13 resultados para Calling Cards

em DigitalCommons@The Texas Medical Center


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Large field studies of travelers' diarrhea for multiple destinations are limited by the need to perform stool cultures on site in a timely manner. A method for the collection, transport, and storage of fecal specimens that does not require immediate processing and refrigeration and that is stable for months would be advantageous. This study was designed to determine if enterotoxigenic Escherichia coli (ETEC) and enteroaggregative E. coli (EAEC) DNA could be identified from cards that were processed for the evaluation of fecal occult blood. U.S. students traveling to Mexico during 2005 to 2007 were monitored for the occurrence of diarrheal illness. When ill, students provided a stool specimen for culture and occult blood by the standard methods. Cards then were stored at room temperature prior to DNA extraction. Fecal PCR was performed to identify ETEC and EAEC in DNA extracted from stools and from occult blood cards. Significantly more EAEC cases were identified by PCR that was performed on DNA that was extracted from cards (49%) or from frozen feces (40%) than from culture methods that used HEp-2 adherence assays (13%) (P < 0.001). Similarly, more ETEC cases were detected from card DNA (38%) than from fecal DNA (30%) or by culture that was followed by hybridization (10%) (P < 0.001). The sensitivity and specificity of the card test were 75 and 62%, respectively, compared to those for EAEC by culture and were 50 and 63%, respectively, compared to those for ETEC. DNA extracted from fecal cards that was used for the detection of occult blood is of use in identifying diarrheagenic E. coli.

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Background. Large field studies in travelers' diarrhea (TD) in multiple destinations are limited by the need to perform stool cultures on site in a timely manner. A method for the collection, transport and storage of fecal specimens that does not require immediate processing, refrigeration and is stable for months would be advantageous. ^ Objectives. Determine if enteric pathogen bacterial DNA can be identified in cards routinely used for evaluation of fecal occult blood. ^ Methods. U.S. students traveling to Mexico in 2005-07 were followed for occurrence of diarrheal illness. When ill, students provided a stool specimen for culture and occult blood by the standard method. Cards were then stored at room temperature prior to DNA extraction. A multiplex fecal PCR was performed to identify enterotoxigenic Escherichia coli and enteroaggregative E. coli (EAEC) in DNA extracted from stools and occult blood cards. ^ Results. Significantly more EAEC cases were identified by PCR done in DNA extracted from cards (49%) or from frozen feces (40%) than by culture followed by HEp-2 adherence assays (13%). Similarly more ETEC cases were detected in card DNA (38%) than fecal DNA (30%) or culture followed by hybridization (10%). Sensitivity and specificity of the card test was 75% and 62%, respectively, and 50% and 63%, respectively, when compared to EAEC and ETEC culture, respectively, and 53% and 51%, respectively compared to EAEC multiplex fecal PCR and 56% and 70%, respectively, compared to ETEC multiplex fecal PCR. ^ Conclusions. DNA extracted from fecal cards used for detection of occult blood is of use in detecting enteric pathogens. ^

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The implications of the new research presented in Volume 2, Issue 1 (Human Trafficking) of the Journal of Applied Research on Children are explored, calling attention to the need for increased awareness, greater availability of data, and proactive policy solutions to combat child trafficking.

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A commentary on Busch-Armendariz, Nsonwu, and Heffron’s article, “Human Trafficking Victims and Their Children: Assessing Needs, Vulnerabilities, Strengths, and Survivorship,” noting key findings and calling for further research.

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The implications of the new research presented in Volume 2, Issue 2 (Teen Pregnancy) of the Journal of Applied Research on Children are explored, calling attention to proactive policy solutions to combat teen pregnancy.

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Public preferences for policy are formed in a little-understood process that is not adequately described by traditional economic theory of choice. In this paper I suggest that U.S. aggregate support for health reform can be modeled as tradeoffs among a small number of behavioral values and the stage of policy development. The theory underlying the model is based on Samuelson, et al.'s (1986) work and Wilke's (1991) elaboration of it as the Greed/Efficiency/Fairness (GEF) hypothesis of motivation in the management of resource dilemmas, and behavioral economics informed by Kahneman and Thaler's prospect theory. ^ The model developed in this paper employs ordered probit econometric techniques applied to data derived from U.S. polls taken from 1990 to mid-2003 that measured support for health reform proposals. Outcome data are four-tiered Likert counts; independent variables are dummies representing the presence or absence of operationalizations of each behavioral variable, along with an integer representing policy process stage. Marginal effects of each independent variable predict how support levels change on triggering that variable. Model estimation results indicate a vanishingly small likelihood that all coefficients are zero and all variables have signs expected from model theory. ^ Three hypotheses were tested: support will drain from health reform policy as it becomes increasingly well-articulated and approaches enactment; reforms appealing to fairness through universal health coverage will enjoy a higher degree of support than those targeted more narrowly; health reforms calling for government operation of the health finance system will achieve lower support than those that do not. Model results support the first and last hypotheses. Contrary to expectations, universal health care proposals did not provide incremental support beyond those targeted to “deserving” populations—children, elderly, working families. In addition, loss of autonomy (e.g. restrictions on choice of care giver) is found to be the “third rail” of health reform with significantly-reduced support. When applied to a hypothetical health reform in which an employer-mandated Medical Savings Account policy is the centerpiece, the model predicts support that may be insufficient to enactment. These results indicate that the method developed in the paper may prove valuable to health policy designers. ^

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Objectives. The purpose of this paper is to conduct a literature review of research relating to foodborne illness, food inspection policy, and restaurants in the United States. Aim 1: To convey the public health importance of studying restaurant food inspection policies and suggest that more research is needed in this field, Aim 2: To conduct a systematic literature review of recent literature pertaining to this subject such that future researchers can understand the: (1) Public perception and expectations of restaurant food inspection policies; (2) Arguments in favor of a grade card policy; and, conversely; (3) Reasons why inspection policies may not work. ^ Data/methods. This paper utilizes a systematic review format to review articles relating to food inspections and restaurants in the U.S. Eight articles were reviewed. ^ Results. The resulting data from the literature provides no conclusive answer as to how, when, and in what method inspection policies should be carried out. The authors do, however, put forward varying solutions as to how to fix the problem of foodborne illness outbreaks in restaurants. These solutions include the implementation of grade cards in restaurants and, conversely, a complete overhaul of the inspection policy system.^ Discussion. The literature on foodborne disease, food inspection policy, and restaurants in the U.S. is limited and varied. But, from the research that is available, we can see that two schools of thought exist. The first of these calls for the implementation of a grade card system, while the second proposes a reassessment and possible overhaul of the food inspection policy system. It is still unclear which of these methods would best slow the increase in foodborne disease transmission in the U.S.^ Conclusion. In order to arrive at solutions to the problem of foodborne disease transmission as it relates to restaurants in this country, we may need to look at literature from other countries and, subsequently, begin incremental changes in the way inspection policies are developed and enforced.^

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The healthcare industry spends billions on worker injury and employee turnover. Hospitals and healthcare settings have one of the highest rates of lost days due to injuries. The occupational hazards for healthcare workers can be classified into biological, chemical, ergonomic, physical, organizational, and psychosocial. Therefore, interventions addressing a range of occupational health risks are needed to prevent injuries and reduce turnover and reduce costs. ^ The Sacred Vocation Program (SVP) seeks to change the content of work, i.e., the meaningfulness of work, to improve work environments. The SVP intervenes at both the individual and organizational level. First the SVP attempts to connect healthcare workers with meaning from their work through a series of 5 self-discovery group sessions. In a sixth session the graduates take an oath recommitting them to do their work as a vocation. Once motivated to connect with meaning in their work, a representative employee group meets in a second set of five meetings. This representative group suggests organizational changes to create a culture that supports employees in their calling. The employees present their plan in the twelfth session to management beginning a new phase in the existing dialogue between employees and management. ^ The SVP was implemented in a large Dallas hospital (almost 1000 licensed beds). The Baylor University Medical Center (BUMC) Pastoral Care department invited front-line caregivers (primarily Patient Care Assistants, PCAs, or Patient Care Technicians, PCTs) to participate in the SVP. Participants completed SVP questionnaires at the beginning and following SVP implementation. Following implementation, employer records were collected on injury, absence and turnover to further evaluate the program's effectiveness on metrics that are meaningful to managers in assessing organizational performance. This provided an opportunity to perform an epidemiological evaluation of the intervention using the two sources of information: employee self-reports and employer administrative data. ^ The ability to evaluate the effectiveness of the SVP on program outcomes could be limited by the strength of the measures used. An ordinal CFA performed on baseline SVP questionnaire measurements examined the construct validity and reliability of the SVP scales. Scales whose item-factor structure was confirmed in ordinal CFA were evaluated for their psychometric properties (i.e., reliability, mean, ceiling and floor effects). CFA supported the construct validity of six of the proposed scales: blocks to spirituality, meaning at work, work satisfaction, affective commitment, collaborative communication, and MHI-5. Five of the six scales confirmed had acceptable measures of reliability (all but MHI-5 had α>0.7). All six scales had a high percentage (>30%) of the scores at the ceiling. These findings supported the use of these items in the evaluation of change although strong ceiling effects may hinder discerning change. ^ Next, the confirmed SVP scales were used to evaluate whether the intervention improved program constructs. To evaluate the SVP a one group pretest-posttest design compared participants’ self-reports before and after the intervention. It was hypothesized that measurements of reduced blocks to spirituality (α = 0.76), meaning at work (α = 0.86), collaborative communication (α = 0.67) and SVP job tasks (α = 0.97) would improve following SVP implementation. The SVP job tasks scale was included even though it was not included in the ordinal CFA analysis due to a limited sample and high inter-item correlation. Changes in scaled measurements were assessed using multilevel linear regression methods. All post-intervention measurements increased (increases <0.28 points) but only reduced blocks to spirituality was statistically significant (0.22 points on a scale from 1 to 7, p < 0.05) after adjustment for covariates. Intensity of the intervention (stratifying on high participation units) strengthened effects; but were not statistically significant. The findings provide preliminary support for the hypothesis that meaning in work can be improved and, importantly, lend greater credence to any observed improvements in the outcomes. (Abstract shortened by UMI.)^

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Background. EAP programs for airline pilots in companies with a well developed recovery management program are known to reduce pilot absenteeism following treatment. Given the costs and safety consequences to society, it is important to identify pilots who may be experiencing an AOD disorder to get them into treatment. ^ Hypotheses. This study investigated the predictive power of workplace absenteeism in identifying alcohol or drug disorders (AOD). The first hypothesis was that higher absenteeism in a 12-month period is associated with higher risk that an employee is experiencing AOD. The second hypothesis was that AOD treatment would reduce subsequent absence rates and the costs of replacing pilots on missed flights. ^ Methods. A case control design using eight years (time period) of monthly archival absence data (53,000 pay records) was conducted with a sample of (N = 76) employees having an AOD diagnosis (cases) matched 1:4 with (N = 304) non-diagnosed employees (controls) of the same profession and company (male commercial airline pilots). Cases and controls were matched on the variables age, rank and date of hire. Absence rate was defined as sick time hours used over the sum of the minimum guarantee pay hours annualized using the months the pilot worked for the year. Conditional logistic regression was used to determine if absence predicts employees experiencing an AOD disorder, starting 3 years prior to the cases receiving the AOD diagnosis. A repeated measures ANOVA, t tests and rate ratios (with 95% confidence intervals) were conducted to determine differences between cases and controls in absence usage for 3 years pre and 5 years post treatment. Mean replacement costs were calculated for sick leave usage 3 years pre and 5 years post treatment to estimate the cost of sick leave from the perspective of the company. ^ Results. Sick leave, as measured by absence rate, predicted the risk of being diagnosed with an AOD disorder (OR 1.10, 95% CI = 1.06, 1.15) during the 12 months prior to receiving the diagnosis. Mean absence rates for diagnosed employees increased over the three years before treatment, particularly in the year before treatment, whereas the controls’ did not (three years, x = 6.80 vs. 5.52; two years, x = 7.81 vs. 6.30, and one year, x = 11.00cases vs. 5.51controls. In the first year post treatment compared to the year prior to treatment, rate ratios indicated a significant (60%) post treatment reduction in absence rates (OR = 0.40, CI = 0.28, 0.57). Absence rates for cases remained lower than controls for the first three years after completion of treatment. Upon discharge from the FAA and company’s three year AOD monitoring program, case’s absence rates increased slightly during the fourth year (controls, x = 0.09, SD = 0.14, cases, x = 0.12, SD = 0.21). However, the following year, their mean absence rates were again below those of the controls (controls, x = 0.08, SD = 0.12, cases, x¯ = 0.06, SD = 0.07). Significant reductions in costs associated with replacing pilots calling in sick, were found to be 60% less, between the year of diagnosis for the cases and the first year after returning to work. A reduction in replacement costs continued over the next two years for the treated employees. ^ Conclusions. This research demonstrates the potential for workplace absences as an active organizational surveillance mechanism to assist managers and supervisors in identifying employees who may be experiencing or at risk of experiencing an alcohol/drug disorder. Currently, many workplaces use only performance problems and ignore the employee’s absence record. A referral to an EAP or alcohol/drug evaluation based on the employee’s absence/sick leave record as incorporated into company policy can provide another useful indicator that may also carry less stigma, thus reducing barriers to seeking help. This research also confirms two conclusions heretofore based only on cross-sectional studies: (1) higher absence rates are associated with employees experiencing an AOD disorder; (2) treatment is associated with lower costs for replacing absent pilots. Due to the uniqueness of the employee population studied (commercial airline pilots) and the organizational documentation of absence, the generalizability of this study to other professions and occupations should be considered limited. ^ Transition to Practice. The odds ratios for the relationship between absence rates and an AOD diagnosis are precise; the OR for year of diagnosis indicates the likelihood of being diagnosed increases 10% for every hour change in sick leave taken. In practice, however, a pilot uses approximately 20 hours of sick leave for one trip, because the replacement will have to be paid the guaranteed minimum of 20 hour. Thus, the rate based on hourly changes is precise but not practical. ^ To provide the organization with practical recommendations the yearly mean absence rates were used. A pilot flies on average, 90 hours a month, 1080 annually. Cases used almost twice the mean rate of sick time the year prior to diagnosis (T-1) compared to controls (cases, x = .11, controls, x = .06). Cases are expected to use on average 119 hours annually (total annual hours*mean annual absence rate), while controls will use 60 hours. The cases’ 60 hours could translate to 3 trips of 20 hours each. Management could use a standard of 80 hours or more of sick time claimed in a year as the threshold for unacceptable absence, a 25% increase over the controls (a cost to the company of approximately of $4000). At the 80-hour mark, the Chief Pilot would be able to call the pilot in for a routine check as to the nature of the pilot’s excessive absence. This management action would be based on a company standard, rather than a behavioral or performance issue. Using absence data in this fashion would make it an active surveillance mechanism. ^

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This study addresses the responses to a postcard campaign with health messages targeting the parents of children in a sample of low-income elementary schools and assesses the feasibility and areas of possible improvements in such a project. The campaign was implemented in Spring 2009 with 4 th grade students (n=1070) in fifteen economically disadvantaged elementary schools in Travis County, Texas. Postcards were sent home with children, and parents filled out a feedback card that the children returned to school. Response data, in the form of self-administered feedback cards (n=2665) and one-on-one teacher interviews (n=8), were qualitatively analyzed using NVivo 8 software. Postcard reception and points of improvement were then identified from the significant themes that emerged including health, cessation or reduction of unhealthy behaviors, motivation, family, and the comprehension of abstract health concepts. ^ Responses to the postcard campaign were almost completely positive, with less than 1% of responses reporting some sort of dislike, and many parents reported a modification of their behavior. However, possible improvements that could be made to the campaign are: increased focus of the postcards on the parents as the target population, increased information about serving size, greater emphasis on the link between obesity and health, alteration of certain skin tones used in the graphical depiction of people on the cards, and smaller but more frequent incentives to return the feedback cards for the students. The program appears to be an effective method of communicating health messages to the parents of 4th grade children.^

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SNP genotyping arrays have been developed to characterize single-nucleotide polymorphisms (SNPs) and DNA copy number variations (CNVs). The quality of the inferences about copy number can be affected by many factors including batch effects, DNA sample preparation, signal processing, and analytical approach. Nonparametric and model-based statistical algorithms have been developed to detect CNVs from SNP genotyping data. However, these algorithms lack specificity to detect small CNVs due to the high false positive rate when calling CNVs based on the intensity values. Association tests based on detected CNVs therefore lack power even if the CNVs affecting disease risk are common. In this research, by combining an existing Hidden Markov Model (HMM) and the logistic regression model, a new genome-wide logistic regression algorithm was developed to detect CNV associations with diseases. We showed that the new algorithm is more sensitive and can be more powerful in detecting CNV associations with diseases than an existing popular algorithm, especially when the CNV association signal is weak and a limited number of SNPs are located in the CNV.^

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Information technology (IT) in the hospital organization is fast becoming a key asset, particularly in light of recent reform legislation in the United States calling for expanding the role of IT in our health care system. Future payment reductions to hospitals included in current health reform are based on expected improvements in hospital operating efficiency. Since over half of hospital expenses are for labor, improved efficiency in use of labor resources can be critical in meeting this challenge. Policy makers have touted the value of IT investments to improve efficiency in response to payment reductions. ^ This study was the first to directly examine the relationship between electronic health record (EHR) technology and staffing efficiency in hospitals. As the hospital has a myriad of outputs for inpatient and outpatient care, efficiency was measured using an industry standard performance metric – full time equivalent employees per adjusted occupied bed (FTE/AOB). Three hypotheses were tested in this study.^ To operationalize EHR technology adoption, we developed three constructs to model adoption, each of which was tested by separate hypotheses. The first hypothesis that a larger number of EHR applications used by a hospital would be associated with greater staffing efficiency (or lower values of FTE/AOB) was not accepted. Association between staffing efficiency and specific EHR applications was the second hypothesis tested and accepted with some applications showing significant impacts on observed values for FTE/AOB. Finally, the hypothesis that the longer an EHR application was used in a hospital would be associated with greater labor efficiency was not accepted as the model showed few statistically significant relationships to FTE/AOB performance. Generally, there does not appear a strong relationship between EHR usage and improved labor efficiency in hospitals.^ While returns on investment from EHR usage may not come from labor efficiencies, they may be better sought using measures of quality, contribution to an efficient and effective local health care system, and improved customer satisfaction through greater patient throughput.^

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Next-generation sequencing (NGS) technology has become a prominent tool in biological and biomedical research. However, NGS data analysis, such as de novo assembly, mapping and variants detection is far from maturity, and the high sequencing error-rate is one of the major problems. . To minimize the impact of sequencing errors, we developed a highly robust and efficient method, MTM, to correct the errors in NGS reads. We demonstrated the effectiveness of MTM on both single-cell data with highly non-uniform coverage and normal data with uniformly high coverage, reflecting that MTM’s performance does not rely on the coverage of the sequencing reads. MTM was also compared with Hammer and Quake, the best methods for correcting non-uniform and uniform data respectively. For non-uniform data, MTM outperformed both Hammer and Quake. For uniform data, MTM showed better performance than Quake and comparable results to Hammer. By making better error correction with MTM, the quality of downstream analysis, such as mapping and SNP detection, was improved. SNP calling is a major application of NGS technologies. However, the existence of sequencing errors complicates this process, especially for the low coverage (