John F. Hurdle

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OBJECTIVES We examine recent published research on the extraction of information from textual documents in the Electronic Health Record (EHR). METHODS Literature review of the research published after 1995, based on PubMed, conference proceedings, and the ACM Digital Library, as well as on relevant publications referenced in papers already included. (More)
BACKGROUND Numerous studies have shown that specific computerized interventions may reduce medication errors, but few have examined adverse drug events (ADEs) across all stages of the computerized medication process. We describe the frequency and type of inpatient ADEs that occurred following the adoption of multiple computerized medication ordering and(More)
OBJECTIVE To examine potential sources of errors at each step of the described inpatient International Classification of Diseases (ICD) coding process. DATA SOURCES/STUDY SETTING The use of disease codes from the ICD has expanded from classifying morbidity and mortality information for statistical purposes to diverse sets of applications in research,(More)
This paper reports on a shared task involving the assignment of emotions to suicide notes. Two features distinguished this task from previous shared tasks in the biomedical domain. One is that it resulted in the corpus of fully anonymized clinical text and annotated suicide notes. This resource is permanently available and will (we hope) facilitate future(More)
BACKGROUND Patients nearing end-stage renal disease (ESRD) increasingly choose pre-emptive renal transplant (PRT) to avoid pre-transplant dialysis and to minimize ESRD. Compared with long-term dialysis, PRT has been shown to increase allograft survival. However, the merit of short-term dialysis is not well characterized, and it may be the better medical(More)
BACKGROUND The effect of pretransplantation renal replacement therapy (RRT) modality on allograft and recipient survival outcome is not well understood. METHODS We studied allograft and recipient survival by using US Renal Data System records from January 1, 1990, to December 31, 1999, with a follow-up period through December 31, 2000 (n = 92,844; 60%(More)
High-performance computing centers (HPC) traditionally have far less restrictive privacy management policies than those encountered in healthcare. We show how an HPC can be re-engineered to accommodate clinical data while retaining its utility in computationally intensive tasks such as data mining, machine learning, and statistics. We also discuss deploying(More)
Methods for surveillance of adverse events (AEs) in clinical settings are limited by cost, technology, and appropriate data availability. In this study, two methods for semi-automated review of text records within the Veterans Administration database are utilized to identify AEs related to the placement of central venous catheters (CVCs): a Natural Language(More)
BACKGROUND Traditional information retrieval techniques typically return excessive output when directed at large bibliographic databases. Natural Language Processing applications strive to extract salient content from the excessive data. Semantic MEDLINE, a National Library of Medicine (NLM) natural language processing application, highlights relevant(More)
OBJECTIVES It is not uncommon that the introduction of a new technology fixes old problems while introducing new ones. The Veterans Administration recently implemented a comprehensive electronic medical record system (CPRS) to support provider order entry. Progress notes are entered directly by clinicians, primarily through keyboard input. Due to concerns(More)