Household health assessment and associated water sample analysis in the Miches watershed of the Dominican Republic

Background. Diarrhea and malnutrition are the leading causes of mortality for children age one to four in the Dominican Republic. Communities within the Miches watershed lack sanitation infrastructure and water purification systems, which increases the risk of exposure to water-borne pathogens. The purpose of this cross-sectional study was to analyze health information gathered through household interviews and to test water samples for the presence of diarrheagenic pathogens and antibiotic-resistant bacteria within the Miches watershed. Methods. Frequency counts and thematic analysis were used to investigate Human Health Survey responses and Fisher's exact test was used to determine correlation between water source and reported illness. Bacteria cultured from water samples were analyzed by Gram stain, real-time PCR, API® 20E biochemical identification, and for antibiotic resistance. Results. Community members reported concerns about water sources with respect to water quality, availability, and environmental contamination. Pathogenic strains of E. coli were present in the water samples. Drinking aquifer water was positively-correlated with reported stomach aches (p=0.04) while drinking from rivers or creeks was associated with the reported absence of “gripe” (cold or flu) (p=0.01). The lack of association between reported illnesses and water source for the majority of variables suggested that there were multiple vehicles of disease transmission. Antibiotic resistant bacteria were isolated from the water samples tested. Conclusions. The presence of pathogenic E. coli in water samples suggested that water is at least one route of transmission for diarrheagenic pathogens in the Miches watershed. The presence of antibiotic-resistant bacteria in the water samples may indicate the proliferation of resistance plasmids in the environment as a result of antibiotic overuse in human and animal populations and a lack of sanitation infrastructure. An intervention that targets areas of hygiene, sanitation, and water purification is recommended to limit human exposure to diarrheagenic pathogens and antibiotic-resistant organisms. ^

A BAYESIAN APPROACH TO DOSE-RESPONSE ASSESSMENT AND DRUG-DRUG INTERACTION ANALYSIS: APPLICATION TO IN VITRO STUDIES

The considerable search for synergistic agents in cancer research is motivated by the therapeutic benefits achieved by combining anti-cancer agents. Synergistic agents make it possible to reduce dosage while maintaining or enhancing a desired effect. Other favorable outcomes of synergistic agents include reduction in toxicity and minimizing or delaying drug resistance. Dose-response assessment and drug-drug interaction analysis play an important part in the drug discovery process, however analysis are often poorly done. This dissertation is an effort to notably improve dose-response assessment and drug-drug interaction analysis. The most commonly used method in published analysis is the Median-Effect Principle/Combination Index method (Chou and Talalay, 1984). The Median-Effect Principle/Combination Index method leads to inefficiency by ignoring important sources of variation inherent in dose-response data and discarding data points that do not fit the Median-Effect Principle. Previous work has shown that the conventional method yields a high rate of false positives (Boik, Boik, Newman, 2008; Hennessey, Rosner, Bast, Chen, 2010) and, in some cases, low power to detect synergy. There is a great need for improving the current methodology. We developed a Bayesian framework for dose-response modeling and drug-drug interaction analysis. First, we developed a hierarchical meta-regression dose-response model that accounts for various sources of variation and uncertainty and allows one to incorporate knowledge from prior studies into the current analysis, thus offering a more efficient and reliable inference. Second, in the case that parametric dose-response models do not fit the data, we developed a practical and flexible nonparametric regression method for meta-analysis of independently repeated dose-response experiments. Third, and lastly, we developed a method, based on Loewe additivity that allows one to quantitatively assess interaction between two agents combined at a fixed dose ratio. The proposed method makes a comprehensive and honest account of uncertainty within drug interaction assessment. Extensive simulation studies show that the novel methodology improves the screening process of effective/synergistic agents and reduces the incidence of type I error. We consider an ovarian cancer cell line study that investigates the combined effect of DNA methylation inhibitors and histone deacetylation inhibitors in human ovarian cancer cell lines. The hypothesis is that the combination of DNA methylation inhibitors and histone deacetylation inhibitors will enhance antiproliferative activity in human ovarian cancer cell lines compared to treatment with each inhibitor alone. By applying the proposed Bayesian methodology, in vitro synergy was declared for DNA methylation inhibitor, 5-AZA-2'-deoxycytidine combined with one histone deacetylation inhibitor, suberoylanilide hydroxamic acid or trichostatin A in the cell lines HEY and SKOV3. This suggests potential new epigenetic therapies in cell growth inhibition of ovarian cancer cells.

A STUDY OF THE RELATIONSHIP BETWEEN SELF-ASSESSMENT AND CLINICAL EVALUATION OF HEARING STATUS

The relationship was explored between a subjective measure of hearing status, derived from a functional self-assessment expressed in terms of ability to hear and understand spoken words, and a comparable objective measure of hearing status, obtained from a speech reception test. The Augmentation Survey of the Health and Nutrition Examination Survey of the National Center for Health Statistics provided the necessary data for a sample of 3059 adults. Using chi-square tests for the subsample with the highest level of objectively assessed hearing status, favorable subjective assessments were found to be significantly associated with higher income, lower age group, higher level of educational attainment, greater psychological adjustment, fewer symptoms of depression, and higher self-ratings of overall health. In a linear regression with self-assessment of hearing status as the dependent variable, less than one-quarter of the variation could be explained by objective status and the six explanatory variables.^

INTAKE VARIABLES AS PREDICTORS OF ASSESSMENT AND REFERRAL PROCEDURE OUTCOMES IN EMPLOYEE ASSISTANCE PROGRAMS

While reported prevalence rates of troubled employees vary considerably, even conservative estimates indicate a major public health problem. For example, alcohol and drug related problems alone cost U.S. industry more than 45 billion dollars annually.^ Of the alternatives available to deal with these problems, e.g., dismissal or disciplinary actions, the most viable and cost effective are employee assistance programs (EAP), designed to provide professional assistance to employees experiencing alcohol, drug, emotional or personal crisis.^ The principal component of an EAP is that of assessment and referral, and this study was developed to determine which EAP client intake variables are the most efficacious predictors of assessment and referral procedures.^ Although, specific client intake variables were statistically significant the discriminant classification analysis was demonstrably inadequate. Nevertheless, the identification of A/R procedure phases which were not efficacious, as well as EAP client populations for whom services were not effective, were extremely valuable discernments. Identifying the less efficacious components of the A/R process provided an opportunity to recommend alternatives to current program procedures and practices, which may ameliorate program effectiveness. ^

Clinical decision support capabilities of commercially-available clinical information systems.

BACKGROUND: The most effective decision support systems are integrated with clinical information systems, such as inpatient and outpatient electronic health records (EHRs) and computerized provider order entry (CPOE) systems. Purpose The goal of this project was to describe and quantify the results of a study of decision support capabilities in Certification Commission for Health Information Technology (CCHIT) certified electronic health record systems. METHODS: The authors conducted a series of interviews with representatives of nine commercially available clinical information systems, evaluating their capabilities against 42 different clinical decision support features. RESULTS: Six of the nine reviewed systems offered all the applicable event-driven, action-oriented, real-time clinical decision support triggers required for initiating clinical decision support interventions. Five of the nine systems could access all the patient-specific data items identified as necessary. Six of the nine systems supported all the intervention types identified as necessary to allow clinical information systems to tailor their interventions based on the severity of the clinical situation and the user's workflow. Only one system supported all the offered choices identified as key to allowing physicians to take action directly from within the alert. Discussion The principal finding relates to system-by-system variability. The best system in our analysis had only a single missing feature (from 42 total) while the worst had eighteen.This dramatic variability in CDS capability among commercially available systems was unexpected and is a cause for concern. CONCLUSIONS: These findings have implications for four distinct constituencies: purchasers of clinical information systems, developers of clinical decision support, vendors of clinical information systems and certification bodies.

The utility of rapid participatory appraisal for community assessment, diagnosis, and policy development

The selection of a model to guide the understanding and resolution of community problems is an important issue relating to the foundation of public health practice: assessment, policy development, and assurance. Many assessment models produce a diagnosis of community weaknesses, but fail to promote planning and interventions. Rapid Participatory Appraisal (RPA) is a participatory action research model which regards assessment as the first step in the problem solving process, and claims to achieve assessment and policy development within limited resources of time and money. Literature documenting the fulfillment of these claims, and thereby supporting the utility of the model, is relatively sparse and difficult to obtain. Very few articles discuss the changes resulting from RPA assessments in urban areas, and those that do describe studies conducted outside the U.S.A. ^ This study examines the utility of the RPA model and its underlying theories: systems theory, grounded theory, and principles of participatory change, as illustrated by the case study of a community assessment conducted for the Texas Diabetes Institute (TDI), San Antonio, Texas, and subsequent outcomes. Diabetes has a high prevalence and is a major issue in San Antonio. Faculty and students conducted the assessment by informal collaboration between two nursing and public health assessment courses, providing practical student experiences. The study area was large, and the flexibility of the model tested by its use in contiguous sub-regions, reanalyzing aggregated results for the study area. Official TDI reports, and a mail survey of agency employees, described policy development resulting from community diagnoses revealed by the assessment. ^ The RPA model met the criteria for utility from the perspectives of merit, worth, efficiency, and effectiveness. The RPA model best met the agencies' criteria (merit), met the data needs of TDI in this particular situation (worth), provided valid results within budget, time, and personnel constraints (efficiency), and stimulated policy development by TDI (effectiveness). ^ The RPA model appears to have utility for community assessment, diagnosis, and policy development in circumstances similar to the TDI diabetes study. ^

The Comprehensive Assessment of Leadership for Learning: A Next Generation Formative Evaluation and Feedback System

Recent developments in federal policy have prompted the creation of state evaluation frameworks for principals and teachers that hold educators accountable for effective practices and student outcomes. These changes have created a demand for formative evaluation instruments that reflect current accountability pressures and can be used by schools to focus school improvement and leadership development efforts. The Comprehensive Assessment of Leadership for Learning (CALL) is a next generation, 360-degree on-line assessment and feedback system that reflect best practices in feedback design. Some unique characteristics of CALL include a focus on: leadership distributed throughout the school rather than as carried out by an individual leader; assessment of leadership tasks rather than perceptions of leadership practice; a focus on larger complex systems of middle and high school; and transparency of assessment design. This paper describes research contributing to the design and validation of the CALL survey instrument.