Faculty Bibliography

Several training programs in biomedical informatics in the United States are attempting to integrate biological and clinical informatics. However, significant differences in the cultures underlying these two disciplines pose barriers to a uniform educational solution. This paper recounts the experience at Columbia University in adapting a graduate program with an initial focus on clinical informatics to train bioinformaticians. The analysis begins by considering the development of the medical and biological informatics cultures over a 17-year period. Then we review how two separate curricula evolved to serve the needs of each group. Interviews with bioinformatics students and faculty indicated some dissatisfaction with the curriculum that developed within clinical informatics. Their comments are considered in the light of an analysis of the relationship between the application domains of biomedical informatics as a discipline. In response, a new curriculum was developed in which bioinformatics and clinical informatics are regarded as subdivisions of the same subject. A key feature of this curriculum is a new course, Theory and Methods in Biomedical Informatics, which presents informatics principles in their general form, and illustrates their application with examples drawn from across the biomedical spectrum. The paper concludes with suggestions for integrating informatics training programs at other institutions.

One of the goals of the NIH Roadmap Initiative is to re-engineer the national clinical research enterprise, with an emphasis on information technology solutions. Understanding end-users' workflow is critical to developing technology systems that are grounded in the context of the users' environment and are designed to fulfill their needs. Community practices are becoming the prevailing setting for conducting clinical research. Few studies have assessed clinical research workflow in such settings. We have conducted a series of investigations to model the workflow and have previously reported on some basic aspects of it, like the lack of information systems to support the workflow. In this paper we describe finer details of the workflow, using results of observational studies. These findings highlight the needs and inefficiencies that suggest the kind of information system that must be developed to enhance collaboration, communication and improve efficiency. This preliminary investigation also opens ground for more extensive studies to further elucidate the workflow.

The future success of the translational research spectrum depends on the clinical research enterprise's ability to break through the barriers that constrain its productivity. As more basic science discoveries emerge, our ability to effectively translate this knowledge into improved patient care rests squarely on the manner in which we answer clinical questions. Informatics--the science of effective information use--is poised to help advance the conduct of science. However, incorporating informatics into the enterprise comes with its own set of challenges. To harness the benefits of improved information use, it is important to first establish how information flows within research. A thoughtful implementation of informatics--one that factors in social and organizational nuances--will undoubtedly lead to a more efficient and effective clinical research enterprise.

During the past several years, social network analysis methods have been used to model many complex real-world phenomena, including social networks, transportation networks, and the Internet. Graph theoretic methods, based on an elegant representation of entities and relationships, have been used in computational biology to study biological networks; however they have not yet been adopted widely by the greater informatics community. The graphs produced are generally large, sparse, and complex, and share common global topological properties. In this review of research (1998-2005) on large-scale semantic networks, we used a tailored search strategy to identify articles involving both a graph theoretic perspective and semantic information. Thirty-one relevant articles were retrieved. The majority (28, 90.3%) involved an investigation of a real-world network. These included corpora, thesauri, dictionaries, large computer programs, biological neuronal networks, word association networks, and files on the Internet. Twenty-two of the 28 (78.6%) involved a graph comprised of words or phrases. Fifteen of the 28 (53.6%) mentioned evidence of small-world characteristics in the network investigated. Eleven (39.3%) reported a scale-free topology, which tends to have a similar appearance when examined at varying scales. The results of this review indicate that networks generated from natural language have topological properties common to other natural phenomena. It has not yet been determined whether artificial human-curated terminology systems in biomedicine share these properties. Large network analysis methods have potential application in a variety of areas of informatics, such as in development of controlled vocabularies and for characterizing a given domain.

The use of nursing documents from different electronic health record (EHR) systems is challenging due to inconsistency in document naming across systems and institutions. Mapping each local document name to standard document ontology may enable health care professionals to navigate and retrieve documents efficiently for multiple purposes such as quality assurance, outcomes research or public health reporting. The purpose of this study was to evaluate the sufficiency of the Health Level 7 (HL7)/Logical Observation Identifiers, Names, and Codes (LOINC) document ontology for representing nursing document names. We collected 94 nursing document types from the Eclipsys Clinical Information System (CIS) and the Columbia Medical Entities Dictionary (MED) and mapped them to the components of the HL7/LOINC document ontology. Seventy-five (79.8%) nursing document names were completely represented and 19 (20.2%) document names were partially represented. In order for the HL7/LOINC document ontology to be of more use in implementing EHRs that support nursing documentation, Subject Matter Domain and Type of Service axes require extension and clarification.

Temporal information plays a critical role in the understanding of clinical narrative (i.e., free text). We developed a representation for marking up temporal information in a narrative, consisting of five elements: 1) reference point, 2) direction, 3) number, 4) time unit, and 5) pattern. We identified 254 temporal expressions from 50 discharge summaries and represented them using our scheme. The overall inter-rater reliability among raters applying the representation model was 75 percent agreement. The model can contribute to temporal reasoning in computer systems for decision support, data mining, and process and outcomes analyses by providing structured temporal information.

Clinical research is vital to the translation of biomedical knowledge into standard clinical practice. Efforts are underway under the NIH Roadmap initiative to re-engineer the national research enterprise to sustain the rapid pace of innovation in the biomedical domain. As part of these efforts, we have embarked on an empirical evaluation of clinical research workflow in community practice settings. The reasons for this focus are three-fold. First, there is an increasing tendency by trial sponsors to conduct clinical trials in community, rather than academic, settings. Second, understanding workflow is critical to developing re-engineering strategies. Third, workflow associated with the conduct of clinical research in community practices have received virtually no attention in the scientific literature. In this paper, we describe a pilot study using time-motion observations, to determine the workflow of clinical research coordinators, the tools they use to conduct the constituent activities of those workflows, and their ultimate outcomes. The preliminary findings provide insights and understanding of clinical research workflow in community practice settings - knowledge that may significantly impact the way in which information technology based re-engineering can be deployed in such an environment.

eNote is an electronic health record (EHR) system based on semi-structured narrative documents. A heuristic evaluation was conducted with a sample of five usability experts. eNote performed highly in: 1)consistency with standards and 2)recognition rather than recall. eNote needs improvement in: 1)help and documentation, 2)aesthetic and minimalist design, 3)error prevention, 4)helping users recognize, diagnosis, and recover from errors, and 5)flexibility and efficiency of use. The heuristic evaluation was an efficient method of evaluating our interface.

Natural language processing (NLP) systems have demonstrated utility in parsing narrative texts for purposes such as surveillance and decision support. However, there has been little work related to NLP of nursing narratives. The purpose of this study was to compare the semantic categories of a NLP system (Medical Language Extraction and Encoding [MedLEE] system) with the semantic domains, categories, and attributes of the International Standards Organization (ISO) reference terminology models for nursing diagnoses and nursing actions. All but two MedLEE diagnosis and procedure-related semantic categories mapped to ISO models. In some instances, we found exact correspondence between the semantic structures of MedLEE and the ISO models. In other situations (e.g. aspects of Site or Location), the ISO model was not as granular as MedLEE. For clinical procedure and non-invasive examination, two ISO nursing action model components (Action and Target) mapped to a single MedLEE semantic category. The ISO models are applicable to NLP of nursing narratives. However, the ISO models require additional specification of selected semantic categories for the abstract semantic domains in order to achieve the objective of using NLP to parse and encode data from nursing narratives. Our analysis also suggests areas for extension of MedLEE particularly in regard to represent nursing actions.

The conduct of translational health research has become a vital national enterprise. However, multiple barriers prevent the effective translation of basic science discoveries into clinical and community practice. New information technology (IT) applications could help address these barriers. Unfortunately, owing to a combination of organizational, technical, and social factors, neither physician-investigators and research staff nor their clinical and community counterparts have harnessed such applications. Recently, at the request of the Institute of Medicine's Clinical Research Roundtable, a qualitative study of these factors was conducted at several leading academic medical centers. We explore the current status of IT in the translational research domain, describe the qualitative results, and conclude with a proposed set of initiatives to further increase the integration of IT into translational research.