An empirical model to estimate the demand for primary care in urban settings

Objective. To measure the demand for primary care and its associated factors by building and estimating a demand model of primary care in urban settings.^ Data source. Secondary data from 2005 California Health Interview Survey (CHIS 2005), a population-based random-digit dial telephone survey, conducted by the UCLA Center for Health Policy Research in collaboration with the California Department of Health Services, and the Public Health Institute between July 2005 and April 2006.^ Study design. A literature review was done to specify the demand model by identifying relevant predictors and indicators. CHIS 2005 data was utilized for demand estimation.^ Analytical methods. The probit regression was used to estimate the use/non-use equation and the negative binomial regression was applied to the utilization equation with the non-negative integer dependent variable.^ Results. The model included two equations in which the use/non-use equation explained the probability of making a doctor visit in the past twelve months, and the utilization equation estimated the demand for primary conditional on at least one visit. Among independent variables, wage rate and income did not affect the primary care demand whereas age had a negative effect on demand. People with college and graduate educational level were associated with 1.03 (p < 0.05) and 1.58 (p < 0.01) more visits, respectively, compared to those with no formal education. Insurance was significantly and positively related to the demand for primary care (p < 0.01). Need for care variables exhibited positive effects on demand (p < 0.01). Existence of chronic disease was associated with 0.63 more visits, disability status was associated with 1.05 more visits, and people with poor health status had 4.24 more visits than those with excellent health status. ^ Conclusions. The average probability of visiting doctors in the past twelve months was 85% and the average number of visits was 3.45. The study emphasized the importance of need variables in explaining healthcare utilization, as well as the impact of insurance, employment and education on demand. The two-equation model of decision-making, and the probit and negative binomial regression methods, was a useful approach to demand estimation for primary care in urban settings.^

Dynamic Chemical Shift Imaging for Image-Guided Thermal Therapy

Magnetic resonance temperature imaging (MRTI) is recognized as a noninvasive means to provide temperature imaging for guidance in thermal therapies. The most common method of estimating temperature changes in the body using MR is by measuring the water proton resonant frequency (PRF) shift. Calculation of the complex phase difference (CPD) is the method of choice for measuring the PRF indirectly since it facilitates temperature mapping with high spatiotemporal resolution. Chemical shift imaging (CSI) techniques can provide the PRF directly with high sensitivity to temperature changes while minimizing artifacts commonly seen in CPD techniques. However, CSI techniques are currently limited by poor spatiotemporal resolution. This research intends to develop and validate a CSI-based MRTI technique with intentional spectral undersampling which allows relaxed parameters to improve spatiotemporal resolution. An algorithm based on autoregressive moving average (ARMA) modeling is developed and validated to help overcome limitations of Fourier-based analysis allowing highly accurate and precise PRF estimates. From the determined acquisition parameters and ARMA modeling, robust maps of temperature using the k-means algorithm are generated and validated in laser treatments in ex vivo tissue. The use of non-PRF based measurements provided by the technique is also investigated to aid in the validation of thermal damage predicted by an Arrhenius rate dose model.

Quality of life and functional status in a low -income, multiethnic HIV -positive population

The introduction of new medical treatments in recent years, commonly referred to as highly active antiretroviral therapy, has greatly increased the survival of patients with HIV/AIDS. As patients with HIV/AIDS continue to live longer, other important health-related outcomes, such as quality of life (QOL), should be thoroughly studied. There is also evidence that racial/ethnic minorities are disproportionately affected by HIV/AIDS, but potential health disparities among individuals already infected with HIV/AIDS have not been adequately examined in ethnically diverse populations. The purpose of this dissertation was to: (1) examine the impact of both demographic and behavioral variables on functional status and overall QOL among a population of ethnically diverse and economically disadvantaged HIV/AIDS patients; (2) examine the psychometric properties of a functional status measure—the Household and Leisure Time Activities questionnaire (HLTA); and (3) assess a proximal-distal theoretical framework for QOL using a full structural equation model in a population of patients with HIV/AIDS. Analyses were performed using data collected in the fall of 2000 from the project, Health and Work-Related Quality of Life and Health Risk Behaviors in a Multiethnic HIV-positive Population . Investigators from The University of Texas M.D. Anderson Cancer Center, The University of Texas-Houston Medical School, and The University of Texas School of Public Health conducted this project. The study site was the Thomas Street Clinic (TSC), a comprehensive HIV/AIDS care facility funded by the Harris County Hospital District (HCHD). TSC provides HIV/AIDS care to a diverse population of approximately 4000 medically indigent residents of Harris County. A systematic, consecutive sampling procedure yielded a sample size of 348 patients. Findings suggested that overall QOL, work-role functioning, household functioning, and leisure time functioning were impaired in this patient population. Results from the psychometric evaluation indicated that the HLTA was a reliable and valid measure of household and leisure time functioning status in a low-income multiethnic HIV-positive population. Finally, structural equation modeling of the proximal-distal QOL model suggested that this model was not a viable representation of the relationship between the study variables in this patient population. ^