History of Medicine Schedule 2010-2011

William Osler (1849-1919): America’s Most Famous Physician (Robert E. Rakel) The Assassination of John F. Kennedy: A Neurosurgeon’s Eyewitness Account of the Medical Aspect of the Events of November 22, 1963 (Robert G. Grossman) Making Cancer History: Disease and Discovery at the University of Texas M.D. Anderson Cancer Center (James S. Olson) The History of Pathology as a Biological Science and Medical Specialty (L. Maximillian Buja) “Medicine in the Mid-19th Century America” (Student Essay Contest Winner) (David Hunter) The Achievements and Enduring Relevance of Rudolph Virchow (Nathan Grohmann) Medicine: Perspectives in History and Art (Robert E. Greenspan) What Every Physician Should Know: Lessons from the Past (Robert E. Greenspan) Medicine in Ancient Mesopotamia (Sajid Haque) The History of Texas Children’s Hospital (B. Lee Ligon) Visualizing Disease: Motion Pictures in the History of Medical Education (Kirsten Ostherr)

Baylor History of Medicine Society Schedule 2007-2008

"Medicine: Perspectives in History and Art" (Robert E. Greenspan) Eight Practical Lessons from Osler That Will Better Your Life (Bryan Boutwell) History of the American Mental Hospital: From networking to not working & Back (Ed Fann) Ambiguities and Amputations: Methods, mishaps, and the surgical quest to cure breast cancer (Student Essay Contest Winner) (Matt Luedke) An Automated, Algorithmic, Retrospective Analysis of the Growing Influence of Statistics in Medicine (Student Essay Contest Winner) (Ryan Rochat) What’s Special about William Osler? (Charles S. Bryan) The Virtuous Physician: Lessons from Medical Biography (Charles S. Bryan) Legacy: 50 Years of Loving Care – The History of Texas Children’s Hospital, 1954-2004 (Betsy Parish) The Education of a University President: Edgar Odell Lovett of Rice University (John B. Boles) Artists and Illness: The Effect of Illness on an Artist’s Work (David Bybee)

Outcome-based adaptive randomization for binary data in clinical trials---Compare and contrast

Monte Carlo simulation has been conducted to investigate parameter estimation and hypothesis testing in some well known adaptive randomization procedures. The four urn models studied are Randomized Play-the-Winner (RPW), Randomized Pôlya Urn (RPU), Birth and Death Urn with Immigration (BDUI), and Drop-the-Loses Urn (DL). Two sequential estimation methods, the sequential maximum likelihood estimation (SMLE) and the doubly adaptive biased coin design (DABC), are simulated at three optimal allocation targets that minimize the expected number of failures under the assumption of constant variance of simple difference (RSIHR), relative risk (ORR), and odds ratio (OOR) respectively. Log likelihood ratio test and three Wald-type tests (simple difference, log of relative risk, log of odds ratio) are compared in different adaptive procedures. ^ Simulation results indicates that although RPW is slightly better in assigning more patients to the superior treatment, the DL method is considerably less variable and the test statistics have better normality. When compared with SMLE, DABC has slightly higher overall response rate with lower variance, but has larger bias and variance in parameter estimation. Additionally, the test statistics in SMLE have better normality and lower type I error rate, and the power of hypothesis testing is more comparable with the equal randomization. Usually, RSIHR has the highest power among the 3 optimal allocation ratios. However, the ORR allocation has better power and lower type I error rate when the log of relative risk is the test statistics. The number of expected failures in ORR is smaller than RSIHR. It is also shown that the simple difference of response rates has the worst normality among all 4 test statistics. The power of hypothesis test is always inflated when simple difference is used. On the other hand, the normality of the log likelihood ratio test statistics is robust against the change of adaptive randomization procedures. ^

Campaign contributions to congressional candidates by the healthcare sector from 1990 to 2008

Stakeholder groups with special interests as donors to finance congressional campaigns have been a controversial issue in the United Sates. While previous studies concentrated on whether a connection existed between the campaign contributions provided by stakeholder groups and the voting behavior of congressional members, there is little evidence to show the trend of allocation of their campaign contributions to their favorite candidates during the elections. This issue has become increasingly important in the health sector since the health care reform bill was passed in early 2010.^ This study examined the long-term trend of campaign contributions offered by various top healthcare stakeholder groups to particular political parties (i.e. Democrat and Republican). The main focus of this paper was to observe and describe the financial donations provided by these healthcare stakeholder groups in the congressional election cycles from 1990 to 2008 in order to obtain an overview of their patterns of campaign contributions. Their contributing behaviors were characterized based on the campaign finance data collected by the Center for Responsive Politics (CRP). Specifically, I answered the questions: (1) to which political party did specific healthcare stakeholder groups give money and (2) what was the pattern of their campaign contributions from 1990 to 2008?^ The findings of my study revealed that the healthcare stakeholder groups had different political party preferences and partisanship orientations regarding the Democratic or Republican Party. These differences were obvious throughout the election cycles from 1990 to 2008 and their distinct patterns of financial contribution were evident across industries in the health sector as well. Among all the healthcare stakeholder groups in this study, physicians were the top contributors in the congressional election. The pharmaceutical industry was the only group where the majority of contribution funds were allocated to Republicans in every election period studied. This study found that no interest group has succeeded in electing the preferred congressional candidate by giving the majority of its financial support to the winning party in every election. Chiropractors, hospitals/nursing homes, and health services/HMOs performed better than other healthcare stakeholder groups by supporting the electoral winner 8 out of 9 election cycles.^