Three-dimensional electron beam dose calculations

The MDAH pencil-beam algorithm developed by Hogstrom et al (1981) has been widely used in clinics for electron beam dose calculations for radiotherapy treatment planning. The primary objective of this research was to address several deficiencies of that algorithm and to develop an enhanced version. Two enhancements have been incorporated into the pencil-beam algorithm; one models fluence rather than planar fluence, and the other models the bremsstrahlung dose using measured beam data. Comparisons of the resulting calculated dose distributions with measured dose distributions for several test phantoms have been made. From these results it is concluded (1) that the fluence-based algorithm is more accurate to use for the dose calculation in an inhomogeneous slab phantom, and (2) the fluence-based calculation provides only a limited improvement to the accuracy the calculated dose in the region just downstream of the lateral edge of an inhomogeneity. The source of the latter inaccuracy is believed primarily due to assumptions made in the pencil beam's modeling of the complex phantom or patient geometry.^ A pencil-beam redefinition model was developed for the calculation of electron beam dose distributions in three dimensions. The primary aim of this redefinition model was to solve the dosimetry problem presented by deep inhomogeneities, which was the major deficiency of the enhanced version of the MDAH pencil-beam algorithm. The pencil-beam redefinition model is based on the theory of electron transport by redefining the pencil beams at each layer of the medium. The unique approach of this model is that all the physical parameters of a given pencil beam are characterized for multiple energy bins. Comparisons of the calculated dose distributions with measured dose distributions for a homogeneous water phantom and for phantoms with deep inhomogeneities have been made. From these results it is concluded that the redefinition algorithm is superior to the conventional, fluence-based, pencil-beam algorithm, especially in predicting the dose distribution downstream of a local inhomogeneity. The accuracy of this algorithm appears sufficient for clinical use, and the algorithm is structured for future expansion of the physical model if required for site specific treatment planning problems. ^

Evaluating the impact of vertical integration on health system peformance

Vertical integration is grounded in economic theory as a corporate strategy for reducing cost and enhancing efficiency. There were three purposes for this dissertation. The first was to describe and understand vertical integration theory. The review of the economic theory established vertical integration as a corporate cost reduction strategy in response to environmental, structural and performance dimensions of the market. The second purpose was to examine vertical integration in the context of the health care industry, which has greater complexity, higher instability, and more unstable demand than other industries, although many of the same dimensions of the market supported a vertical integration strategy. Evidence on the performance of health systems after integration revealed mixed results. Because the market continues to be turbulent, hybrid non-owned integration in the form of alliances have increased to over 40% of urban hospitals. The third purpose of the study was to examine the application of vertical integration in health care and evaluate the effects. The case studied was an alliance formed between a community hospital and a tertiary medical center to facilitate vertical integration of oncology services while maintaining effectiveness and preserving access. The economic benefits for 1934 patients were evaluated in the delivery system before and after integration with a more detailed economic analysis of breast, lung, colon/rectal, and non-malignant cases. A regression analysis confirmed the relationship between the independent variables of age, sex, location of services, race, stage of disease, and diagnosis, and the dependent variable, cost. The results of the basic regression model, as well as the regression with first-order interaction terms, were statistically significant. The study shows that vertical integration at an intermediate health care system level has economic benefits. If the pre-integration oncology group had been treated in the post-integration model, the expected cost savings from integration would be 31.5%. Quality indicators used were access to health care services and research treatment protocols, and access was preserved in the integrated model. Using survival as a direct quality outcome measure, the survival of lung cancer patients was statistically the same before and after integration. ^