6 resultados para after sales service

em DigitalCommons@The Texas Medical Center


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The policy development process leading to the Labour government's white paper of December 1997—The new NHS: Modern, Dependable—is the focus of this project and the public policy development literature is used to aid in the understanding of this process. Policy makers who had been involved in the development of the white paper were interviewed in order to acquire a thorough understanding of who was involved in this process and how they produced the white paper. A theoretical framework is used that sorts policy development models into those that focus on knowledge and experience, and those which focus on politics and influence. This framework is central to understanding the evidence gathered from the individuals and associations that participated in this policy development process. The main research question to be asked in this project is to what extent do either of these sets of policy development models aid in understanding and explicating the process by which the Labour government's policies were developed. The interview evidence, along with published evidence, show that a clear pattern of policy change emerged from this policy development process, and the Knowledge-Experience and Politics-Influence policy making models both assist in understanding this process. The early stages of the policy development process were characterized as hierarchical and iterative, yet also very collaborative among those participating, with knowledge and experience being quite prevalent. At every point in the process, however, informal networks of political influence were used and noted to be quite prevalent by all of the individuals interviewed. The later stages of the process then became increasingly noninclusive, with decisions made by a select group of internal and external policy makers. These policy making models became an important tool with which to understand the policy development process. This Knowledge-Experience and Politics-Influence dichotomy of policy development models could therefore be useful in analyzing other types of policy development. ^

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Homelessness is associated with high use of public services such as health care and criminal justice services. Intervention designs to reverse homelessness have broadly fallen into two categories: either standard care which employs requisitely addressing the causes of homelessness, or housing first, which emphasizes provision of permanent housing without requisitely addressing the causes of homelessness. Multiple cities have recently commenced housing first interventions. Locally, Houston’s first housing first development is the Jackson Hinds Gardens project. The purpose of this study is to analyze the public service use of residents of housing first in Houston. Residents of Jackson Hinds Gardens who have been enrolled for at least 6 months were evaluated for public service use for an equal amount of time preceding and during their residence at Jackson Hinds. Resident interactions with county health services and criminal justice entities were determined by electronic database searches; these data were supplemented by life experience interview data. Service usage values pre- and post-enrollment at Jackson Hinds Gardens were compared by paired t-test analyses. We found that ER and inpatient usage decreased following enrollment in Jackson Hinds, although these reductions were not significant. In contrast, outpatient care and number of medications significantly increased following enrollment. These analyses inform on the effects of housing first in another major city, as well as informing the ethical considerations regarding housing first versus standard care. ^

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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. ^

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Background. Each year thousands of people participate in mass health screenings for diabetes and hypertension, but little is known about whether or not those who receive higher than normal screening results obtain the recommended follow-up medical care, or what barriers they perceive to doing so. ^ Methods. Study participants were recruited from attendees at three health fairs in low-income neighborhoods in Houston, Texas Potential participants had higher than normal blood pressure (> 90/140 mgHg) or blood glucose readings (100 mm/dL fasting or 140 mm/dL random). Study participants were called at one, two, and three months and asked if they had obtained follow-up medical care; those who had not yet obtained follow-up care were asked to identify barriers. Using a modified Aday-Andersen model of health service access, the independent variables were individual and community characteristics and self-perceived need. The dependent variable was obtaining follow-up care, with barriers to care a secondary outcome. ^ Results. Eighty-two study participants completed the initial questionnaire and 59 participants completed the study protocol. Forty-eight participants (59% under an intent to treat analysis, 81% of those completing the study protocol) obtained follow-up care. Those who completed the initial questionnaire and who reported a regular source of care were significantly more likely to obtain follow-up care. For those who completed the study protocol the relationship between having a regular source of care and obtaining follow-up care approached but did not reach significance. For those who completed the initial questionnaire, self-described health status, when examined as a binary variable (good, very good, excellent, or poor, fair, not sure) was associated with obtaining follow-up care for those who rated their health as poor, fair, or not sure. While the group who completed the study protocol did not reach statistical significance, the same relationship between self-described health status of poor, fair, or not sure and obtaining follow-up care was present. The participants who completed the study protocol and described their blood pressure as OK or a little high were statistically more likely to get follow-up care than those who described it as high or very high. All those on oral medications for hypertension (12/12) and diabetes (4/4) who were told to obtain follow-up care did so; however, the small sample size allows this correlation to be of statistical significance only for those treating hypertension. ^ The variables significantly associated with obtaining follow-up care were having a regular source of care, self-described health status of poor, fair, or not sure, self-described blood pressure of OK or a little high, and taking medication for blood pressure. ^ At the follow-up telephone calls, 34 participants identified barriers to care; cost was a significant barrier reported by 16 participants, and 10 reported that they didn’t have time because they were working long hours after Hurricane Ike. ^ The study included the offer of access assistance: information about nearby safety-net providers, a visit to or information from the Health Information Center at their Neighborhood Center location, or information from Project Safety Net (a searchable web site for safety net providers). Access assistance was offered at the health fairs and then again at follow-up telephone calls to those who had not yet obtained follow-up care. Of the 48 participants who reported obtaining follow-up care, 26 said they had made use of the access assistance to do so. The use of access assistance was associated with being Hispanic, not having health insurance or a regular source of care, and speaking Spanish. It was also associated with being worried about blood glucose. ^ Conclusion. Access assistance, as a community enabling characteristic, may be useful in aiding low-income people in obtaining medical care. ^

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Patients who had started HAART (Highly Active Anti-Retroviral Treatment) under previous aggressive DHHS guidelines (1997) underwent a life-long continuous HAART that was associated with many short term as well as long term complications. Many interventions attempted to reduce those complications including intermittent treatment also called pulse therapy. Many studies were done to study the determinants of rate of fall in CD4 count after interruption as this data would help guide treatment interruptions. The data set used here was a part of a cohort study taking place at the Johns Hopkins AIDS service since January 1984, in which the data were collected both prospectively and retrospectively. The patients in this data set consisted of 47 patients receiving via pulse therapy with the aim of reducing the long-term complications. ^ The aim of this project was to study the impact of virologic and immunologic factors on the rate of CD4 loss after treatment interruption. The exposure variables under investigation included CD4 cell count and viral load at treatment initiation. The rates of change of CD4 cell count after treatment interruption was estimated from observed data using advanced longitudinal data analysis methods (i.e., linear mixed model). Using random effects accounted for repeated measures of CD4 per person after treatment interruption. The regression coefficient estimates from the model was then used to produce subject specific rates of CD4 change accounting for group trends in change. The exposure variables of interest were age, race, and gender, CD4 cell counts and HIV RNA levels at HAART initiation. ^ The rate of fall of CD4 count did not depend on CD4 cell count or viral load at initiation of treatment. Thus these factors may not be used to determine who can have a chance of successful treatment interruption. CD4 and viral load were again studied by t-tests and ANOVA test after grouping based on medians and quartiles to see any difference in means of rate of CD4 fall after interruption. There was no significant difference between the groups suggesting that there was no association between rate of fall of CD4 after treatment interruption and above mentioned exposure variables. ^

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A life table methodology was developed which estimates the expected remaining Army service time and the expected remaining Army sick time by years of service for the United States Army population. A measure of illness impact was defined as the ratio of expected remaining Army sick time to the expected remaining Army service time. The variances of the resulting estimators were developed on the basis of current data. The theory of partial and complete competing risks was considered for each type of decrement (death, administrative separation, and medical separation) and for the causes of sick time.^ The methodology was applied to world-wide U.S. Army data for calendar year 1978. A total of 669,493 enlisted personnel and 97,704 officers were reported on active duty as of 30 September 1978. During calendar year 1978, the Army Medical Department reported 114,647 inpatient discharges and 1,767,146 sick days. Although the methodology is completely general with respect to the definition of sick time, only sick time associated with an inpatient episode was considered in this study.^ Since the temporal measure was years of Army service, an age-adjusting process was applied to the life tables for comparative purposes. Analyses were conducted by rank (enlisted and officer), race and sex, and were based on the ratio of expected remaining Army sick time to expected remaining Army service time. Seventeen major diagnostic groups, classified by the Eighth Revision, International Classification of Diseases, Adapted for Use In The United States, were ranked according to their cumulative (across years of service) contribution to expected remaining sick time.^ The study results indicated that enlisted personnel tend to have more expected hospital-associated sick time relative to their expected Army service time than officers. Non-white officers generally have more expected sick time relative to their expected Army service time than white officers. This racial differential was not supported within the enlisted population. Females tend to have more expected sick time relative to their expected Army service time than males. This tendency remained after diagnostic groups 580-629 (Genitourinary System) and 630-678 (Pregnancy and Childbirth) were removed. Problems associated with the circulatory system, digestive system and musculoskeletal system were among the three leading causes of cumulative sick time across years of service. ^