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)

Caring Minds

Welcome from Dean Patricia Starck The Face of Health Care Leading Technology School of Nursing Collaborates to Initiate Texas Medical Center’s First Digital Repository Nursing Research, A Growing Field Nursing in the Wake of the Storm Profile: Huaping Liu, RN, PhD, Dean and Associate Professor, School of Nursing at Peking Union Medical College Newsbrief: Planning for the Future with a New Doctor of Nursing Practice Program in Fall 2006 Newsbrief: Fast Track Nursing Program Gives Students a Speedy Start Profile: Susan Bankston, RN, BSN, Psychiatric Nursing, Currently enrolled in the MSN to DSN track Newsbrief: University of Texas Health Services Reports Outstanding Achievements in FY’05 Student Grants Newsbrief: New Degree Program Develops Leadership and Business Skills for Today’s Nurses Profile: Pamela Klauer Triolo, PhD, RN, FAAN Clinical Professor of Nursing Director, Nursing Leadership and Administration in Health Systems Newsbrief: Successful Luncheon Completes $1 Million Endowment UT School of Nursing Building Recognized as Blending Form and Function Faculty Scholarship Endowed Faculty Positions

The cost of publicly financed dental care in relation to community water fluoridation in Texas

Dental caries lead to children being less ready to learn and results in diminished productivity in the classroom. Tooth decay causes pain and infection, leading to impaired chewing, speech, and facial expression, in addition to a loss in self-esteem. There have been many studies supporting the safety and efficacy of community water fluoridation in reducing dental caries. Water fluoridation has been identified by the Centers for Disease Control and Prevention as one of 10 great public health achievements of the 20th century. The decline in the prevalence and severity of tooth decay in the United States during the past 60 years has been attributed largely to the increased use of fluoride; in particular, the widespread utilization of community water fluoridation. However, in the decades since fluoridation was first introduced, reductions in dental caries have declined, most likely due to the presence of other sources of fluoride. Questions have been raised regarding the need to continue to fluoridate community water supplies in the face of possible excessive exposure to fluoride. Nevertheless, dental caries continue to be a significant public health burden throughout the world, including the United States, especially among low-income and disadvantaged populations. Although many poor children receive their dental care through Medicaid, the percentage of Texas children with untreated dental caries continues to exceed the U.S. average and is well above Healthy People 2010 goals, even as state Medicaid expenditures continue to rise. The objective of this study is to determine the relationship between Medicaid dental expenditures and community water fluoridation levels in Texas counties. By examining this relationship, the cost-effectiveness of community water fluoridation in the Texas pediatric Medicaid beneficiary population, as measured by publicly financed dental care expenditures, may be ascertained.^

A comparison of techniques for forecasting utilization of Veterans Affairs hospitals

This study demonstrated that accurate, short-term forecasts of Veterans Affairs (VA) hospital utilization can be made using the Patient Treatment File (PTF), the inpatient discharge database of the VA. Accurate, short-term forecasts of two years or less can reduce required inventory levels, improve allocation of resources, and are essential for better financial management. These are all necessary achievements in an era of cost-containment.^ Six years of non-psychiatric discharge records were extracted from the PTF and used to calculate four indicators of VA hospital utilization: average length of stay, discharge rate, multi-stay rate (a measure of readmissions) and days of care provided. National and regional levels of these indicators were described and compared for fiscal year 1984 (FY84) to FY89 inclusive.^ Using the observed levels of utilization for the 48 months between FY84 and FY87, five techniques were used to forecast monthly levels of utilization for FY88 and FY89. Forecasts were compared to the observed levels of utilization for these years. Monthly forecasts were also produced for FY90 and FY91.^ Forecasts for days of care provided were not produced. Current inpatients with very long lengths of stay contribute a substantial amount of this indicator and it cannot be accurately calculated.^ During the six year period between FY84 and FY89, average length of stay declined substantially, nationally and regionally. The discharge rate was relatively stable, while the multi-stay rate increased slightly during this period. FY90 and FY91 forecasts show a continued decline in the average length of stay, while the discharge rate is forecast to decline slightly and the multi-stay rate is forecast to increase very slightly.^ Over a 24 month ahead period, all three indicators were forecast within a 10 percent average monthly error. The 12-month ahead forecast errors were slightly lower. Average length of stay was less easily forecast, while the multi-stay rate was the easiest indicator to forecast.^ No single technique performed significantly better as determined by the Mean Absolute Percent Error, a standard measure of error. However, Autoregressive Integrated Moving Average (ARIMA) models performed well overall and are recommended for short-term forecasting of VA hospital utilization. ^