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You searched for +publisher:"Vanderbilt University" +contributor:("Melissa McPheeters"). Showing records 1 – 2 of 2 total matches.

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Vanderbilt University

1. Masterman, Clayton J. An Empirical Analysis of Policy Responses to the Opioid Epidemic.

Degree: PhD, Law and Economics, 2019, Vanderbilt University

This dissertation studies the relationship between state laws, federal regulations, and the ongoing opioid epidemic. Chapter one studies the effect of naloxone access laws on opioid overdoses. Using a richly detailed dataset, this chapter separately identifies the effects of different naloxone access provisions on different subpopulations of opioid users. The results demonstrate that loosening naloxone prescription requirements saves thousands of lives annually, particularly among illegal drug users in urban areas. Chapter two investigates the effect of the U.S. Food and Drug Administration’s 2014 boxed warnings on opioid prescriptions. The FDA required manufacturers of opioids to place a boxed warning on the drug labels of all extended release opioid products in April 2014. Using the language of the warning, this chapter explores how the warning affected opioid prescriptions among groups that the warning targeted. I find that the warning decreased prescriptions to repeat users of opioids by thirty-five percent, but did not affect prescriptions to relatively riskier opioid users or individuals that the warning specifically targeted. Finally, chapter three studies the relationship between fatal occupational injuries and opioid overdoses. I find consistent evidence that opioid abuse significantly increased fatal worker injuries, while finding no evidence that dangerous working conditions increase fatal opioid overdoses. Approximately 300 worker fatalities that occurred between 2006 and 2016 are attributable to opioid abuse. Advisors/Committee Members: Kevin Stack (committee member), Melissa McPheeters (committee member), Christopher Carpenter (committee member), W. Kip Viscusi (Committee Chair).

Subjects/Keywords: epidemic; naloxone; boxed warnings; occupational safety; health law; opioids

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

APA (6th Edition):

Masterman, C. J. (2019). An Empirical Analysis of Policy Responses to the Opioid Epidemic. (Doctoral Dissertation). Vanderbilt University. Retrieved from http://hdl.handle.net/1803/10697

Chicago Manual of Style (16th Edition):

Masterman, Clayton J. “An Empirical Analysis of Policy Responses to the Opioid Epidemic.” 2019. Doctoral Dissertation, Vanderbilt University. Accessed May 09, 2021. http://hdl.handle.net/1803/10697.

MLA Handbook (7th Edition):

Masterman, Clayton J. “An Empirical Analysis of Policy Responses to the Opioid Epidemic.” 2019. Web. 09 May 2021.

Vancouver:

Masterman CJ. An Empirical Analysis of Policy Responses to the Opioid Epidemic. [Internet] [Doctoral dissertation]. Vanderbilt University; 2019. [cited 2021 May 09]. Available from: http://hdl.handle.net/1803/10697.

Council of Science Editors:

Masterman CJ. An Empirical Analysis of Policy Responses to the Opioid Epidemic. [Doctoral Dissertation]. Vanderbilt University; 2019. Available from: http://hdl.handle.net/1803/10697


Vanderbilt University

2. Deppen, Stephen Andrew. Development of a lung cancer prediction model for surgeons and factors affecting its national application.

Degree: PhD, Epidemiology, 2013, Vanderbilt University

Lung cancer is deadly, killing more people than breast, colon and prostate cancer combined. Surgeons evaluating patients for lung cancer face a dilemma: to operate and subject the individual to operation associated mortality and morbidity or not operate and possibly miss early diagnosis and treatment. No models designed for surgeons evaluating lung lesions. We successfully estimated the TREAT model. A model designed for surgeons with an internally validated AUC of 0.87 and Brier score of 13. If the TREAT model is applied to a national population, its accuracy may decrease due to local conditions. To determine the possible extent of such variation, benign disease prevalence after lung surgery was estimated using 2009 Medicare hospital discharge data. Significant variation in benign disease prevalence between states was observed with a low of 1.3% in Vermont and a high of 25% in Hawaii. The causes for this observed variation are unknown. Residence in a county with high fungal lung disease prevalence was not associated with increased likelihood of benign disease. FDG-PET scan variance was observed in the national ACOGOS Z4031 trial. FDG-PET sensitivity (82%) and specificity (31%) were significantly lower than in previous published studies. Granuloma occurred in 68% of the false positive FDG-PET scans and sensitivity varied significantly between sites. Scan accuracy increased with increasing lung lesion size. Whether the observed variation is caused by practice variation, referral patterns, fungal lung disease, or other factors is unknown. A meta-analysis examined FDG-PET accuracy to diagnose lung lesions sought to determine if other researchers had observed variance in FDG-PET accuracy. Seven studies reported false positive scans arising from granulomas caused by infectious lung disease. Specificity of those studies was 59%, significantly lower than the specificity (77%) observed in the remaining 53 studies. Studies whose mean lesion size was less than or equal to 20 mm had significantly lower sensitivity than studies conducted in larger lesions. The TREAT model shows clinical promise and should be externally validated. The causes of observed variation in benign disease prevalence and FDG-PET accuracy should be investigated with particular attention made to measuring infectious disease exposures that cause granulomas. Advisors/Committee Members: Pierre P. Massion (committee member), Melissa McPheeters (committee member), Jeffrey Blume (committee member), Melinda Aldrich (committee member), Eric L. Grogan (Committee Chair).

Subjects/Keywords: lung cancer; diagnosis; surgery; predictive model; meta-analysis; epidemiology

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

APA (6th Edition):

Deppen, S. A. (2013). Development of a lung cancer prediction model for surgeons and factors affecting its national application. (Doctoral Dissertation). Vanderbilt University. Retrieved from http://hdl.handle.net/1803/12484

Chicago Manual of Style (16th Edition):

Deppen, Stephen Andrew. “Development of a lung cancer prediction model for surgeons and factors affecting its national application.” 2013. Doctoral Dissertation, Vanderbilt University. Accessed May 09, 2021. http://hdl.handle.net/1803/12484.

MLA Handbook (7th Edition):

Deppen, Stephen Andrew. “Development of a lung cancer prediction model for surgeons and factors affecting its national application.” 2013. Web. 09 May 2021.

Vancouver:

Deppen SA. Development of a lung cancer prediction model for surgeons and factors affecting its national application. [Internet] [Doctoral dissertation]. Vanderbilt University; 2013. [cited 2021 May 09]. Available from: http://hdl.handle.net/1803/12484.

Council of Science Editors:

Deppen SA. Development of a lung cancer prediction model for surgeons and factors affecting its national application. [Doctoral Dissertation]. Vanderbilt University; 2013. Available from: http://hdl.handle.net/1803/12484

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