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You searched for +publisher:"Georgia Tech" +contributor:("Griffin, Susan"). Showing records 1 – 2 of 2 total matches.

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1. Johnson, Benjamin J. Evaluating policy decisions in health systems.

Degree: PhD, Industrial and Systems Engineering, 2017, Georgia Tech

This thesis focuses on four policy decisions relevant in health systems today: (i) the impact of geographic distance to care on patients with cystic fibrosis, (ii) the impact of global health supply chain design on the health outcomes where they operate, (iii) the impact of three interventions to improve access to pediatric preventive dental care, and (iv) the cost effectiveness of using silver diamine for treating caries in young children. Chapter 2 evaluates the impact of geographic distance from cystic fibrosis centers on lung function in patients with cystic fibrosis. Clinical patient-level data on 20,351 patients for years 1986-2011 are evaluated from the Cystic Fibrosis Foundation National Patient Registry. Distance is measured using a patient’s zip code centroid to the center where they received care. A heteroscedastic mixed effects model is used to capture the association of distance with longitudinal variation in patients’ lung function. Chapter 3 includes a study of the USAID malaria supply chain design in the context of the health outcomes in each of the counties it operates. Malaria is a life-threatening mosquito-borne infectious disease that causes fevers, chills, and vomiting. Sub-Saharan Africa is both resource-constrained and has 90 percent of malaria related deaths. To combat the disease, global health agencies including USAID provide commodities necessary to prevent and treat malaria. The supply chain systems at these organizations are integral to the success of programs aimed to combat malaria. Using publically available data regarding malaria, global development, and the USAID malaria supply chain, the impact of funding levels, supply chain performance, and other global development and malaria indicators on malaria mortality are determined. Linear regression is used to determine if there is a significant association between supply chain factors and malaria health. Chapters 4 and 5 evaluate the existing state of access to preventive oral health in Georgia and three policy interventions to improve access to dental care for children in Georgia: i) loan repayment programs ii) revising Medicaid fee-for-service rates, and iii) changing dental hygienist supervision requirements. Met need, cost savings of preventive care, and the cost of implementation are estimated for the three interventions. Chapter 6 determines the cost saving potential and cost effectiveness of using silver diamine fluoride (SDF) to treat caries in young children. SDF is a cheap alternative to traditional restorative care. While it does not have the ability to restore the tooth completely, it provides a valuable treatment option for young children by potentially arresting the caries in affected primary teeth until are replaced with healthy permanent teeth. This study evaluates the potential of this treatment option using a simulation approach with costs based on the realized costs of Medicaid treatments. Advisors/Committee Members: Serban, Nicoleta (advisor), Swann, Julie L. (advisor), Griffin, Paul M. (committee member), Griffin, Susan (committee member), Sokol, Joel (committee member).

Subjects/Keywords: Health policy; Humanitarian logistics; Cystic fibrosis; Preventive care; Oral health; Silver diamine fluoride; Supply chain; Healthcare supply chain

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Johnson, B. J. (2017). Evaluating policy decisions in health systems. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/58720

Chicago Manual of Style (16th Edition):

Johnson, Benjamin J. “Evaluating policy decisions in health systems.” 2017. Doctoral Dissertation, Georgia Tech. Accessed January 24, 2020. http://hdl.handle.net/1853/58720.

MLA Handbook (7th Edition):

Johnson, Benjamin J. “Evaluating policy decisions in health systems.” 2017. Web. 24 Jan 2020.

Vancouver:

Johnson BJ. Evaluating policy decisions in health systems. [Internet] [Doctoral dissertation]. Georgia Tech; 2017. [cited 2020 Jan 24]. Available from: http://hdl.handle.net/1853/58720.

Council of Science Editors:

Johnson BJ. Evaluating policy decisions in health systems. [Doctoral Dissertation]. Georgia Tech; 2017. Available from: http://hdl.handle.net/1853/58720

2. Hamilton, Erin Kinzel. Multiscale and meta-analytic approaches to inference in clinical healthcare data.

Degree: PhD, Biomedical Engineering, 2013, Georgia Tech

The field of medicine is regularly faced with the challenge of utilizing information that is complicated or difficult to characterize. Physicians often must use their best judgment in reaching decisions or recommendations for treatment in the clinical setting. The goal of this thesis is to use innovative statistical tools in tackling three specific challenges of this nature from current healthcare applications. The first aim focuses on developing a novel approach to meta-analysis when combining binary data from multiple studies of paired design, particularly in cases of high heterogeneity between studies. The challenge is in properly accounting for heterogeneity when dealing with a low or moderate number of studies, and with a rarely occurring outcome. The proposed approach uses a Rasch model for translating data from multiple paired studies into a unified structure that allows for properly handling variability associated with both pair effects and study effects. Analysis is then performed using a Bayesian hierarchical structure, which accounts for heterogeneity in a direct way within the variances of the separate generating distributions for each model parameter. This approach is applied to the debated topic within the dental community of the comparative effectiveness of materials used for pit-and-fissure sealants. The second and third aims of this research both have applications in early detection of breast cancer. The interpretation of a mammogram is often difficult since signs of early disease are often minuscule, and the appearance of even normal tissue can be highly variable and complex. Physicians often have to consider many important pieces of the whole picture when trying to assess next steps. The final two aims focus on improving the interpretation of findings in mammograms to aid in early cancer detection. When dealing with high frequency and irregular data, as is seen in most medical images, the behaviors of these complex structures are often difficult or impossible to quantify by standard modeling techniques. But a commonly occurring phenomenon in high-frequency data is that of regular scaling. The second aim in this thesis is to develop and evaluate a wavelet-based scaling estimator that reduces the information in a mammogram down to an informative and low-dimensional quantification of the innate scaling behavior, optimized for use in classifying the tissue as cancerous or non-cancerous. The specific demands for this estimator are that it be robust with respect to distributional assumptions on the data, and with respect to outlier levels in the frequency domain representation of the data. The final aim in this research focuses on enhancing the visualization of microcalcifications that are too small to capture well on screening mammograms. Using scale-mixing discrete wavelet transform methods, the existing detail information contained in a very small and course image will be used to impute scaled details at finer levels. These "informed" finer details will then be used to produce an image of… Advisors/Committee Members: Vidakovic, Brani (Committee Chair), Griffin, Paul (Committee Co-Chair), Goldsman, David (Committee Member), Griffin, Susan (Committee Member), Kemp, Melissa (Committee Member).

Subjects/Keywords: Rasch model; Bayesian hierarchical model; Paired data; Meta-analysis; Heterogeneity; Scale-mixing wavelet transform; Sampling distribution; Bootstrapping; Dental sealants; Waveletes; Spectral tools; Breast cancer; Scaling; Wavelet spectra; Weighted regression; Theil; Microcalcification; Diagnostic classification; Image enhancement; Rasch models; Item response theory; Sampling (Statistics); Bootstrap (Statistics)

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Hamilton, E. K. (2013). Multiscale and meta-analytic approaches to inference in clinical healthcare data. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/47600

Chicago Manual of Style (16th Edition):

Hamilton, Erin Kinzel. “Multiscale and meta-analytic approaches to inference in clinical healthcare data.” 2013. Doctoral Dissertation, Georgia Tech. Accessed January 24, 2020. http://hdl.handle.net/1853/47600.

MLA Handbook (7th Edition):

Hamilton, Erin Kinzel. “Multiscale and meta-analytic approaches to inference in clinical healthcare data.” 2013. Web. 24 Jan 2020.

Vancouver:

Hamilton EK. Multiscale and meta-analytic approaches to inference in clinical healthcare data. [Internet] [Doctoral dissertation]. Georgia Tech; 2013. [cited 2020 Jan 24]. Available from: http://hdl.handle.net/1853/47600.

Council of Science Editors:

Hamilton EK. Multiscale and meta-analytic approaches to inference in clinical healthcare data. [Doctoral Dissertation]. Georgia Tech; 2013. Available from: http://hdl.handle.net/1853/47600

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