17 resultados para planners

em DigitalCommons@The Texas Medical Center


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Geographic health planning analyses, such as service area calculations, are hampered by a lack of patient-specific geographic data. Using the limited patient address information in patient management systems, planners analyze patient origin based on home address. But activity space research done sparingly in public health and extensively in non-health related arenas uses multiple addresses per person when analyzing accessibility. Also, health care access research has shown that there are many non-geographic factors that influence choice of provider. Most planning methods, however, overlook non-geographic factors influencing choice of provider, and the limited data mean the analyses can only be related to home address. This research attempted to determine to what extent geography plays a part in patient choice of provider and to determine if activity space data can be used to calculate service areas for primary care providers. During Spring 2008, a convenience sample of 384 patients of a locally-funded Community Health Center in Houston, Texas, completed a survey that asked about what factors are important when he or she selects a health care provider. A subset of this group (336) also completed an activity space log that captured location and time data on the places where the patient regularly goes. Survey results indicate that for this patient population, geography plays a role in their choice of health care provider, but it is not the most important reason for choosing a provider. Other factors for choosing a health care provider such as the provider offering “free or low cost visits”, meeting “all of the patient’s health care needs”, and seeing “the patient quickly” were all ranked higher than geographic reasons. Analysis of the patient activity locations shows that activity spaces can be used to create service areas for a single primary care provider. Weighted activity-space-based service areas have the potential to include more patients in the service area since more than one location per patient is used. Further analysis of the logs shows that a reduced set of locations by time and type could be used for this methodology, facilitating ongoing data collection for activity-space-based planning efforts.

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Individuals who are diagnosed with a chronic mental illness and an alcohol use disorder comprise a high risk population that challenges the mental health care system. Effective treatment for the dually diagnosed, who are characterized by heterogeneity in their psychiatric diagnoses, their substance use patterns, and their current degree of dysfunction, presents a challenge. Several integrated treatment models have been developed that attempt to concurrently treat patients' psychiatric and substance abuse problems. At this point in the development of these "dual diagnosis" programs, treatment planning is hindered by a lack of knowledge about the relation of psychiatric severity to the process of recovery from alcohol abuse and dependence.^ The present study sought to advance the field's understanding of the relation between psychiatric severity and the process of behavior change through an examination of the relation between dimensions of psychiatric severity and Prochaska and DiClemente's Transtheoretical Model (TTM) constructs. The TTM, which focuses on identifying the processes of change that appear to underlie the modification of addictive behaviors, provides a way of conceptualizing and measuring specific elements relevant to the desired behavior change. Knowledge of the relation between these constructs and psychiatric severity will enable treatment planners to develop dual diagnosis programs which target clients' needs with a much higher level of specificity.^ One hundred-thirty two alcohol dependent patients in a dual diagnosis treatment program were assessed on psychiatric severity (defined as number of symptoms and level of distress resulting from symptoms) and the Transtheoretical Model constructs. The constructs include stages and processes of change for alcohol use, alcohol decisional balance, and alcohol abstinence self-efficacy. Results indicate that the TTM variable of "temptation to drink" is most strongly related to psychiatric severity: the more psychiatric distress a person is experiencing, the more he or she is tempted to drink. The "cons" of drinking were also related to psychiatric severity, indicating that participants who were experiencing more psychiatric distress also endorsed as important a higher number of the negative aspects of drinking.^ Additional aims of this investigation were to determine whether participants' scores on the Transtheoretical Model variables were associated with their: (a) severity of drinking, defined as frequency, quantity and consequences of use, (b) previous psychiatric and substance abuse treatment episodes, and (c) functional impairment. Associations were found among these variables and each of the key constructs of the Transtheoretical Model. Each association is explored in detail and implications for treatment programming are discussed. ^

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The purpose of this dissertation was to examine the relationship between key psychosocial and behavioral components of the Transtheoretical Model and the Theory of Reasoned Action for sexual risk reduction in a population of crack cocaine smokers and sex workers, not in drug treatment. ^ The first study examined the results of an analysis of the association between two principal constructs in the Transtheoretical Model, the processes of change and the stages of change for condom use, in a high risk population. In the analysis of variance for all respondents, the overall F-test revealed that people in different stages have different levels of experiential process use, F(3,317) = 17.79, p = 0.0001 and different levels of behavioral process use, F(3,317) = 28.59, p = .0001. For the experiential processes, there was a significant difference between the precontemplation/contemplation stage, and both the action, and maintenance, stages.^ The second study explored the relationship between the Theory of Reasoned Action “beliefs” and the stages-of-change in the same population. In the analysis of variance for all participants, the results indicate that people in different stages did value the positive beliefs differently, F(3,502) = 15.38, p = .0001 but did not value the negative beliefs differently, F(3,502) = 2.08, p = .10. ^ The third study explored differences in stage-of-change by gender, partner type drug use, and HIV status. Three discriminant functions emerged, with a combined χ2(12) = 139.57, p = <.0001. The loading matrix of correlations between predictors and discriminant functions demonstrate that the strongest predictor for distinguishing between the precontemplation/contemplation stage and the preparation, action, and maintenance stages (first function) is partner type (.962). The loadings on the second discriminant function suggest that once partner type has been accounted for, ever having HIV/AIDS (.935) was the best predictor for distinguishing between the first three stages and the maintenance stage. ^ These studies demonstrate that behavioral change theories can contribute important insight to researchers and program planners attempting to alter HIV risk behavior in high-risk populations. ^

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In the last several decades traditional community health indicators have become ambiguous and lost some of their relevance. During this same period national and international health agencies adopted new expanded definitions of Health that include underlying social determinants. These two influences are responsible for a proliferation of new health indicators and many are constructed from a combination of older mortality measures and available information on morbidity. Problems inherent in attempting to combine these sources of information have produced a situation where some indicators are difficult to calculate at the national level and may not function at all for small communities. What is needed is a relevant measure of the burden of ill health appropriate for smaller populations that is accessible to local health planners. ^ Death records are still the best available population health information. In Europe the burden of health problems is often portrayed using 'premature' death. Health agencies in the United States have moved to adopt Years of Potential Life Lost. Both these regions are also developing systems of 'avoidable' or 'preventable' death as health indicators. This research proposes a method combining these methodologies to produce a relevant indicator portraying the burden of ill health in communities. ^

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Geographic health planning analyses, such as service area calculations, are hampered by a lack of patient-specific geographic data. Using the limited patient address information in patient management systems, planners analyze patient origin based on home address. But activity space research done sparingly in public health and extensively in non-health related arenas uses multiple addresses per person when analyzing accessibility. Also, health care access research has shown that there are many non-geographic factors that influence choice of provider. Most planning methods, however, overlook non-geographic factors influencing choice of provider, and the limited data mean the analyses can only be related to home address. This research attempted to determine to what extent geography plays a part in patient choice of provider and to determine if activity space data can be used to calculate service areas for primary care providers. ^ During Spring 2008, a convenience sample of 384 patients of a locally-funded Community Health Center in Houston, Texas, completed a survey that asked about what factors are important when he or she selects a health care provider. A subset of this group (336) also completed an activity space log that captured location and time data on the places where the patient regularly goes. ^ Survey results indicate that for this patient population, geography plays a role in their choice of health care provider, but it is not the most important reason for choosing a provider. Other factors for choosing a health care provider such as the provider offering "free or low cost visits", meeting "all of the patient's health care needs", and seeing "the patient quickly" were all ranked higher than geographic reasons. ^ Analysis of the patient activity locations shows that activity spaces can be used to create service areas for a single primary care provider. Weighted activity-space-based service areas have the potential to include more patients in the service area since more than one location per patient is used. Further analysis of the logs shows that a reduced set of locations by time and type could be used for this methodology, facilitating ongoing data collection for activity-space-based planning efforts. ^

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Alzheimer's disease (AD), the most common form of dementia, is the fifth leading cause of death among U.S. adults aged 65 or older. Most AD patients have shorter life expectancy compared with older people without dementia. This disease has become an enormous challenge in the aging society and is also a global problem. Not only do families of patients with Alzheimer's disease need to pay attention to this problem, but also the healthcare system and society as a whole have to confront. In dementia, functional impairment is associated with basic activities of daily living (ADL) and instrumental activities of daily living (IADL). For patients with Alzheimer's disease, problems typically appear in performing IADL and progress to the inability of managing less complex ADL functions of personal care. Thus, assessment of ADLs can be used for early accurate diagnosis of Alzheimer's disease. It should be useful for patients, caregivers, clinicians, and policy planners to estimate the survival of patients with Alzheimer's disease. However, it is unclear that when making predictions of patient outcome according to their histories, time-dependent covariates will provide us with important information on how changes in a patient's status can effect the survival. In this study, we examined the effect of impaired basic ADL as measured by the Physical Self-Maintenance Scale (PSMS) and utilized a multistate survival analysis approach to estimate the probability of death in the first few years of initial visit for AD patients taking into consideration the possibility of impaired basic ADL. The dataset used in this study was obtained from the Baylor Alzheimer's Disease and Memory Disorders Center (ADMDC). No impaired basic ADL and older age at onset of impaired basic ADL were associated with longer survival. These findings suggest that the occurrence of impaired basic ADL and age at impaired basic ADL could be predictors of survival among patients with Alzheimer's disease. ^

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A crucial link in preserving and protecting the future of our communities resides in maintaining the health and well being of our youth. While every member of the community owns an opinion regarding where to best utilize monies for prevention and intervention, the data to support such opinion is often scarce. In an effort to generate data-driven indices for community planning and action, the United Way of Comal County, Texas partnered with the University Of Texas - Houston Health Science Center, School Of Public Health to accomplish a county-specific needs assessment. A community-based participatory research emphasis utilizing the Mobilization for Action through Planning and Partnership (MAPP) format developed by the National Association of City and County Health Officials (NACCHO) was implemented to engage community members in identifying and addressing community priorities. The single greatest area of consensus and concern identified by community members was the health and well being of the youth population. Thus, a youth survey, targeting these specific areas of community concern, was designed, coordinated and administered to all 9-11th grade students in the county. 20% of the 3,698 completed surveys (72% response rate) were randomly selected for analysis. These 740 surveys were coded and scanned into an electronic survey database. Statistical analysis provided youth-reported data on the status of the multiple issues affecting the health and well being of the community's youth. These data will be reported back to the community stakeholders, as part of the larger Comal County Needs Assessment, for the purposes of community planning and action. Survey data will provide community planners with an awareness of the high risk behaviors and habit patterns amongst their youth. This knowledge will permit more effective targeting of the means for encouraging healthy behaviors and preventing the spread of disease. Further, the community-oriented, population-based nature of this effort will provide answers to questions raised by the community and will provide an effective launching pad for the development and implementation of targeted, preventive health strategies. ^

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The three articles that comprise this dissertation describe how small area estimation and geographic information systems (GIS) technologies can be integrated to provide useful information about the number of uninsured and where they are located. Comprehensive data about the numbers and characteristics of the uninsured are typically only available from surveys. Utilization and administrative data are poor proxies from which to develop this information. Those who cannot access services are unlikely to be fully captured, either by health care provider utilization data or by state and local administrative data. In the absence of direct measures, a well-developed estimation of the local uninsured count or rate can prove valuable when assessing the unmet health service needs of this population. However, the fact that these are “estimates” increases the chances that results will be rejected or, at best, treated with suspicion. The visual impact and spatial analysis capabilities afforded by geographic information systems (GIS) technology can strengthen the likelihood of acceptance of area estimates by those most likely to benefit from the information, including health planners and policy makers. ^ The first article describes how uninsured estimates are currently being performed in the Houston metropolitan region. It details the synthetic model used to calculate numbers and percentages of uninsured, and how the resulting estimates are integrated into a GIS. The second article compares the estimation method of the first article with one currently used by the Texas State Data Center to estimate numbers of uninsured for all Texas counties. Estimates are developed for census tracts in Harris County, using both models with the same data sets. The results are statistically compared. The third article describes a new, revised synthetic method that is being tested to provide uninsured estimates at sub-county levels for eight counties in the Houston metropolitan area. It is being designed to replicate the same categorical results provided by a current U.S. Census Bureau estimation method. The estimates calculated by this revised model are compared to the most recent U.S. Census Bureau estimates, using the same areas and population categories. ^

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Background. Today modern day slavery is known as human trafficking and is a growing pandemic that is a grave human rights violation. Estimates suggest that 12.3 million people are working under conditions of force, fraud or coercion. Working toward eradication is a worthy effort; it would free millions of humans from slavery, mostly women and children, as well as uphold basic human rights. One tactic to eradicating human trafficking is to increase identification of victims among those likely to encounter victims of human trafficking.^ Purpose. This study aims to develop an intervention that improves certain stakeholders' ability, in the health clinic setting, to appropriately identify and report victims of human trafficking to the National Human Trafficking Resource Center.^ Methods. The Intervention Mapping (IM) process was used by program planners to develop an intervention for health professionals. This methodology is a six step process that guides program planners to develop an intervention. Each step builds on the others through the execution of a needs assessment, and the development of matrices based on performance objectives and determinants of the targeted health behavior. The end product results in an ecological, theoretical, and evidence based intervention.^ Discussion. The IM process served as a useful protocol for program planners to take an ecological approach as well as incorporate theory and evidence into the intervention. Consultation with key informants, the planning group, adopters, implementers, and individuals responsible for institutionalization also contributed to the practicality and feasibility of the intervention. Program planners believe that this intervention fully meets recommendations set forth in the literature.^ Conclusions. The intervention mapping methodology enabled program planners to develop an intervention that is appropriate and acceptable to the implementer and the recipients.^

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The built environment is recognized as having an impact on health and physical activity. Ecological theories of physical activity suggest that enhancing access to places to be physically active may increase activity levels. Studies show that users of fitness facilities are more likely to be active than inactive and active people are more likely to report access to fitness facilities. The purpose of this study was to examine the ecologic relationship between density of fitness facilities and self-reported levels of physical activity in adults in selected Metropolitan Statistical Areas (MSAs) in the United States.^ The 2007 MSA Business Patterns and the 2007 Behavioral Risk Factor Surveillance System (BRFSS) were used to gather fitness facility and physical activity data for 141 MSAs in the United States. Pearson correlations were performed between fitness facility density (number of facilities/100,000 people) and six summary measures of physical activity prevalence. Regional analysis was done using the nine U.S. Standard Regions for Temperature and Precipitation. ^ Direct correlations between fitness facility density and the percent of those physically active (r=0.27, 95% CI 0.11, 0.42, p=0.0012), those meeting moderate-intensity activity guidelines, (r=0.23, 95% CI 0.07, 0.38, p=0.006), and those meeting vigorous-intensity activity guidelines (r=0.30, 95% CI 0.14, 0.44, p=0.003) were found. An inverse correlation was found between fitness facility density and the percent of people physically inactive (r=-0.45, 95% CI -0.57, -0.31), p<0.0001). Regional analysis showed the same trends across most regions.^ Access to fitness facilities, defined here as fitness facility density, is related to physical activity levels. Results suggest the potential importance of the influence of the built environment on physical activity behaviors. Public health officials and city planners should consider the possible positive effect that increasing the number of fitness facilities in communities would have on activity levels.^

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This study examines variations in physical activity by season, and within seasons by age and gender among park users living in the Cameron Park Colonia, a low-income Hispanic community along the Texas-Mexico border. This is the first study of its kind to evaluate seasonal variations by physical activity among a Hispanic population. We hypothesized that (1) there are no differences in overall physical activity by season; (2) youth engage in more sport-related physical activity compared to adults, (3) males engage in more physical activity than females, and (4) there are differences in physical activity between walk-trail users compared to non walk-trail users in the park.^ Physical activity behavioral data was collected (males n=2,093; females n=1,014) at two time periods (winter 2007; summer 2007) via direct observations and assessed park use, walking trail use, and physical activity (moderate-to-vigorous physical activity (MVPA) by seasons. Frequencies for physical activities were calculated for gender, age groups, and season. Separate Pearson's chi-square analyses were used to address variations in physical activity, age, gender, intensity level of physical activity by season, between walk-trails users and non walk-trail users.^ People visiting the park engaged in more sedentary behavior in winter than summer and a higher percentage engaged in MVPA in the summer than winter (p<.05). More females engaged in light activity compared to males (p<.05). Walk-trail users consisted mostly of females and engaged in more light activity than non walk-trail users (p<.05) who participated in more MVPA.^ Increasing access to parks and walk-trails may be an intervention strategy to increase physical activity among Hispanics. More research is needed to assess promoting trail use and determining long-term effects on physical activity among minority/ethnic groups at greater risk of a sedentary lifestyle and reasons for trail use and non-use. Future studies should focus on the types of activities Hispanics engage in at different parks particularly between men and women. As a result of this study city officials and planners may use this information to build and design parks that cater to the types of activities that Hispanics engage in and may use to meet physical activity guidelines.^

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In the midst of health care reform, and as health care organizations reorganize to provide more cost-effective healthcare, the population is being shifted into new healthcare delivery systems such as health insurance purchasing alliances, and health maintenance organizations. These new models of delivery are usually organized within resource restricted and data limited environments. Health care planners are faced with the challenge of identifying priorities for preventive and primary care services within these newly organized populations (Medicare HMO, Medicaid HMO, etc.). The author proposes a technique usually employed in epidemiology--attributable risk estimation--as a planning methodology to establish preventive health priorities within newly organized populations. Illustrations of the methodology are provided utilizing the Texas 1992 population. ^

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One of the broad objectives of the Nigerian health service, vigorously being pursued at all levels of government, is to make comprehensive health care available and accessible to the population at the lowest possible cost, within available resources. Some state governments in the federation have already introduced free medical service as a practical way to remove financial barriers to access and in turn to encourage greater utilization of publicly funded care facilities.^ To aid health planners and decision makers in identifying a shorter corridor through which urban dwellers can gain access to comprehensive health care, a health interview survey of the metropolitan Lagos was undertaken. The primary purpose was to ascertain the magnitude of access problems which urban households face in seeking care from existing public facilities at the time of need. Six categories of illness chosen from the 1975 edition of the International Classification of Disease were used as indicators of health need.^ Choice of treatment facilities in response to illness episode was examined in relation to distance, travel time, time of use and transportation experiences. These were graphically described. The overall picture indicated that distance and travel time coexist with transportation problems in preventing a significant segment of those in need of health care from benefitting in the free medical service offered in public health facilities. Within this milieu, traditional medicine and its practitioners became the most preferred alternative. Recommendations were offered for action with regard to decentralization of general practitioner (GP) consultations in general hospitals and integration of traditional medicine and its practitioners into public health service. ^

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As the requirements for health care hospitalization have become more demanding, so has the discharge planning process become a more important part of the health services system. A thorough understanding of hospital discharge planning can, then, contribute to our understanding of the health services system. This study involved the development of a process model of discharge planning from hospitals. Model building involved the identification of factors used by discharge planners to develop aftercare plans, and the specification of the roles of these factors in the development of the discharge plan. The factors in the model were concatenated in 16 discrete decision sequences, each of which produced an aftercare plan.^ The sample for this study comprised 407 inpatients admitted to the M. D. Anderson Hospital and Tumor Institution at Houston, Texas, who were discharged to any site within Texas during a 15 day period. Allogeneic bone marrow donors were excluded from the sample. The factors considered in the development of discharge plans were recorded by discharge planners and were used to develop the model. Data analysis consisted of sorting the discharge plans using the plan development factors until for some combination and sequence of factors all patients were discharged to a single site. The arrangement of factors that led to that aftercare plan became a decision sequence in the model.^ The model constructs the same discharge plans as those developed by hospital staff for every patient in the study. Tests of the validity of the model should be extended to other patients at the MDAH, to other cancer hospitals, and to other inpatient services. Revisions of the model based on these tests should be of value in the management of discharge planning services and in the design and development of comprehensive community health services.^

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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. ^