Towards a Hybrid Method to Categorize Interruptions and Activities in Healthcare

Objective Interruptions are known to have a negative impact on activity performance. Understanding how an interruption contributes to human error is limited because there is not a standard method for analyzing and classifying interruptions. Qualitative data are typically analyzed by either a deductive or an inductive method. Both methods have limitations. In this paper a hybrid method was developed that integrates deductive and inductive methods for the categorization of activities and interruptions recorded during an ethnographic study of physicians and registered nurses in a Level One Trauma Center. Understanding the effects of interruptions is important for designing and evaluating informatics tools in particular and for improving healthcare quality and patient safety in general. Method The hybrid method was developed using a deductive a priori classification framework with the provision of adding new categories discovered inductively in the data. The inductive process utilized line-by-line coding and constant comparison as stated in Grounded Theory. Results The categories of activities and interruptions were organized into a three-tiered hierarchy of activity. Validity and reliability of the categories were tested by categorizing a medical error case external to the study. No new categories of interruptions were identified during analysis of the medical error case. Conclusions Findings from this study provide evidence that the hybrid model of categorization is more complete than either a deductive or an inductive method alone. The hybrid method developed in this study provides the methodical support for understanding, analyzing, and managing interruptions and workflow.

Towards a hybrid method to categorize interruptions and activities in healthcare.

OBJECTIVE: Interruptions are known to have a negative impact on activity performance. Understanding how an interruption contributes to human error is limited because there is not a standard method for analyzing and classifying interruptions. Qualitative data are typically analyzed by either a deductive or an inductive method. Both methods have limitations. In this paper, a hybrid method was developed that integrates deductive and inductive methods for the categorization of activities and interruptions recorded during an ethnographic study of physicians and registered nurses in a Level One Trauma Center. Understanding the effects of interruptions is important for designing and evaluating informatics tools in particular as well as improving healthcare quality and patient safety in general. METHOD: The hybrid method was developed using a deductive a priori classification framework with the provision of adding new categories discovered inductively in the data. The inductive process utilized line-by-line coding and constant comparison as stated in Grounded Theory. RESULTS: The categories of activities and interruptions were organized into a three-tiered hierarchy of activity. Validity and reliability of the categories were tested by categorizing a medical error case external to the study. No new categories of interruptions were identified during analysis of the medical error case. CONCLUSIONS: Findings from this study provide evidence that the hybrid model of categorization is more complete than either a deductive or an inductive method alone. The hybrid method developed in this study provides the methodical support for understanding, analyzing, and managing interruptions and workflow.

A hybrid method in combining treatment effects from matched and unmatched studies

In the biomedical studies, the general data structures have been the matched (paired) and unmatched designs. Recently, many researchers are interested in Meta-Analysis to obtain a better understanding from several clinical data of a medical treatment. The hybrid design, which is combined two data structures, may create the fundamental question for statistical methods and the challenges for statistical inferences. The applied methods are depending on the underlying distribution. If the outcomes are normally distributed, we would use the classic paired and two independent sample T-tests on the matched and unmatched cases. If not, we can apply Wilcoxon signed rank and rank sum test on each case. ^ To assess an overall treatment effect on a hybrid design, we can apply the inverse variance weight method used in Meta-Analysis. On the nonparametric case, we can use a test statistic which is combined on two Wilcoxon test statistics. However, these two test statistics are not in same scale. We propose the Hybrid Test Statistic based on the Hodges-Lehmann estimates of the treatment effects, which are medians in the same scale.^ To compare the proposed method, we use the classic meta-analysis T-test statistic on the combined the estimates of the treatment effects from two T-test statistics. Theoretically, the efficiency of two unbiased estimators of a parameter is the ratio of their variances. With the concept of Asymptotic Relative Efficiency (ARE) developed by Pitman, we show ARE of the hybrid test statistic relative to classic meta-analysis T-test statistic using the Hodges-Lemann estimators associated with two test statistics.^ From several simulation studies, we calculate the empirical type I error rate and power of the test statistics. The proposed statistic would provide effective tool to evaluate and understand the treatment effect in various public health studies as well as clinical trials.^

UNDERSTANDING INTERRUPTIONS IN HEALTHCARE: DEVELOPING A MODEL

Developing a Model Interruption is a known human factor that contributes to errors and catastrophic events in healthcare as well as other high-risk industries. The landmark Institute of Medicine (IOM) report, To Err is Human, brought attention to the significance of preventable errors in medicine and suggested that interruptions could be a contributing factor. Previous studies of interruptions in healthcare did not offer a conceptual model by which to study interruptions. As a result of the serious consequences of interruptions investigated in other high-risk industries, there is a need to develop a model to describe, understand, explain, and predict interruptions and their consequences in healthcare. Therefore, the purpose of this study was to develop a model grounded in the literature and to use the model to describe and explain interruptions in healthcare. Specifically, this model would be used to describe and explain interruptions occurring in a Level One Trauma Center. A trauma center was chosen because this environment is characterized as intense, unpredictable, and interrupt-driven. The first step in developing the model began with a review of the literature which revealed that the concept interruption did not have a consistent definition in either the healthcare or non-healthcare literature. Walker and Avant’s method of concept analysis was used to clarify and define the concept. The analysis led to the identification of five defining attributes which include (1) a human experience, (2) an intrusion of a secondary, unplanned, and unexpected task, (3) discontinuity, (4) externally or internally initiated, and (5) situated within a context. However, before an interruption could commence, five conditions known as antecedents must occur. For an interruption to take place (1) an intent to interrupt is formed by the initiator, (2) a physical signal must pass a threshold test of detection by the recipient, (3) the sensory system of the recipient is stimulated to respond to the initiator, (4) an interruption task is presented to recipient, and (5) the interruption task is either accepted or rejected by v the recipient. An interruption was determined to be quantifiable by (1) the frequency of occurrence of an interruption, (2) the number of times the primary task has been suspended to perform an interrupting task, (3) the length of time the primary task has been suspended, and (4) the frequency of returning to the primary task or not returning to the primary task. As a result of the concept analysis, a definition of an interruption was derived from the literature. An interruption is defined as a break in the performance of a human activity initiated internal or external to the recipient and occurring within the context of a setting or location. This break results in the suspension of the initial task by initiating the performance of an unplanned task with the assumption that the initial task will be resumed. The definition is inclusive of all the defining attributes of an interruption. This is a standard definition that can be used by the healthcare industry. From the definition, a visual model of an interruption was developed. The model was used to describe and explain the interruptions recorded for an instrumental case study of physicians and registered nurses (RNs) working in a Level One Trauma Center. Five physicians were observed for a total of 29 hours, 31 minutes. Eight registered nurses were observed for a total of 40 hours 9 minutes. Observations were made on either the 0700–1500 or the 1500-2300 shift using the shadowing technique. Observations were recorded in the field note format. The field notes were analyzed by a hybrid method of categorizing activities and interruptions. The method was developed by using both a deductive a priori classification framework and by the inductive process utilizing line-byline coding and constant comparison as stated in Grounded Theory. The following categories were identified as relative to this study: Intended Recipient - the person to be interrupted Unintended Recipient - not the intended recipient of an interruption; i.e., receiving a phone call that was incorrectly dialed Indirect Recipient – the incidental recipient of an interruption; i.e., talking with another, thereby suspending the original activity Recipient Blocked – the intended recipient does not accept the interruption Recipient Delayed – the intended recipient postpones an interruption Self-interruption – a person, independent of another person, suspends one activity to perform another; i.e., while walking, stops abruptly and talks to another person Distraction – briefly disengaging from a task Organizational Design – the physical layout of the workspace that causes a disruption in workflow Artifacts Not Available – supplies and equipment that are not available in the workspace causing a disruption in workflow Initiator – a person who initiates an interruption Interruption by Organizational Design and Artifacts Not Available were identified as two new categories of interruption. These categories had not previously been cited in the literature. Analysis of the observations indicated that physicians were found to perform slightly fewer activities per hour when compared to RNs. This variance may be attributed to differing roles and responsibilities. Physicians were found to have more activities interrupted when compared to RNs. However, RNs experienced more interruptions per hour. Other people were determined to be the most commonly used medium through which to deliver an interruption. Additional mediums used to deliver an interruption vii included the telephone, pager, and one’s self. Both physicians and RNs were observed to resume an original interrupted activity more often than not. In most interruptions, both physicians and RNs performed only one or two interrupting activities before returning to the original interrupted activity. In conclusion the model was found to explain all interruptions observed during the study. However, the model will require an even more comprehensive study in order to establish its predictive value.

The identification and regulation of a novel interaction occurring between $\beta$-catenin and the actin -bundling protein fascin

Catenins were first characterized as linking the cytoplasmic domains of cadherin cell-cell adhesion molecules to the cortical actin cytoskeleton. In addition to their essential role in modulating cadherin adhesion, catenins have more recently been indicated to participate in cell and developmental signaling pathways. $\beta$-catenin, for example, associates directly with receptor tyrosine kinases and transcription factors such as LEF-1/TCF, and tranduces developmental signals within the Wnt pathway. $\beta$-catenin also appear to a role in regulating cell proliferation via its interaction with the tumor supressor protein APC. I have employed the yeast two-hybrid method to reveal that fascin, a bundler of actin filaments, binds to $\beta$-catenin's central Armadillo-repeat domain. The $\beta$-catenin-fascin interaction exists in cell lines as well as in animal brain tissues as revealed by immunoprecipitation analysis, and substantiated in vitro with purified proteins. Fascin additionally binds to plakoglobin, which contains a more divergent Armadillo-repeat domain. Fascin and E-cadherin utilize a similar binding-site within $\beta$-catenin, such that they form mutually exclusive complexes with $\beta$-catenin. Fascin and $\beta$-catenin co-localize at cell-cell borders and dynamic cell leading edges of epithelial and endothelial cells. Total immunoprecipitable b-catein has several isoforms, only the hyperphosphorylated isoform 1 associated with fascin. An increased $\beta$-catenin-fascin interaction was observed in HGF stimulated cells, and in Xenopus embryos injected with src kinase RNAs. The increased $\beta$-catenin association with fascin is correlated with increased levels of $\beta$-catenin phosphorylation. $\beta$-catenin, but not fascin, can be readily phosphorylated on tyrosine in vivo following src injection of embryos, or in vitro following v-src addition to purified protein components. These observations suggest a role of $\beta$-catenin phosphorylation in regulating its interaction with fascin, and src kinase may be an important regulator of the $\beta$-catenin-fascin association in vivo. The $\beta$-catenin-fascin interaction represents a novel catenin complex, that may conceivably regulate actin cytoskeletal structures, cell adhesion, and cellular motility, perhaps in a coordinate manner with its functions in cadherin and APC complexes. ^

Regulations of SOX9 activity during chondrogenesis

Sox9 is a transcription factor required for chondrocyte differentiation and cartilage formation. In an effort to identify SOX9 interacting protein(s), we screened a chondrocyte cDNA library with a modified yeast two-hybrid method, Son of Sevenless (SOS) recruitment system (SRS). The catalytic subunit of cyclic AMP-dependent protein kinase A (PKA-Cα) and a new long form of c-Maf transcription factor (Lc-Maf) were found to interact specifically with SOX9. We showed here that two PKA phosphorylation consensus sites of SOX9 could be phosphorylated by PKA in vitro as well as in vivo. PKA phosphorylation of SOX9 increases its DNA binding and transcriptional activities on a Col2a1 chondrocyte-specific enhancer. Mutations of these two PKA phosphorylation sites markedly decreased the activation of SOX9 by PKA. ^ To test whether parathyroid hormone-related peptide (PTHrP) signaling results in SOX9 phosphorylation, we generated a phosphospecific antibody that specifically recognizes SOX9 that is phosphorylated at serine 181 (S 181) one of the two consensus PKA phosphorylation sites. Addition of PTHrP to COS7 cells cotransfected with SOX9 and PTH/PTHrP receptor strongly increased phosphorylation of SOX9 at S181; this phosphorylation was blocked by a PKA-specific inhibitor. In similar experiments we showed that PTHrP increased the activity of a SOX9-dependent Col2a1 enhancer. This increase in activity was abolished when a SOX9 mutant was used containing serine-to-alanine substitution in the two consensus PKA phosphorylation sites of SOX9. Using our phosphospecific SOX9 antibody we showed by immunohistochemistry of mouse embryos that Sox9 phosphorylated at S181 was localized almost exclusively in the pre-hypertrophic zone of the growth plate, an area corresponding to the major site of expression of PTH/PTHrP receptor. In contrast, no phosphorylation of Sox9 at S181 was detected in growth plates of PTH/PTHrP receptor null mutant mice. Sox9, regardless of phosphorylation state, was present in all chondrocytes of both genotypes except in hypertrophic chondrocytes. Thus, Sox9 is a target of PTHrP signaling and the PTHrP-dependent phosphorylation of SOX9 enhances its transcriptional activity. ^ In order to investigate the in vivo function of Sox9 phosphorylation by PKA, we are generating a mouse model of mutant Sox9 harboring point mutations in two PKA phosphorylation sites. Preliminary results indicated that heterozygous mice containing half amount of mutant Sox9 that can not be phosphorylated by PKA have normal skeletal phenotype and homozygous mice are being generated. ^ Lc-Maf encodes an extra ten amino acids at the carboxyl terminus of c-Maf and contains a completely different 3′ untranslated region. The interaction between SOX9 and Lc-Maf was further confirmed by co-immunoprecipitation and GST-pull down assays, which mapped the interacting domains of SOX9 to HMG DNA binding domain and that of Lc-Maf to basic leusine zipper motif. In situ hybridizations showed that RNA of Lc-Maf coexpressed with those of Sox9 and Col2a1 in areas of mesenchymal condensation during the early stages of mouse embryo development. A DNA binding site of Lc-Maf was identified at the 5′ part of a 48-bp Col2a1 enhancer element near the HMG binding site of SOX9. Lc-Maf and SOX9 synergistically activated a luciferase reporter plasmid containing a Col2al enhancer and increased the transcription of endogenous Col2a1 gene. In summary, Lc-Maf is the first identified SOX9-interating protein during chondrogenesis and may be an important activator of Col2a1 gene. ^

Hybrid stochastic simulations of intracellular reaction-diffusion systems.

With the observation that stochasticity is important in biological systems, chemical kinetics have begun to receive wider interest. While the use of Monte Carlo discrete event simulations most accurately capture the variability of molecular species, they become computationally costly for complex reaction-diffusion systems with large populations of molecules. On the other hand, continuous time models are computationally efficient but they fail to capture any variability in the molecular species. In this study a hybrid stochastic approach is introduced for simulating reaction-diffusion systems. We developed an adaptive partitioning strategy in which processes with high frequency are simulated with deterministic rate-based equations, and those with low frequency using the exact stochastic algorithm of Gillespie. Therefore the stochastic behavior of cellular pathways is preserved while being able to apply it to large populations of molecules. We describe our method and demonstrate its accuracy and efficiency compared with the Gillespie algorithm for two different systems. First, a model of intracellular viral kinetics with two steady states and second, a compartmental model of the postsynaptic spine head for studying the dynamics of Ca+2 and NMDA receptors.

A simulation study using the hybrid statistic and the meta-analysis t-test for data with matched and unmatched subjects in the interim analysis of clinical trials

An interim analysis is usually applied in later phase II or phase III trials to find convincing evidence of a significant treatment difference that may lead to trial termination at an earlier point than planned at the beginning. This can result in the saving of patient resources and shortening of drug development and approval time. In addition, ethics and economics are also the reasons to stop a trial earlier. In clinical trials of eyes, ears, knees, arms, kidneys, lungs, and other clustered treatments, data may include distribution-free random variables with matched and unmatched subjects in one study. It is important to properly include both subjects in the interim and the final analyses so that the maximum efficiency of statistical and clinical inferences can be obtained at different stages of the trials. So far, no publication has applied a statistical method for distribution-free data with matched and unmatched subjects in the interim analysis of clinical trials. In this simulation study, the hybrid statistic was used to estimate the empirical powers and the empirical type I errors among the simulated datasets with different sample sizes, different effect sizes, different correlation coefficients for matched pairs, and different data distributions, respectively, in the interim and final analysis with 4 different group sequential methods. Empirical powers and empirical type I errors were also compared to those estimated by using the meta-analysis t-test among the same simulated datasets. Results from this simulation study show that, compared to the meta-analysis t-test commonly used for data with normally distributed observations, the hybrid statistic has a greater power for data observed from normally, log-normally, and multinomially distributed random variables with matched and unmatched subjects and with outliers. Powers rose with the increase in sample size, effect size, and correlation coefficient for the matched pairs. In addition, lower type I errors were observed estimated by using the hybrid statistic, which indicates that this test is also conservative for data with outliers in the interim analysis of clinical trials.^