolic blood pressure readings tend to start diminishing about 10-20 minutes before an arrest, whereas heart rates tend to diminish rapidly less than 5 minutes before an arrest.

A space-time analysis of reported shigellosis and salmonellosis cases in Texas from 2000 to 2004

Background. The purpose of this study was to describe the risk factors and demographics of persons with salmonellosis and shigellosis and to investigate both seasonal and spatial variations in the occurrence of these infections in Texas from 2000 to 2004, utilizing time series analyses and the geographic information system digital mapping methods. ^ Methods. Spatial Analysis: MapInfo software was used to map the distribution of age-adjusted rates of reported shigellosis and salmonellosis in Texas from 2000–2004 by zip codes. Census data on above or below poverty level, household income, highest level of educational attainment, race, ethnicity, and urban/rural community status was obtained from the 2000 Decennial Census for each zip code. The zip codes with the upper 10% and lower 10% were compared using t-tests and logistic regression to determine whether there were any potential risk factors. ^ Temporal analysis. Seasonal patterns in the prevalence of infections in Texas from 2000 to 2003 were determined by performing time-series analysis on the numbers of cases of salmonellosis and shigellosis. A linear regression was also performed to assess for trends in the incidence of each disease, along with auto-correlation and multi-component cosinor analysis. ^ Results. Spatial analysis: Analysis by general linear model showed a significant association between infection rates and age, with young children aged less than 5 and those aged 5–9 years having increased risk of infection for both disease conditions. The data demonstrated that those populations with high percentages of people who attained a higher than high school education were less likely to be represented in zip codes with high rates of shigellosis. However, for salmonellosis, logistic regression models indicated that when compared to populations with high percentages of non-high school graduates, having a high school diploma or equivalent increased the odds of having a high rate of infection. ^ Temporal analysis. For shigellosis, multi-component cosinor analyses were used to determine the approximated cosine curve which represented a statistically significant representation of the time series data for all age groups by sex. The shigellosis results show 2 peaks, with a major peak occurring in June and a secondary peak appearing around October. Salmonellosis results showed a single peak and trough in all age groups with the peak occurring in August and the trough occurring in February. ^ Conclusion. The results from this study can be used by public health agencies to determine the timing of public health awareness programs and interventions in order to prevent salmonellosis and shigellosis from occurring. Because young children depend on adults for their meals, it is important to increase the awareness of day-care workers and new parents about modes of transmission and hygienic methods of food preparation and storage. ^

Cost analysis of opt-in consent procedures for the Texas statewide immunization information system, ImmTrac

Background. Childhood immunization programs have dramatically reduced the morbidity and mortality associated with vaccine-preventable diseases. Proper documentation of immunizations that have been administered is essential to prevent duplicate immunization of children. To help improve documentation, immunization information systems (IISs) have been developed. IISs are comprehensive repositories of immunization information for children residing within a geographic region. The two models for participation in an IIS are voluntary inclusion, or "opt-in," and voluntary exclusion, or "opt-out." In an opt-in system, consent must be obtained for each participant, conversely, in an opt-out IIS, all children are included unless procedures to exclude the child are completed. Consent requirements for participation vary by state; the Texas IIS, ImmTrac, is an opt-in system.^ Objectives. The specific objectives are to: (1) Evaluate the variance among the time and costs associated with collecting ImmTrac consent at public and private birthing hospitals in the Greater Houston area; (2) Estimate the total costs associated with collecting ImmTrac consent at selected public and private birthing hospitals in the Greater Houston area; (3) Describe the alternative opt-out process for collecting ImmTrac consent at birth and discuss the associated cost savings relative to an opt-in system.^ Methods. Existing time-motion studies (n=281) conducted between October, 2006 and August, 2007 at 8 birthing hospitals in the Greater Houston area were used to assess the time and costs associated with obtaining ImmTrac consent at birth. All data analyzed are deidentified and contain no personal information. Variations in time and costs at each location were assessed and total costs per child and costs per year were estimated. The cost of an alternative opt-out system was also calculated.^ Results. The median time required by birth registrars to complete consent procedures varied from 72-285 seconds per child. The annual costs associated with obtaining consent for 388,285 newborns in ImmTrac's opt-in consent process were estimated at $702,000. The corresponding costs of the proposed opt-out system were estimated to total $194,000 per year. ^ Conclusions. Substantial variation in the time and costs associated with completion of ImmTrac consent procedures were observed. Changing to an opt-out system for participation could represent significant cost savings. ^

Phototaxis signaling by the membrane complex of archaeal sensory rhodopsins and their transducers

Sensory rhodopsins I and II (SRI and SRII) are visual pigment-like phototaxis receptors in the archaeon Halobacterium salinarum. The receptor proteins each consist of a single polypeptide that folds into 7 $\alpha$-helical membrane-spanning segments forming an internal pocket where the chromophore retinal is bound. They transmit signals to their tightly bound transducer proteins, HtrI and HtrII, respectively, which in turn control a phosphotransfer pathway modulating the flagellar motors. SRI-HtrI mediates attractant responses to orange-light and repellent responses to UV light, while SRII-HtrII mediates repellent response to blue light. Experiments were designed to analyze the molecular processes in the SR-Htr complexes responsible for receptor activation, which previously had been shown by our laboratory to involve proton transfer reactions of the retinylidene Schiff base in the photoactive site, transfer of signals from receptor to transducer, and signaling specificity by the receptor-transducer complex.^ Site-directed mutagenesis and laser-flash kinetic spectroscopy revealed that His-166 in SRI (i) plays a role in the proton transfers both to and from the Schiffbase, either as a structurally critical residue or possibly as a direct participant, (ii) is involved in the modulation of SIU photoreaction kinetics by HtrI, and (iii) modulates the pKa of Asp-76, an important residue in the photoactive site, through a long-distance electrostatic interaction. Computerized cell tracking and motion analysis demonstrated that (iv) His-166 is crucial in phototaxis signaling: a spectrum of substitutions either eliminate signaling or greatly perturb the activation process that produces attractant and repellent signaling states of the receptor.^ The signaling states of SRI are communicated to HtrI, whose oligomeric structure and conformational changes were investigated by engineered sulfhydryl probes. It was found that signaling by the SRI-HtrI complex involves reversible conformational changes within a preexisting HtrI dimer, which is likely accomplished through a slight winding or unwinding of the two HtrT monomers via their loose coiled coil association. To elucidate which domains of the Htr dimers confer specificity for interaction with SRI or SRII, chimeras of HtrI and HtrII were constructed. The only determinant needed for functional and specific interaction with SRI or SRII was found to be the four transmembrane segments of the HtrI or HtrII dimers, respectively. The entire cytoplasmic parts of HtrI and HtrII, which include the functionally important signaling and adaptation domains, were interchangeable.^ These observations support a model in which SRI and SRII undergo conformational changes coupled to light-induced proton transfers in their photoactive sites, and that lateral helix-helix interactions with their cognate transducers' 4-helix bundle in the membrane relay these conformational changes into different states of the Htr proteins which regulate the down-stream phosphotransfer pathway. ^

STUDIES OF THE MOLECULAR MECHANISMS OF CHROMOSOME ABERRATION FORMATION (DNA REPAIR, CROSSLINKS, MITOMYCIN C)

The objective of this research has been to study the molecular basis for chromosome aberration formation. Predicated on a variety of data, Mitomycin C (MMC)-induced DNA damage has been postulated to cause the formation of chromatid breaks (and gaps) by preventing the replication of regions of the genome prior to mitosis. The basic protocol for these experiments involved treating synchronized Hela cells in G(,1)-phase with a 1 (mu)g/ml dose of MMC for one hour. After removing the drug, cells were then allowed to progress to mitosis and were harvested for analysis by selective detachment. Utilizing the alkaline elution assay for DNA damage, evidence was obtained to support the conclusion that Hela cells can progress through S-phase into mitosis with intact DNA-DNA interstrand crosslinks. A higher level of crosslinking was observed in those cells remaining in interphase compared to those able to reach mitosis at the time of analysis. Dual radioisotope labeling experiments revealed that, at this dose, these crosslinks were associated to the same extent with both parental and newly replicated DNA. This finding was shown not to be the result of a two-step crosslink formation mechanism in which crosslink levels increase with time after drug treatment. It was also shown not to be an artefact of the double-labeling protocol. Using neutral CsCl density gradient ultracentrifugation of mitotic cells containing BrdU-labeled newly replicated DNA, control cells exhibited one major peak at a heavy/light density. However, MMC-treated cells had this same major peak at the heavy/light density, in addition to another minor peak at a density characteristic for light/light DNA. This was interpreted as indicating either: (1) that some parental DNA had not been replicated in the MMC treated sample or; (2) that a recombination repair mechanism was operational. To distinguish between these two possibilities, flow cytometric DNA fluorescence (i.e., DNA content) measurements of MMC-treated and control cells were made. These studies revealed that the mitotic cells that had been treated with MMC while in G(,1)-phase displayed a 10-20% lower DNA content than untreated control cells when measured under conditions that neutralize chromosome condensation effects (i.e., hypotonic treatment). These measurements were made under conditions in which the binding of the drug, MMC, was shown not to interfere with the stoichiometry of the ethidium bromide-mithramycin stain. At the chromosome level, differential staining techniques were used in an attempt to visualize unreplicated regions of the genome, but staining indicative of large unreplicated regions was not observed. These results are best explained by a recombinogenic mechanism. A model consistent with these results has been proposed.^

Transcriptional regulation of lung tumor suppressor GPRC5A in malignant and normal cells

Chronic exposure of the airways to cigarette smoke induces inflammatory response and genomic instability that play important roles in lung cancer development. Nuclear factor kappa B (NF-κB), the major intracellular mediator of inflammatory signals, is frequently activated in preneoplastic and malignant lung lesions. ^ Previously, we had shown that a lung tumor suppressor GPRC5A is frequently repressed in human non-small cell lung cancers (NSCLC) cells and lung tumor specimens. Recently, other groups have shown that human GPRC5A transcript levels are higher in bronchial samples of former than of current smokers. These results suggested that smoking represses GPRC5A expression and thus promotes the occurrence of lung cancer. We hypothesized that cigarette smoking or associated inflammatory response repressed GPRC5A expression through NF-κB signaling. ^ To determine the effect of inflammation, we examined GPRC5A protein expression in several lung cell lines following by TNF-α treatment. TNF-α significantly suppressed GPRC5A expression in normal small airway epithelial cells (SAEC) as well as in Calu-1 cells. Real-time PCR analysis indicated that TNF-α inhibits GPRC5A expression at the transcriptional level. NF-κB, the major downstream effectors of TNF-α signaling, mediates TNF-α-induced repression of GPRC5A because over-expression of NF-κB suppressed GPRC5A. To determine the region in the GPRC5A promoter through which NF-κB acts, we examined the ability of TNF-α to inhibit a series of reporter constructs with different deletions of GPRC5A promoter. The luciferase assay showed that the potential NF-κB binding sites containing region are irresponsible for TNF-α-induced suppression. Further analysis using constructs with different deletions in p65 revealed that NF-κB-mediated repression of GPRC5A is transcription-independent. Co-immunoprecipitation assays revealed that NF-κB could form a complex with RAR/RXR heterodimer. Moreover, the inhibitory effect of NF-κB has been found to be proportional to NF-κB/RAR ratio in luciferase assay. Finally, Chromatin IP demonstrated that NF-κB/p65 bound to GPRC5A promoter as well as RAR/RXR and suppressed transcription. Taken together, we propose that inflammation-induced NF-κB activation disrupts the RA signaling and suppresses GPRC5A expression and thus contributes to the oncogenesis of lung cancer. Our studies shed new light on the pathogenesis of lung cancer and potentially provide novel interventions for preventing and treating this disease. ^