Patient classification system: An integrated method for measuring nursing intensity and optimizing resource allocation

A patient classification system was developed integrating a patient acuity instrument with a computerized nursing distribution method based on a linear programming model. The system was designed for real-time measurement of patient acuity (workload) and allocation of nursing personnel to optimize the utilization of resources.^ The acuity instrument was a prototype tool with eight categories of patients defined by patient severity and nursing intensity parameters. From this tool, the demand for nursing care was defined in patient points with one point equal to one hour of RN time. Validity and reliability of the instrument was determined as follows: (1) Content validity by a panel of expert nurses; (2) predictive validity through a paired t-test analysis of preshift and postshift categorization of patients; (3) initial reliability by a one month pilot of the instrument in a practice setting; and (4) interrater reliability by the Kappa statistic.^ The nursing distribution system was a linear programming model using a branch and bound technique for obtaining integer solutions. The objective function was to minimize the total number of nursing personnel used by optimally assigning the staff to meet the acuity needs of the units. A penalty weight was used as a coefficient of the objective function variables to define priorities for allocation of staff.^ The demand constraints were requirements to meet the total acuity points needed for each unit and to have a minimum number of RNs on each unit. Supply constraints were: (1) total availability of each type of staff and the value of that staff member (value was determined relative to that type of staff's ability to perform the job function of an RN (i.e., value for eight hours RN = 8 points, LVN = 6 points); (2) number of personnel available for floating between units.^ The capability of the model to assign staff quantitatively and qualitatively equal to the manual method was established by a thirty day comparison. Sensitivity testing demonstrated appropriate adjustment of the optimal solution to changes in penalty coefficients in the objective function and to acuity totals in the demand constraints.^ Further investigation of the model documented: correct adjustment of assignments in response to staff value changes; and cost minimization by an addition of a dollar coefficient to the objective function. ^

An analysis of two methods for the classification of stage of readiness to obtain repeat mammography screening

Background and purpose: Breast cancer continues to be a health problem for women, representing 28 percent of all female cancers and remaining one of the leading causes of death for women. Breast cancer incidence rates become substantial before the age of 50. After menopause, breast cancer incidence rates continue to increase with age creating a long-lasting source of concern (Harris et al., 1992). Mammography, a technique for the detection of breast tumors in their nonpalpable stage when they are most curable, has taken on considerable importance as a public health measure. The lifetime risk of breast cancer is approximately 1 in 9 and occurs over many decades. Recommendations are that screening be periodic in order to detect cancer at early stages. These recommendations, largely, are not followed. Not only are most women not getting regular mammograms, but this circumstance is particularly the case among older women where regular mammography has been proven to reduce mortality by approximately 30 percent. The purpose of this project was to increase our understanding of factors that are associated with stage of readiness to obtain subsequent mammograms. A secondary purpose of this research was to suggest further conceptual considerations toward the extension of the Transtheoretical Model (TTM) of behavior change to repeat screening mammography. ^ Methods. A sample (n = 1,222) of women 50 years and older in a large multi-specialty clinic in Houston, Texas was surveyed by mail questionnaire regarding their previous screening experience and stage of readiness to obtain repeat screening. A computerized database, maintained on all women who undergo mammography at the clinic, was used to identify women who are eligible for the project. The major statistical technique employed to select the significant variables and to examine the man and interaction effects of independent variables on dependent variables was polychotomous stepwise, logistic regression. A prediction model for each stage of readiness definition was estimated. The expected probabilities for stage of readiness were calculated to assess the magnitude and direction of significant predictors. ^ Results. Analysis showed that both ways of defining stage of readiness for obtaining a screening mammogram were associated with specific constructs, including decisional balance and processes of the change. ^ Conclusions. The results of the present study demonstrate that the TTM appears to translate to repeat mammography screening. Findings in the current study also support finding of previous studies that suggest that stage of readiness is associated with respondent decisional balance and the processes of change. ^

A survey of the implementation status of environmental management systems in U.S. colleges and universities, and, An environmental management system implementation model for U.S. colleges and universities

A census of 925 U.S. colleges and universities offering masters and doctorate degrees was conducted in order to study the number of elements of an environmental management system as defined by ISO 14001 possessed by small, medium and large institutions. A 30% response rate was received with 273 responses included in the final data analysis. Overall, the number of ISO 14001 elements implemented among the 273 institutions ranged from 0 to 16, with a median of 12. There was no significant association between the number of elements implemented among institutions and the size of the institution (p = 0.18; Kruskal-Wallis test) or among USEPA regions (p = 0.12; Kruskal-Wallis test). The proportion of U.S. colleges and universities that reported having implemented a structured, comprehensive environmental management system, defined by answering yes to all 16 elements, was 10% (95% C.I. 6.6%–14.1%); however 38% (95% C.I. 32.0%–43.8%) reported that they had implemented a structured, comprehensive environmental management system, while 30.0% (95% C.I. 24.7%–35.9%) are planning to implement a comprehensive environmental management system within the next five years. Stratified analyses were performed by institution size, Carnegie Classification and job title. ^ The Osnabruck model, and another under development by the South Carolina Sustainable Universities Initiative, are the only two environmental management system models that have been proposed specifically for colleges and universities, although several guides are now available. The Environmental Management System Implementation Model for U.S. Colleges and Universities developed is an adaptation of the ISO 14001 standard and USEPA recommendations and has been tailored to U.S. colleges and universities for use in streamlining the implementation process. In using this implementation model created for the U.S. research and academic setting, it is hoped that these highly specialized institutions will be provided with a clearer and more cost-effective path towards the implementation of an EMS and greater compliance with local, state and federal environmental legislation. ^

Metastatic lung cancer in a new mouse model inheriting p53 and latent K-ras mutations

Lung cancer is a devastating disease with very poor prognosis. The design of better treatments for patients would be greatly aided by mouse models that closely resemble the human disease. The most common type of human lung cancer is adenocarcinoma with frequent metastasis. Unfortunately, current models for this tumor are inadequate due to the absence of metastasis. Based on the molecular findings in human lung cancer and metastatic potential of osteosarcomas in mutant p53 mouse models, I hypothesized that mice with both K-ras and p53 missense mutations might develop metastatic lung adenocarcinomas. Therefore, I incorporated both K-rasLA1 and p53RI72HΔg alleles into mouse lung cells to establish a more faithful model for human lung adenocarcinoma and for translational and mechanistic studies. Mice with both mutations ( K-rasLA1/+ p53R172HΔg/+) developed advanced lung adenocarcinomas with similar histopathology to human tumors. These lung adenocarcinomas were highly aggressive and metastasized to multiple intrathoracic and extrathoracic sites in a pattern similar to that seen in lung cancer patients. This mouse model also showed gender differences in cancer related death and developed pleural mesotheliomas in 23.2% of them. In a preclinical study, the new drug Erlotinib (Tarceva) decreased the number and size of lung lesions in this model. These data demonstrate that this mouse model most closely mimics human metastatic lung adenocarcinoma and provides an invaluable system for translational studies. ^ To screen for important genes for metastasis, gene expression profiles of primary lung adenocarcinomas and metastases were analyzed. Microarray data showed that these two groups were segregated in gene expression and had 79 highly differentially expressed genes (more than 2.5 fold changes and p<0.001). Microarray data of Bub1b, Vimentin and CCAM1 were validated in tumors by quantitative real-time PCR (QPCR). Bub1b , a mitotic checkpoint gene, was overexpressed in metastases and this correlated with more chromosomal abnormalities in metastatic cells. Vimentin, a marker of epithelial-mesenchymal transition (EMT), was also highly expressed in metastases. Interestingly, Twist, a key EMT inducer, was also highly upregulated in metastases by QPCR, and this significantly correlated with the overexpression of Vimentin in the same tumors. These data suggest EMT occurs in lung adenocarcinomas and is a key mechanism for the development of metastasis in K-ras LA1/+ p53R172HΔg/+ mice. Thus, this mouse model provides a unique system to further probe the molecular basis of metastatic lung cancer.^

Colorectal cancer screening: Racial/ethnic and gender disparities in a population-based cross-sectional analysis of the United States

Gender and racial/ethnic disparities in colorectal cancer screening (CRC) has been observed and associated with income status, education level, treatment and late diagnosis. According to the American Cancer Society, among both males and females, CRC is the third most frequently diagnosed type of cancer and accounts for 10% of cancer deaths in the United States. Differences in CRC test use have been documented and limited to access to health care, demographics and health behaviors, but few studies have examined the correlates of CRC screening test use by gender. This present study examined the prevalence of CRC screening test use and assessed whether disparities are explained by gender and racial/ethnic differences. To assess these associations, the study utilized a cross-sectional design and examined the distribution of the covariates for gender and racial/ethnic group differences using the chi square statistic. Logistic regression was used to estimate the prevalence odds ratio and to adjust for the confounding effects of the covariates. ^ Results indicated there are disparities in the use of CRC screening test use and there were statistically significant difference in the prevalence for both FOBT and endoscopy screening between gender, χ2, p≤0.003. Females had a lower prevalence of endoscopy colorectal cancer screening than males when adjusting for age and education (OR 0.88, 95% CI 0.82–0.95). However, no statistically significant difference was reported between racial/ethnic groups, χ 2 p≤0.179 after adjusting for age, education and gender. For both FOBT and endoscopy screening Non-Hispanic Blacks and Hispanics had a lower prevalence of screening compared with Non-Hispanic Whites. In the multivariable regression model, the gender disparities could largely be explained by age, income status, education level, and marital status. Overall, individuals between the age "70–79" years old, were married, with some college education and income greater than $20,000 were associated with a higher prevalence of colorectal cancer screening test use within gender and racial/ethnic groups. ^

Gender associated risk factors of aortic aneurysms and dissections

Objectives. Predict who will develop a dissection. To create male and female prediction models using the risk factors: age, ethnicity, hypertension, high cholesterol, smoking, alcohol use, diabetes, heart attack, congestive heart failure, congenital and non-congenital heart disease, Marfan syndrome, and bicuspid aortic valve. ^ Methods. Using 572 patients diagnosed with aortic aneurysms, a model was developed for each of males and females using 80% of the data and then verified using the remaining 20% of the data. ^ Results. The male model predicted the probability of a male in having a dissection (p=0.076) and the female model predicted the probability of a female in having a dissection (p=0.054). The validation models did not support the choice of the developmental models. ^ Conclusions. The best models obtained suggested that those who are at a greater risk of having a dissection are males with non-congenital heart disease and who drink alcohol, and females with non-congenital heart disease and bicuspid aortic valve.^

Information bias and lifetime mortality risks of radiation-induced cancer

Additive and multiplicative models of relative risk were used to measure the effect of cancer misclassification and DS86 random errors on lifetime risk projections in the Life Span Study (LSS) of Hiroshima and Nagasaki atomic bomb survivors. The true number of cancer deaths in each stratum of the cancer mortality cross-classification was estimated using sufficient statistics from the EM algorithm. Average survivor doses in the strata were corrected for DS86 random error ($\sigma$ = 0.45) by use of reduction factors. Poisson regression was used to model the corrected and uncorrected mortality rates with covariates for age at-time-of-bombing, age at-time-of-death and gender. Excess risks were in good agreement with risks in RERF Report 11 (Part 2) and the BEIR-V report. Bias due to DS86 random error typically ranged from $-$15% to $-$30% for both sexes, and all sites and models. The total bias, including diagnostic misclassification, of excess risk of nonleukemia for exposure to 1 Sv from age 18 to 65 under the non-constant relative projection model was $-$37.1% for males and $-$23.3% for females. Total excess risks of leukemia under the relative projection model were biased $-$27.1% for males and $-$43.4% for females. Thus, nonleukemia risks for 1 Sv from ages 18 to 85 (DRREF = 2) increased from 1.91%/Sv to 2.68%/Sv among males and from 3.23%/Sv to 4.02%/Sv among females. Leukemia excess risks increased from 0.87%/Sv to 1.10%/Sv among males and from 0.73%/Sv to 1.04%/Sv among females. Bias was dependent on the gender, site, correction method, exposure profile and projection model considered. Future studies that use LSS data for U.S. nuclear workers may be downwardly biased if lifetime risk projections are not adjusted for random and systematic errors. (Supported by U.S. NRC Grant NRC-04-091-02.) ^

Gender disparities in utilization, unmet need and expenditure for mental health care

Objectives: To compare mental health care utilization regarding the source, types, and intensity of mental health services received, unmet need for services, and out of pocket cost among non-institutionalized psychologically distressed women and men. ^ Method: Cross-sectional data for 19,325 non-institutionalized mentally distressed adult respondents to the “The National Survey on Drug Use and Health” (NSDUH), for the years 2006 -2008, representing over twenty-nine millions U.S. adults was analyzed. To assess the relative odds for women compared to men, logistic regression analysis was used for source of service, for types of barriers, for unmet need and cost; zero inflated negative binomial regression for intensity of utilization; and ordinal logistic regression analysis for quantifying out-of-pocket expenditure. ^ Results: Overall, 43% of mentally distressed adults utilized a form of mental health treatment; representing 12.6 million U.S psychologically distressed adults. Females utilized more mental health care compared to males in the previous 12 months (OR: 1. 70; 95% CI: 1.54, 1.83). Similarly, females were 54% more likely to get help for psychological distress in an outpatient setting and females were associated with an increased probability of using medication for mental distress (OR: 1.72; 95% CI: 1.63, 1.98). Women were 1.25 times likelier to visit a mental health center (specialty care) than men. ^ Females were positively associated with unmet needs (OR: 1.50; 95% CI: 1.29, 1.75) after taking into account predisposing, enabling, and need (PEN) characteristics. Women with perceived unmet needs were 23% (OR: 0.77; 95% CI: 0.59, 0.99) less likely than men to report societal accommodation (stigma) as a barrier to mental health care. At any given cutoff point, women were 1.74 times likelier to be in the higher payment categories for inpatient out of pocket cost when other variables in the model are held constant. Conclusions: Women utilize more specialty mental healthcare, report more unmet need, and pay more inpatient out of pocket costs than men. These gender disparities exist even after controlling for predisposing, enabling, and need variables. Creating policies that not only provide mental health care access but also de-stigmatize mental illness will bring us one step closer to eliminating gender disparities in mental health care.^

Assessing and applying evidence-based interventions at the community level in India as a model policy to reduce neonatal mortality rates in Nigeria

Background. The United Nations' Millennium Development Goal (MDG) 4 aims for a two-thirds reduction in death rates for children under the age of five by 2015. The greatest risk of death is in the first week of life, yet most of these deaths can be prevented by such simple interventions as improved hygiene, exclusive breastfeeding, and thermal care. The percentage of deaths in Nigeria that occur in the first month of life make up 28% of all deaths under five years, a statistic that has remained unchanged despite various child health policies. This paper will address the challenges of reducing the neonatal mortality rate in Nigeria by examining the literature regarding efficacy of home-based, newborn care interventions and policies that have been implemented successfully in India. ^ Methods. I compared similarities and differences between India and Nigeria using qualitative descriptions and available quantitative data of various health indicators. The analysis included identifying policy-related factors and community approaches contributing to India's newborn survival rates. Databases and reference lists of articles were searched for randomized controlled trials of community health worker interventions shown to reduce neonatal mortality rates. ^ Results. While it appears that Nigeria spends more money than India on health per capita ($136 vs. $132, respectively) and as percent GDP (5.8% vs. 4.2%, respectively), it still lags behind India in its neonatal, infant, and under five mortality rates (40 vs. 32 deaths/1000 live births, 88 vs. 48 deaths/1000 live births, 143 vs. 63 deaths/1000 live births, respectively). Both countries have comparably low numbers of healthcare providers. Unlike their counterparts in Nigeria, Indian community health workers receive training on how to deliver postnatal care in the home setting and are monetarily compensated. Gender-related power differences still play a role in the societal structure of both countries. A search of randomized controlled trials of home-based newborn care strategies yielded three relevant articles. Community health workers trained to educate mothers and provide a preventive package of interventions involving clean cord care, thermal care, breastfeeding promotion, and danger sign recognition during multiple postnatal visits in rural India, Bangladesh, and Pakistan reduced neonatal mortality rates by 54%, 34%, and 15–20%, respectively. ^ Conclusion. Access to advanced technology is not necessary to reduce neonatal mortality rates in resource-limited countries. To address the urgency of neonatal mortality, countries with weak health systems need to start at the community level and invest in cost-effective, evidence-based newborn care interventions that utilize available human resources. While more randomized controlled studies are urgently needed, the current available evidence of models of postnatal care provision demonstrates that home-based care and health education provided by community health workers can reduce neonatal mortality rates in the immediate future.^

Impact of donor-recipient gender and race mismatching on patient survival in patients with end-stage liver diseases undergoing liver transplantation

Background. End-stage liver disease (ESLD) is an irreversible condition that leads to the imminent complete failure of the liver. Orthotopic liver transplantation (OLT) has been well accepted as the best curative option for patients with ESLD. Despite the progress in liver transplantation, the major limitation nowadays is the discrepancy between donor supply and organ demand. In an effort to alleviate this situation, mismatched donor and recipient gender or race livers are being used. However, the simultaneous impact of donor and recipient gender and race mismatching on patient survival after OLT remains unclear and relatively challenging to surgeons. ^ Objective. To examine the impact of donor and recipient gender and race mismatching on patient survival after OLT using the United Network for Organ Sharing (UNOS) database. ^ Methods. A total of 40,644 recipients who underwent OLT between 2002 and 2011 were included. Kaplan-Meier survival curves and the log-rank tests were used to compare the survival rates among different donor-recipient gender and race combinations. Univariate Cox regression analysis was used to assess the association of donor-recipient gender and race mismatching with patient survival after OLT. Multivariable Cox regression analysis was used to model the simultaneous impact of donor-recipient gender and race mismatching on patient survival after OLT adjusting for a list of other risk factors. Multivariable Cox regression analysis stratifying on recipient hepatitis C virus (HCV) status was also conducted to identify the variables that were differentially associated with patient survival in HCV + and HCV − recipients. ^ Results. In the univariate analysis, compared to male donors to male recipients, female donors to male recipients had a higher risk of patient mortality (HR, 1.122; 95% CI, 1.065–1.183), while in the multivariable analysis, male donors to female recipients experienced an increased mortality rates (adjusted HR, 1.114; 95% CI, 1.048–1.184). Compared to white donors to white recipients, Hispanic donors to black recipients had a higher risk of patient mortality (HR, 1.527; 95% CI, 1.293–1.804) in the univariate analysis, and similar result (adjusted HR, 1.553; 95% CI, 1.314–1.836) was noted in multivariable analysis. After the stratification on recipient HCV status in the multivariable analysis, HCV + mismatched recipients appeared to be at greater risk of mortality than HCV − mismatched recipients. Female donors to female HCV − recipients (adjusted HR, 0.843; 95% CI, 0.769–0.923), and Hispanic HCV + recipients receiving livers from black donors (adjusted HR, 0.758; 95% CI, 0.598–0.960) had a protective effect on patient survival after OLT. ^ Conclusion. Donor-recipient gender and race mismatching adversely affect patient survival after OLT, both independently and after the adjustment for other risk factors. Female recipient HCV status is an important effect modifier in the association between donor-recipient gender combination and patient survival.^

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.

INTEGRATIVE BIOMARKER IDENTIFICATION AND CLASSIFICATION USING HIGH THROUGHPUT ASSAYS

It is well accepted that tumorigenesis is a multi-step procedure involving aberrant functioning of genes regulating cell proliferation, differentiation, apoptosis, genome stability, angiogenesis and motility. To obtain a full understanding of tumorigenesis, it is necessary to collect information on all aspects of cell activity. Recent advances in high throughput technologies allow biologists to generate massive amounts of data, more than might have been imagined decades ago. These advances have made it possible to launch comprehensive projects such as (TCGA) and (ICGC) which systematically characterize the molecular fingerprints of cancer cells using gene expression, methylation, copy number, microRNA and SNP microarrays as well as next generation sequencing assays interrogating somatic mutation, insertion, deletion, translocation and structural rearrangements. Given the massive amount of data, a major challenge is to integrate information from multiple sources and formulate testable hypotheses. This thesis focuses on developing methodologies for integrative analyses of genomic assays profiled on the same set of samples. We have developed several novel methods for integrative biomarker identification and cancer classification. We introduce a regression-based approach to identify biomarkers predictive to therapy response or survival by integrating multiple assays including gene expression, methylation and copy number data through penalized regression. To identify key cancer-specific genes accounting for multiple mechanisms of regulation, we have developed the integIRTy software that provides robust and reliable inferences about gene alteration by automatically adjusting for sample heterogeneity as well as technical artifacts using Item Response Theory. To cope with the increasing need for accurate cancer diagnosis and individualized therapy, we have developed a robust and powerful algorithm called SIBER to systematically identify bimodally expressed genes using next generation RNAseq data. We have shown that prediction models built from these bimodal genes have the same accuracy as models built from all genes. Further, prediction models with dichotomized gene expression measurements based on their bimodal shapes still perform well. The effectiveness of outcome prediction using discretized signals paves the road for more accurate and interpretable cancer classification by integrating signals from multiple sources.