Publications

Neuropsychological (NP) impairments in human immunodeficiency virus (HIV)-infected individuals remain high despite the introduction of highly active antiretroviral therapy (HAART). We sought to determine whether or not a monocyte gene expression profile along with other peripheral factors would correlate with neuropsychological impairment among HIV-infected individuals. Forty-four HIV-1-seropositive subjects (HIV+) on HAART and 11 HIV-1-seronegative controls (HIV-) had NP testing and blood drawn for monocyte gene expression analysis. All HIV+ subjects were assessed for CD4 counts, apolipoprotein E (ApoE) genotype, viral load, and plasma lipopolysaccharide (LPS) and soluble CD14 (sCD14). NP scores were normalized to age, gender, and education. Twenty-five percent of HIV+ individuals showed abnormal NP testing results (> 1.5 SD below normal in two domains). HIV+ individuals had deficits in attention/working memory, verbal learning, and information processing speed compared to HIV- controls. There was no correlation between overall NP impairment and plasma viral load, level of education, age, ethnic diversity, sCD14, plasma LPS, CD4 cell count, ApoE genotype, or years of infection. However, greater years of infection had worse visual learning performance. sCD14 and CD4 nadir positively correlated with information processing speed and fine motor skills, respectively. LPS correlated with viral load but not cognitive impairment. Monocyte gene expression confirmed a chronic inflammatory profile that correlated with viral load but not cognition. No blood index or profile was associated with overall NP impairment.

Most California prisoners experience discontinuity of health care upon return to the community. In January 2006, physicians working with community organizations and representatives of the San Francisco Department of Public Health's safety-net health system opened the Transitions Clinic (TC) to provide transitional and primary care as well as case management for prisoners returning to San Francisco. This article provides a complete description of TC, including an illustrative case, and reports information about the recently released individuals who participated in the program. From January 2006 to October 2007, TC saw 185 patients with chronic medical conditions. TC patients are socially and economically disenfranchised; 86% belong to ethnic minority groups and 38% are homeless. Eighty-nine percent of patients did not have a primary care provider prior to their incarceration. Preliminary findings demonstrate that a community-based model of care tailored to this disenfranchised population successfully engages them in seeking health care.

BACKGROUND

Although residency programs must prepare physicians who can analyze and improve their practice, practice improvement (PI) is new for many faculty preceptors. We describe the pilot of a PI curriculum incorporating a practice improvement module (PIM) from the American Board of Internal Medicine for residents and their faculty preceptors.

METHODS

Residents attended PI didactics and completed a PIM during continuity clinic and outpatient months working in groups under committed faculty.

RESULTS

All residents participated in PI group projects. Residents agreed or strongly agreed that the projects and the curriculum benefited their learning and patient care. A self-assessment revealed significant improvement in PI competencies, but residents were just reaching a "somewhat confident" level.

CONCLUSION

A PI curriculum incorporating PIMs is an effective way to teach PI to both residents and faculty preceptors. We recommend the team approach and use of the PIM tutorial approach especially for faculty.

Human studies, encompassing interventional and observational studies, are the most important source of evidence for advancing our understanding of health, disease, and treatment options. To promote discovery, the design and results of these studies should be made machine-readable for large-scale data mining, synthesis, and re-analysis. The Human Studies Database Project aims to define and implement an informatics infrastructure for institutions to share the design of their human studies. We have developed the Ontology of Clinical Research (OCRe) to model study features such as design type, interventions, and outcomes to support scientific query and analysis. We are using OCRe as the reference semantics for federated data sharing of human studies over caGrid, and are piloting this implementation with several Clinical and Translational Science Award (CTSA) institutions.

An integrated data repository (IDR) containing aggregations of clinical, biomedical, economic, administrative, and public health data is a key component of an overall translational research infrastructure. But most available data repositories are designed using standard data warehouse architecture that employs arbitrary data encoding standards, making queries across disparate repositories difficult. In response to these shortcomings we have designed a Health Ontology Mapper (HOM) that translates terminologies into formal data encoding standards without altering the underlying source data. We believe the HOM system promotes inter-institutional data sharing and research collaboration, and will ultimately lower the barrier to developing and using an IDR.

Formal, computer-interpretable representations of eligibility criteria would allow computers to better support key clinical research and care use cases such as eligibility determination. To inform the development of such formal representations for eligibility criteria, we conducted this study to characterize and quantify the complexity present in 1000 eligibility criteria randomly selected from studies in ClinicalTrials.gov. We classified the criteria by their complexity, semantic patterns, clinical content, and data sources. Our analyses revealed significant semantic and clinical content variability. We found that 93% of criteria were comprehensible, with 85% of these criteria having significant semantic complexity, including 40% relying on temporal data. We also identified several domains of clinical content. Using the findings of the study as requirements for computer-interpretable representations of eligibility, we discuss the challenges for creating such representations for use in clinical research and practice.