Prevalence of "one and done" phenomenon in adenoma detection within a large community-based healthcare system.

Background And Aims: Adenoma detection rate (ADR) is a key quality metric in colonoscopy, reflecting the ability to detect adenomas. However, concerns remain regarding the robustness of ADR as a benchmark. In particular, the "one and done" phenomenon may exist in which physicians are less motivated to find additional adenomas after discovery of the first adenoma.

History of Cholecystectomy and Risk of Clostridium Difficile Infection.

Background: Cholecystectomy affects bile acid physiology. There is growing evidence that both primary and secondary bile acids play a role in the pathogenesis of Clostridium difficile infections (CDIs).

Aims: The aim of this study is to elucidate the relationship and risk of CDI in patients with cholecystectomy.

Synergistic drug combinations from electronic health records and gene expression.

Objective: Using electronic health records (EHRs) and biomolecular data, we sought to discover drug pairs with synergistic repurposing potential. EHRs provide real-world treatment and outcome patterns, while complementary biomolecular data, including disease-specific gene expression and drug-protein interactions, provide mechanistic understanding.

Method: We applied Group Lasso INTERaction NETwork (glinternet), an overlap group lasso penalty on a logistic regression model, with pairwise interactions to identify variables and interacting drug pairs associated with reduced 5-year mortality using EHRs of 9945 breast cancer patients.

Use of Gene Expression Profiling and Chemotherapy in Early-Stage Breast Cancer: A Study of Linked Electronic Medical Records, Cancer Registry Data, and Genomic Data Across Two Health Care Systems.

Purpose: The 21-gene recurrence score (RS) identifies patients with breast cancer who derive little benefit from chemotherapy; it may reduce unwarranted variability in the use of chemotherapy. We tested whether the use of RS seems to guide chemotherapy receipt across different cancer care settings.

Methods: We developed a retrospective cohort of patients with breast cancer by using electronic medical record data from Stanford University (hereafter University) and Palo Alto Medical Foundation (hereafter Community) linked with demographic and staging data from the California Cancer Registry and RS results from the testing laboratory (Genomic Health Inc.

Breast cancer treatment across health care systems: linking electronic medical records and state registry data to enable outcomes research.

Background: Understanding of cancer outcomes is limited by data fragmentation. In the current study, the authors analyzed the information yielded by integrating breast cancer data from 3 sources: electronic medical records (EMRs) from 2 health care systems and the state registry.

Methods: Diagnostic test and treatment data were extracted from the EMRs of all patients with breast cancer treated between 2000 and 2010 in 2 independent California institutions: a community-based practice (Palo Alto Medical Foundation; "Community") and an academic medical center (Stanford University; "University").

Oncoshare: lessons learned from building an integrated multi-institutional database for comparative effectiveness research.

Comparative effectiveness research (CER) using observational data requires informatics methods for the extraction, standardization, sharing, and integration of data derived from a variety of electronic sources. In the Oncoshare project, we have developed such methods as part of a collaborative multi-institutional CER study of patterns, predictors, and outcome of breast cancer care. In this paper, we present an evaluation of the approaches we undertook and the lessons we learned in building and validating the Oncoshare data resource.