The Houston Academy of Medicine--Texas Medical Center Library management information system.

A management information system (MIS) provides a means for collecting, reporting, and analyzing data from all segments of an organization. Such systems are common in business but rare in libraries. The Houston Academy of Medicine-Texas Medical Center Library developed an MIS that operates on a system of networked IBM PCs and Paradox, a commercial database software package. The data collected in the system include monthly reports, client profile information, and data collected at the time of service requests. The MIS assists with enforcement of library policies, ensures that correct information is recorded, and provides reports for library managers. It also can be used to help answer a variety of ad hoc questions. Future plans call for the development of an MIS that could be adapted to other libraries' needs, and a decision-support interface that would facilitate access to the data contained in the MIS databases.

Predictive validity of the personal background and preparation survey and effectiveness of targeted interventions among health science community college students

Existing data, collected from 1st-year students enrolled in a major Health Science Community College in the south central United States, for Fall 2010, Spring 2011, Fall 2011 and Spring 2012 semesters as part of the "Online Navigational Assessment Vehicle, Intervention Guidance, and Targeting of Risks (NAVIGATOR) for Undergraduate Minority Student Success" with CPHS approval number HSC-GEN-07-0158, was used for this thesis. The Personal Background and Preparation Survey (PBPS) and a two-question risk self-assessment subscale were administered to students during their 1st-year orientation. The PBPS total risk score, risk self-assessment total and overall scores, and Under Representative Minority Student (URMS) status were recorded. The purpose of this study is to evaluate and report the predictive validity of the indicators identified above for Adverse Academic Status Events (AASE) and Nonadvancement Adverse Academic Status Events (NAASE) as well as the effectiveness of interventions targeted using the PBPS among a diverse population of health science community college students. The predictive validity of the PBPS for AASE has previously been demonstrated among health science professions and graduate students (Johnson, Johnson, Kim, & McKee, 2009a; Johnson, Johnson, McKee, & Kim, 2009b). Data will be analyzed using binary logistic regression and correlation using SPSS 19 statistical package. Independent variables will include baseline- versus intervention-year treatments, PBPS, risk self-assessment, and URMS status. The dependent variables will be binary AASE and NAASE status. ^ The PBPS was the first reliable diagnostic and prescriptive instrument to establish documented predictive validity for student Adverse Academic Status Events (AASE) among students attending health science professional schools. These results extend the documented validity for the PBPS in predicting AASE to a health science community college student population. Results further demonstrated that interventions introduced using the PBPS were followed by approximately one-third reduction in the odds of Nonadvancement Adverse Academic Status Events (NAASE), controlling for URMS status and risk self-assessment scores. These results indicate interventions introduced using the PBPS may have potential to reduce AASE or attrition among URMS and nonURMS attending health science community colleges on a broader scale; positively impacting costs, shortages, and diversity of health science professionals.^

A feasibility study for assessing building occupants' indoor air quality expectations compared to nationally recognized standards

Indoor Air Quality (IAQ) can have significant implications for health, productivity, job performance, and operating cost. Professional experience in the field of indoor air quality suggests that high expectations (better than nationally established standards) (American Society of Heating, Refrigerating, and Air-conditioning Engineers (ASHRAE)) of workplace indoor air quality lead to increase air quality complaints. To determine whether there is a positive association between expectations and indoor air quality complaints, a one-time descriptive and analytical cross-sectional pilot study was conducted. Area Safety Liaisons (n = 330) at University of Texas Health Science Center – Houston were asked to answer a questionnaire regarding their expectations of four workplace indoor air quality indicators i.e., (temperature, relative humidity, carbon dioxide, and carbon monoxide) and if they experienced and reported indoor air quality problems. A chi-square test for independence was used to evaluate associations among the variables of interest. The response rate was 54% (n = 177). Results did not show significant associations between expectation and indoor air quality. However, a greater proportion of Area Safety Liaisons who expected indoor air quality indicators to be better than the established standard experienced greater indoor air quality problems. Similarly, a slightly higher proportion of Area Liaisons who expected indoor air quality indicators to be better than the standard reported greater indoor air quality complaints. ^ The findings indicated that a greater proportion of Area Safety Liaisons with high expectations (conditions that are beyond what is considered normal and acceptable by ASHRAE) experienced greater indoor air quality discomfort. This result suggests a positive association between high expectations and experienced and reported indoor air quality complaints. Future studies may be able to address whether the frequency of complaints and resulting investigations can be reduced through information and education about what are acceptable conditions.^

Introduction to E-Science

An introduction to computationally-enabled science, challenges, and opportunities.

Data Management Policies and Issues with Life Science Data

Data management and sharing are relatively new concepts in the health and life sciences fields. This presentation will cover some basic policies as well as the impediments to data sharing unique to health and life sciences data.

Compliance: E-Science Mandates and Policies

Data collected under federally funded research is subject to compliance rules and regulations. Policies affecting what you can and cannot do with your data, who is responsible, and what role your institution plays can vary with funding agencies and the type of data collected. This talk will address many of the compliance issues associated with research data, as well as funder mandates that you need to be aware of to ensure compliance.