Interview with Anna Steinberger

An oral interview with Dr. Anna Steinberger, who taught and conducted basic research in Reproductive Biology and served as Assistant Dean for Faculty Affairs at UT Medical School-Houston. Her research yielded over 250 scientific articles, books, and book chapters for which she received numerous awards and recognitions in the USA and abroad.

The Critical Friends Group: An Innovative Way to Build Intercultural Competence Among Student and Faculty Groups

Introduction Few physicians involved in medical education are likely to have had formal training in teaching. One pedagogical method that can enhance relationships, thus improve teaching and learning is the Critical Friends Group (CFG). The CFG is a collegial support team that offers improved understanding of others. Unconditional high regard for team members frames the interactions in the CFG. These teams could be used to reduce bias and enhance intercultural competence among student CFGs and faculty CFGs. [See PDF for complete abstract]

Citation analysis of faculty publication: beyond Science Citation Index and Social Science Citation Index.

When evaluated for promotion or tenure, faculty members are increasingly judged more on the quality than on the quantity of their scholarly publications. As a result, they want help from librarians in locating all citations to their published works for documentation in their curriculum vitae. Citation analysis using Science Citation Index and Social Science Citation Index provides a logical starting point in measuring quality, but the limitations of these sources leave a void in coverage of citations to an author's work. This article discusses alternative and additional methods of locating citations to published works.

Risk factors for Clostridium difficile nosocomial diarrhea in patients at the Michael E. Debakey Veterans Affairs Medical Center, Houston, Texas

Background. Clostridium difficile is the leading cause of hospital associated infectious diarrhea and colitis. About 3 million cases of Clostridium difficile diarrhea occur each year with an annual cost of $1 billion. ^ About 20% of patients acquire C. difficile during hospitalization. Infection with Clostridium difficile can result in serious complications, posing a threat to the patient's life. ^ Purpose. The aim of this research was to demonstrate the uniqueness in the characteristics of C. difficile positive nosocomial diarrhea cases compared with C. difficile negative nosocomial diarrhea controls admitted to a local hospital. ^ Methods. One hundred and ninety patients with a positive test and one hundred and ninety with a negative test for Clostridium difficile nosocomial diarrhea, selected from patients tested between January 1, 2002 and December 31, 2003, comprised the study population. Demographic and clinical data were collected from medical records. Logistic regression analyses were conducted to determine the associated odds between selected variables and the outcome of Clostridium difficile nosocomial diarrhea. ^ Results. For the antibiotic classes, cephalosporins (OR, 1.87; CI 95, 1.23 to 2.85), penicillins (OR, 1.57; CI 95, 1.04 to 2.37), fluoroquinolones (OR, 1.65; CI 95, 1.09 to 2.48) and antifungals (OR, 2.17; CI 95, 1.20 to 3.94), were significantly associated with Clostridium difficile nosocomial diarrhea Ceftazidime (OR, 1.95; CI 95, 1.25 to 3.03, p=0.003), gatifloxacin (OR, 1.97; CI 95, 1.31 to 2.97, p=0.001), clindamycin (OR, 3.13; CI 95, 1.99 to 4.93, p<0.001) and vancomycin (OR, 1.77; CI 95, 1.18 to 2.66, p=0.006, were also significantly associated with the disease. Vancomycin was not statistically significant when analyzed in a multivariable model. Other significantly associated drugs were, antacids, laxatives, narcotics and ranitidine. Prolong use of antibiotics and an increased number of comorbid conditions were also associated with C. difficile nosocomial diarrhea. ^ Conclusion. The etiology for C. difficile diarrhea is multifactorial. Exposure to antibiotics and other drugs, prolonged antibiotic usage, the presence and severity of comorbid conditions and prolonged hospital stay were shown to contribute to the development of the disease. It is imperative that any attempt to prevent the disease, or contain its spread, be done on several fronts. ^

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. ^