8 resultados para Monitoring, SLA, JBoss, Middleware, J2EE, Java, Service Level Agreements
em DigitalCommons@The Texas Medical Center
Resumo:
In a large health care system, the importance of accurate information as feedback mechanisms about its performance is necessary on many levels from the senior level management to service level managers for valid decision-making purposes. The implementation of dashboards is one way to remedy the problem of data overload by providing up-to-date, accurate, and concise information. As this health care system seeks to have an organized, systematic review mechanism in place, dashboards are being created in a variety of the hospital service departments to monitor performance indicators. The Infection Control Administration of this health care system is one that does not currently utilize a dashboard but seeks to implement one. ^ The purpose of this project is to research and design a clinical dashboard for the Infection Control Administration. The intent is that the implementation and usefulness of the clinical dashboard translates into improvement in the measurement of health care quality.^
Resumo:
This article examines the predictors of placement following IFPSfor a sample of child mental health service recipients and their families. Risk and protective factors vary depending on the time frame under consideration. Immediately following service, children 's level of Social/Legal functioning, a previous group home placement, and the presence of mental health problems for other family members increase risk of placement, while the number of follow-up services serves to lessen risk. Three to six months after service, the presence of a child behavior presenting problem and a projected placement in foster care serve as protective factors, while two service targets, alcohol monitoring and time management, serve to increase risk. Appropriate use of results for program design and for structuring access to services is discussed.
Resumo:
This study of ambulance workers for the emergency medical services of the City of Houston studied the factors related to shiftwork tolerance and intolerance. The EMS personnel work a 24-hour shift with rotating days of the week. Workers are assigned to A, B, C, D shift, each of which rotate 24-hours on, 24-hours off, 24-hours on and 4 days off. One-hundred and seventy-six male EMTs, paramedics and chauffeurs from stations of varying levels of activity were surveyed. The sample group ranged in age from 20 to 45. The average tenure on the job was 8.2 years. Over 68% of the workers held a second job, the majority of which worked over 20 hours a week at the second position.^ The survey instrument was a 20-page questionnaire modeled after the Folkard Standardized Shiftwork Index. In addition to demographic data, the survey tool provided measurements of general job satisfaction, sleep quality, general health complaints, morningness/eveningness, cognitive and somatic anxiety, depression, and circadian types. The survey questionnaire included an EMS-specific scaler of stress.^ A conceptual model of Shiftwork Tolerance was presented to identify the key factors examined in the study. An extensive list of 265 variables was reduced to 36 key variables that related to: (1) shift schedule and demographic/lifestyle factors, (2) individual differences related to traits and characteristics, and (3) tolerance/intolerance effects. Using the general job satisfaction scaler as the key measurement of shift tolerance/intolerance, it was shown that a significant relationship existed between this dependent variable and stress, number of years working a 24-hour shift, sleep quality, languidness/vigorousness. The usual amount of sleep received during the shift, general health complaints and flexibility/rigidity (R$\sp2$ =.5073).^ The sample consisted of a majority of morningness-types or extreme-morningness types, few evening-types and no extreme-evening types, duplicating the findings of Motohashi's previous study of ambulance workers. The level of activity by station was not significant on any of the dependent variables examined. However, the shift worked had a relationship with sleep quality, despite the fact that all shifts work the same hours and participate in the same rotation schedule. ^
Resumo:
A process evaluation of the Houston Childhood Lead Poisoning Prevention Program, 1992-1995, was conducted. The Program's goal is to reduce lead poisoning prevalence. The study proposed to determine to what extent the Program was implemented as planned by measuring how well Program services were actually: (1) received by the intended target population; (2) delivered to children with elevated blood lead levels; (3) delivered in compliance with the Centers for Disease Control and Prevention and Program guidelines and timetables; and (4) able to reduce lead poisoning prevalence among those rescreened. Utilizing a program monitoring design, the Program's pre-collected computer records were reviewed. The study sample consisted of 820 children whose blood lead levels were above 15 micrograms per deciLiter, representing approximately 2.9% of the 28,406 screened over this period. Three blood lead levels from each participant were examined: the initial elevated result; the confirmatory result; and the next rescreen result, after the elevated confirmatory level. Results showed that the Program screened approximately 18% (28,406 of 161,569) of Houston's children under age 6 years for lead poisoning. Based on Chi-square tests of significance, results also showed that lead-poisoned participants were more likely to be younger than 3 years, male and Hispanic, compared to those not lead poisoned. The age, gender and ethnic differences observed were statistically significant (p =.01, p =.00, p =.00). Four of the six Program services: medical evaluations, rescreening, environmental inspections and confirmation, had satisfactory delivery completion rates of 71%-98%. Delivery timetable compliance rates for three of the six services examined: outreach contacts, home visits and environmental inspections were below 32%. However, dangerously elevated blood lead levels fell and lead poisoning prevalence dropped from 3.3% at initial screening to 1.2% among those rescreened, after intervention. From a public health perspective, reductions in lead poisoning prevalence are very meaningful. Based on these findings, the following are recommendations for future research: (1) integrate Program database files by utilizing a computer database management program; (2) target services at Hispanic male children under age 3 years living in the highest risk neighborhoods; (3) increase resources to: improve tracking and documentation of service delivery and provide more non-medical case management and environmental services; and (4) share the evaluation methodology/findings with the Centers for Disease Control and Prevention administrators; the implications may be relevant to other program managers conducting such assessments. ^
Resumo:
The Houston region is home to arguably the largest petrochemical and refining complex anywhere. The effluent of this complex includes many potentially hazardous compounds. Study of some of these compounds has led to recognition that a number of known and probable carcinogens are at elevated levels in ambient air. Two of these, benzene and 1,3-butadiene, have been found in concentrations which may pose health risk for residents of Houston.^ Recent popular journalism and publications by local research institutions has increased the interest of the public in Houston's air quality. Much of the literature has been critical of local regulatory agencies' oversight of industrial pollution. A number of citizens in the region have begun to volunteer with air quality advocacy groups in the testing of community air. Inexpensive methods exist for monitoring of ozone, particulate matter and airborne toxic ambient concentrations. This study is an evaluation of a technique that has been successfully applied to airborne toxics.^ This technique, solid phase microextraction (SPME), has been used to measure airborne volatile organic hydrocarbons at community-level concentrations. It is has yielded accurate and rapid concentration estimates at a relatively low cost per sample. Examples of its application to measurement of airborne benzene exist in the literature. None have been found for airborne 1,3-butadiene. These compounds were selected for an evaluation of SPME as a community-deployed technique, to replicate previous application to benzene, to expand application to 1,3-butadiene and due to the salience of these compounds in this community. ^ This study demonstrates that SPME is a useful technique for quantification of 1,3-butadiene at concentrations observed in Houston. Laboratory background levels precluded recommendation of the technique for benzene. One type of SPME fiber, 85 μm Carboxen/PDMS, was found to be a sensitive sampling device for 1,3-butadiene under temperature and humidity conditions common in Houston. This study indicates that these variables affect instrument response. This suggests the necessity of calibration within specific conditions of these variables. While deployment of this technique was less expensive than other methods of quantification of 1,3-butadiene, the complexity of calibration may exclude an SPME method from broad deployment by community groups.^
Resumo:
A simple and inexpensive method is described for analysis of uranium (U) activity and mass in water by liquid scintillation counting using $\alpha$/$\beta$ discrimination. This method appears to offer a solution to the need for an inexpensive protocol for monitoring U activity and mass simultaneously and an alternative to the potential inaccuracy involved when depending on the mass-to-activity conversion factor or activity screen.^ U is extracted virtually quantitatively into 20 ml extractive scintillator from a 1-$\ell$ aliquot of water acidified to less than pH 2. After phase separation, the sample is counted for a 20-minute screening count with a minimum detection level of 0.27 pCi $\ell\sp{-1}$. $\alpha$-particle emissions from the extracted U are counted with close to 100% efficiency with a Beckman LS6000 LL liquid scintillation counter equipped with pulse-shape discrimination electronics. Samples with activities higher than 10 pCi $\ell\sp-1$ are recounted for 500-1000 minutes for isotopic analysis. Isotopic analysis uses events that are automatically stored in spectral files and transferred to a computer during assay. The data can be transferred to a commercially available spreadsheet and retrieved for examination or data manipulation. Values for three readily observable spectral features can be rapidly identified by data examination and substituted into a simple formula to obtain $\sp{234}$U/$\sp{238}$U ratio for most samples. U mass is calculated by substituting the isotopic ratio value into a simple equation.^ The utility of this method for the proposed compliance monitoring of U in public drinking water supplies was field tested with a survey of drinking water from Texas supplies that had previously been known to contain elevated levels of gross $\alpha$ activity. U concentrations in 32 samples from 27 drinking water supplies ranged from 0.26 to 65.5 pCi $\ell\sp{-1}$, with seven samples exceeding the proposed Maximum Contaminant Level of 20 $\mu$g $\ell\sp{-1}$. Four exceeded the proposed activity screening level of 30 pCi $\ell\sp{-1}$. Isotopic ratios ranged from 0.87 to 41.8, while one sample contained $\sp{234}$U activity of 34.6 pCi $\ell\sp{-1}$ in the complete absence of its parent, $\sp{238}$U. U mass in the samples with elevated activity ranged from 0.0 to 103 $\mu$g $\ell\sp{-1}$. A limited test of screening surface and groundwaters for contamination by U from waste sites and natural processes was also successful. ^
Resumo:
The National Health Planning and Resources Development Act of 1974 (Public Law 93-641) requires that health systems agencies (HSAs) plan for their health service areas by the use of existing data to the maximum extent practicable. Health planning is based on the identificaton of health needs; however, HSAs are, at present, identifying health needs in their service areas in some approximate terms. This lack of specificity has greatly reduced the effectiveness of health planning. The intent of this study is, therefore, to explore the feasibility of predicting community levels of hospitalized morbidity by diagnosis by the use of existing data so as to allow health planners to plan for the services associated with specific diagnoses.^ The specific objectives of this study are (a) to obtain by means of multiple regression analysis a prediction equation for hospital admission by diagnosis, i.e., select the variables that are related to demand for hospital admissions; (b) to examine how pertinent the variables selected are; and (c) to see if each equation obtained predicts well for health service areas.^ The existing data on hospital admissions by diagnosis are those collected from the National Hospital Discharge Surveys, and are available in a form aggregated to the nine census divisions. When the equations established with such data are applied to local health service areas for prediction, the application is subject to the criticism of the theory of ecological fallacy. Since HSAs have to rely on the availability of existing data, it is imperative to examine whether or not the theory of ecological fallacy holds true in this case.^ The results of the study show that the equations established are highly significant and the independent variables in the equations explain the variation in the demand for hospital admission well. The predictability of these equations is good when they are applied to areas at the same ecological level but become poor, predominantly due to ecological fallacy, when they are applied to health service areas.^ It is concluded that HSAs can not predict hospital admissions by diagnosis without primary data collection as discouraged by Public Law 93-641. ^
Resumo:
The purpose of this study was to understand the scope of breast cancer disparities within the Texas Medical Center. The goal was to increase the awareness of breast cancer disparities at the health care organization level, and to foster the development of organizational interventions to reduce breast cancer disparities. The study seeks to answer the following questions: 1. Are hospitals in the Texas Medical Center implementing interventions to reduce breast cancer disparities? 2. What are their interventions for reducing the effects of non clinical factors on breast cancer treatment disparities? 3. What are their measures for monitoring, continuously improving, and evaluating the success of their interventions? ^ This research project was designed as a mixed methods case study. Quantitative breast cancer data for the years 2000-2009 was obtained from the Texas Cancer Registry (TCR). Qualitative data collection and analysis was done by conducting a total of 20 semi-structured interviews of administrators, physicians and nurses at five hospitals (A, B, C, D and E) in the Texas Medical Center (TMC). For quantitative analysis, the study was limited to early stage breast cancer patients: local and regional. The dependent variable was receipt of standard treatment: Surgery (Yes/No), BCS vs Mastectomy, Chemotherapy (Yes/No) and Radiation after BCS (Yes/No). The main independent variable was race: non-Hispanic White (NHW) , non-Hispanic Black (NHB), and Hispanic. Other covariates included age at diagnosis, diagnosis date, percent poverty, grade, stage, and regional nodes. Multivariate logistic regression was used to test the adjusted association between receipt of standard care and race. Qualitative data was analyzed with the Atlas.ti7 software (ATLAS.ti GmbH, Berlin). ^ Though there were significant differences by race for all dependent variables when the data was analyzed as a single group of all hospitals; at the level of the individual hospitals the results were not consistent by race/ethnicity across all dependent variables for hospitals A, B, and E. There were no racial differences in adjusted analysis for receipt of chemotherapy for the individual hospitals of interest in this study. For hospitals C and D, no racial disparities in treatment was observed in adjusted multivariable analysis. All organizations in this study were aware of the body of research which shows that there are disparities in breast cancer outcomes for patient population groups. However, qualitative data analysis found that there were differences in interest among hospitals in addressing breast cancer disparities in their patient population groups. Some organizations were actively implementing directed measures to reduce the breast cancer disparity gap in outcomes for patients, and others were not. Despite the differences in levels of interest, quantitative data analysis showed that organizations in the Texas Medical Center were making progress in reducing the burden of breast cancer disparities in the patient populations being served.^