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Clinical research informatics: a conceptual perspective

JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 2012年第E1期19卷 E36-E42页

作者： Kahn, Michael G. Weng, Chunhua Univ Colorado Dept Pediat Aurora CO USA Columbia Univ Dept Biomed Informat New York NY USA

Clinical research informatics is the rapidly evolving sub-discipline within biomedical informatics that focuses on developing new informatics theories, tools, and solutions to accelerate the full translational continuum: basic research to clinical trials (T1), clinical trials to academic health center practice (T2), diffusion and implementation to community practice (T3), and 'real world' outcomes (T4). We present a conceptual model based on an informatics-enabled clinical research workflow, integration across heterogeneous data sources, and core informatics tools and platforms. We use this conceptual model to highlight 18 new articles in the JAMIA special issue on clinical research informatics.

关键词： Clinical research informatics clinical and translational research visualization of data and knowledge knowledge representations methods for integration of information from disparate sources data models data exchange knowledge bases knowledge acquisition knowledge acquisition and knowledge management

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Clinical utility of sequence-based genotype compared with that derivable from genotyping arrays

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JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 2012年第E1期19卷 E21-E27页

作者： Morgan, Alexander A. Chen, Rong Butte, Atul Janardhan Stanford Univ Dept Biochem Stanford Genome Technol Ctr Stanford CA 94305 USA Stanford Univ Dept Pediat Div Syst Med Biomed Informat Grad Training Program Stanford CA 94305 USA Lucile Packard Childrens Hosp Palo Alto CA USA

Objective We investigated the common-disease relevant information obtained from sequencing compared with that reported from genotyping arrays. Materials and methods Using 187 publicly available individual human genomes, we constructed genomic disease risk summaries based on 55 common diseases with reported gene-disease associations in the research literature using two different risk models, one based on the product of likelihood ratios and the other on the allelic variant with the maximum associated disease risk. We also constructed risk profiles based on the single nucleotide polymorphisms (SNPs) of these individuals that could be measured or imputed from two common genotyping array platforms. Results We show that the model risk predictions derived from sequencing differ substantially from those obtained from the SNPs measured on commercially available genotyping arrays for several different non-monogenic diseases, although high density genotyping arrays give identical results for many diseases. Conclusions Our approach may be used to compare the ability of different platforms to probe known genetic risks disease by disease.

关键词： genomic medicine personalized medicine genotyping sequencing modeling physiologic and disease processes linking the genotype and phenotype identifying genome and protein structure and function visualization of data and knowledge

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Using the time and motion method to study clinical work processes and workflow: methodological inconsistencies and a call for standardized research

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JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 2011年第5期18卷 704-710页

作者： Zheng, Kai Guo, Michael H. Hanauer, David A. Univ Michigan Sch Publ Hlth Dept Hlth Management & Policy Ann Arbor MI 48109 USA Univ Michigan Sch Informat Ann Arbor MI 48109 USA Univ Florida Coll Med Gainesville FL USA Univ Michigan Dept Pediat Ann Arbor MI 48109 USA Univ Michigan Ctr Comprehens Canc Ann Arbor MI 48109 USA

Objective To identify ways for improving the consistency of design, conduct, and results reporting of time and motion (TEM) research in health informatics. Materials and methods We analyzed the commonalities and divergences of empirical studies published 1990-2010 that have applied the T&M approach to examine the impact of health IT implementation on clinical work processes and workflow. The analysis led to the development of a suggested 'checklist' intended to help future T&M research produce compatible and comparable results. We call this checklist STAMP (Suggested Time And Motion Procedures). Results STAMP outlines a minimum set of 29 data/information elements organized into eight key areas, plus three supplemental elements contained in an 'Ancillary data' area, that researchers may consider collecting and reporting in their future T&M endeavors. Discussion TEM is generally regarded as the most reliable approach for assessing the impact of health IT implementation on clinical work. However, there exist considerable inconsistencies in how previous TEN studies were conducted and/or how their results were reported, many of which do not seem necessary yet can have a significant impact on quality of research and generalisability of results. Therefore, we deem it is time to call for standards that can help improve the consistency of TEN research in health informatics. This study represents an initial attempt. Conclusion We developed a suggested checklist to improve the methodological and results reporting consistency of T&M research, so that meaningful insights can be derived from across-study synthesis and health informatics, as a field, will be able to accumulate knowledge from these studies.

关键词： Time and motion studies (F02.784.412.846.707) workflow (L01.906.893) health information technology (L01.700) medical informatics applications (L01.700.508) collaborative technologies personal health records and self-care systems developing/using clinical decision support (other than diagnostic) and guideline systems systems supporting patient-provider interaction human-computer interaction and human-centered computing improving healthcare workflow and process efficiency system implementation and management issues social/organizational study qualitative/ethnographic field study cognitive study (including experiments emphasizing verbal protocol analysis and usability) methods for integration of information from disparate sources information storage and retrieval (text and images) data exchange communication integration across care settings (inter- and intra-enterprise) visualization of data and knowledge developing/using computerized provider order entry

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Handling anticipated exceptions in clinical care: investigating clinician use of 'exit strategies' in an electronic health records system

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JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 2011年第6期18卷 883-889页

作者： Zheng, Kai Hanauer, David A. Padman, Rema Johnson, Michael P. Hussain, Anwar A. Ye, Wen Zhou, Xiaomu Diamond, Herbert S. Univ Michigan Sch Informat Dept Hlth Management & Policy Sch Publ Hlth Ann Arbor MI 48109 USA Univ Michigan Dept Pediat Ann Arbor MI 48109 USA Carnegie Mellon Univ H John Heinz Coll 3 Pittsburgh PA 15213 USA Univ Massachusetts Dept Publ Policy & Publ Affairs John W McCormack Grad Sch Policy Studies Boston MA 02125 USA United Hlth Serv Hosp Johnson City NY USA Univ Michigan Sch Publ Hlth Dept Biostat Ann Arbor MI 48109 USA Rutgers State Univ Sch Commun & Informat New Brunswick NJ 08903 USA Univ Pittsburgh Sch Med Dept Med Div Rheumatol Pittsburgh PA USA

Unpredictable yet frequently occurring exception situations pervade clinical care. Handling them properly often requires aberrant actions temporarily departing from normal practice. In this study, the authors investigated several exception-handling procedures provided in an electronic health records system for facilitating clinical documentation, which the authors refer to as 'data entry exit strategies.' Through a longitudinal analysis of computer-recorded usage data, the authors found that (1) utilization of the exit strategies was not affected by postimplementation system maturity or patient visit volume, suggesting clinicians' needs to 'exit' unwanted situations are persistent;and (2) clinician type and gender are strong predictors of exit-strategy usage. Drilldown analyses further revealed that the exit strategies were judiciously used and enabled actions that would be otherwise difficult or impossible. However, many data entries recorded via them could have been 'properly' documented, yet were not, and a considerable proportion containing temporary or incomplete information was never subsequently amended. These findings may have significant implications for the design of safer and more user-friendly point-of-care information systems for healthcare.

关键词： Electronic health records (E05.318.308.940.968.625.500) workflow (L01.906.893) documentation (L01.453.245) exit strategy exception-handling collaborative technologies personal health records and self-care systems developing/using clinical decision support (other than diagnostic) and guideline systems systems supporting patient–provider interaction human–computer interaction and human-centered computing improving healthcare workflow and process efficiency system implementation and management issues social/organizational study qualitative/ethnographic field study cognitive study (including experiments emphasizing verbal protocol analysis and usability) methods for integration of information from disparate sources information storage and retrieval (text and images) data exchange communication and integration across care settings (inter- and intraenterprise) visualization of data and knowledge developing/using computerized provider order entry diamond

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Factors influencing alert acceptance: a novel approach for predicting the success of clinical decision support

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JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 2011年第4期18卷 479-484页

作者： Seidling, Hanna M. Phansalkar, Shobha Seger, Diane L. Paterno, Marilyn D. Shaykevich, Shimon Haefeli, Walter E. Bates, David W. Brigham & Womens Hosp Div Gen Med & Primary Care Boston MA 02115 USA Harvard Univ Sch Med Boston MA USA Heidelberg Univ Dept Clin Pharmacol & Pharmacoepidemiol Heidelberg Germany Partners HealthCare Syst Wellesley MA USA

Background Clinical decision support systems can prevent knowledge-based prescription errors and improve patient outcomes. The clinical effectiveness of these systems, however, is substantially limited by poor user acceptance of presented warnings. To enhance alert acceptance it may be useful to quantify the impact of potential modulators of acceptance. Methods We built a logistic regression model to predict alert acceptance of drug drug interaction (DDI) alerts in three different settings. Ten variables from the clinical and human factors literature were evaluated as potential modulators of provider alert acceptance. ORs were calculated for the impact of knowledge quality, alert display, textual information, prioritization, setting, patient age, dose-dependent toxicity, alert frequency, alert level, and required acknowledgment on acceptance of the DDI alert. Results 50 788 DDI alerts were analyzed. Providers accepted only 1.4% of non-interruptive alerts. For interruptive alerts, user acceptance positively correlated with frequency of the alert (OR 1.30, 95% CI 1.23 to 1.38), quality of display (4.75, 3.87 to 5.84), and alert level (1.74, 1.63 to 1.86). Alert acceptance was higher in inpatients (2.63, 2.32 to 2.97) and for drugs with dose-dependent toxicity (1.13, 1.07 to 1.21). The textual information influenced the mode of reaction and providers were more likely to modify the prescription if the message contained detailed advice on how to manage the DDI. Conclusion We evaluated potential modulators of alert acceptance by assessing content and human factors issues, and quantified the impact of a number of specific factors which influence alert acceptance. This information may help improve clinical decision support systems design.

关键词： visualization of data and knowledge knowledge representations knowledge acquisition and knowledge management distributed systems agents software engineering: architecture developing and refining EHR data standards (including image standards) data models data exchange controlled terminologies and vocabularies communication integration across care settings (inter- and intra-enterprise) knowledge bases electronic decision support medication errors patient safety decision support

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The Yale cTAKES extensions for document classification: architecture and application

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JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 2011年第5期18卷 614-620页

作者： Garla, Vijay Lo Re, Vincent, III Dorey-Stein, Zachariah Kidwai, Farah Scotch, Matthew Womack, Julie Justice, Amy Brandt, Cynthia Yale Univ Ctr Med Informat Interdept Program Computat Biol & Bioinformat New Haven CT 06520 USA Univ Penn Sch Med Ctr Clin Epidemiol & Biostat Philadelphia PA 19104 USA Connecticut VA Healthcare Syst West Haven CT USA Arizona State Univ Dept Biomed Informat Tempe AZ USA Yale Univ Sch Nursing New Haven CT 06520 USA Yale Univ Sch Med Gen Internal Med New Haven CT 06520 USA Yale Univ Ctr Med Informat Sch Med New Haven CT 06520 USA

Background Open-source clinical natural-language-processing (NLP) systems have lowered the barrier to the development of effective clinical document classification systems. Clinical natural-language-processing systems annotate the syntax and semantics of clinical text;however, feature extraction and representation for document classification pose technical challenges. Methods The authors developed extensions to the clinical Text Analysis and knowledge Extraction System (cTAKES) that simplify feature extraction, experimentation with various feature representations, and the development of both rule and machine-learning based document classifiers. The authors describe and evaluate their system, the Yale cTAKES Extensions (YTEX), on the classification of radiology reports that contain findings suggestive of hepatic decompensation. Results and discussion The F-1-Score of the system for the retrieval of abdominal radiology reports was 96%, and was 79%, 91%, and 95% for the presence of liver masses, ascites, and varices, respectively. The authors released YTEX as open source, available at http://***/p/ytex.

关键词： Hepatitis visualization of data and knowledge languages computational methods advanced algorithms natural-language processing distributed systems agents software engineering: architecture developing and refining EHR data standards (including image standards) data models data exchange communication integration across care settings (inter- and intra-enterprise) detecting disease outbreaks and biological threats translational research—application of biological knowledge to clinical care linking the genotype and phenotype natural-language processing delivering health information and knowledge to the public monitoring the health of populations

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User perspectives on the usability of a regional health information exchange

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JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 2011年第5期18卷 711-716页

作者： Gadd, Cynthia S. Ho, Yun-Xian Cala, Cather Marie Blakemore, Dana Chen, Qingxia Frisse, Mark E. Johnson, Kevin B. Vanderbilt Univ Dept Biomed Informat Eskind Lib Nashville TN 37203 USA Vanderbilt Univ Dept Biostat Nashville TN 37203 USA

Objective We assessed the usability of a health information exchange (HIE) in a densely populated metropolitan region. This grant-funded HIE had been deployed rapidly to address the imminent needs of the patient population and the need to draw wider participation from regional entities. Design We conducted a cross-sectional survey of individuals given access to the HIE at participating organizations and examined some of the usability and usage factors related to the technology acceptance model. Measurements We probed user perceptions using the Questionnaire for User Interaction Satisfaction, an author-generated Trust scale, and user characteristic questions (eg, age, weekly system usage time). Results Overall, users viewed the system favorably (ratings for all usability items were greater than neutral (one-sample Wilcoxon test, p<0.0014, Bonferroni-corrected for 35 tests). System usage was regressed on usability, trust, and demographic and user characteristic factors. Three usability factors were positively predictive of system usage: overall reactions (p<0 0.01), learning (p<0.05), and system functionality (p<0.01). Although trust is an important component in collaborative relationships, we did not find that user trust of other participating healthcare entities was significantly predictive of usage. An analysis of respondents' comments revealed ways to improve the HIE. Conclusion We used a rapid deployment model to develop an HIE and found that perceptions of system usability were positive. We also found that system usage was predicted well by some aspects of usability. Results from this study suggest that a rapid development approach may serve as a viable model for developing usable HIEs serving communities with limited resources.

关键词： Information dissemination medical records system regional health planning usability usage biomedical informatics evaluation Qualitative/ethnographic field study Improving the education and skills training of health professionals System implementation and management issues Social/organizational study Collaborative technologies Methods for integration of information from disparate sources Demonstrating return on IT investment distributed systems agents Software engineering: architecture Supporting practice at a distance (telehealth) data exchange communication and integration across care settings (inter- and intra-enterprise) visualization of data and knowledge policy Legal historical ethical study methods clinical informatics biomedical informatics pediatrics e-prescribing human factors

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Collaborative search in electronic health records

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JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 2011年第3期18卷 282-291页

作者： Zheng, Kai Mei, Qiaozhu Hanauer, David A. Univ Michigan Sch Publ Hlth Dept Hlth Management & Policy Sch Informat Ann Arbor MI 48109 USA Univ Michigan Dept Elect Engn & Comp Sci Ann Arbor MI 48109 USA Univ Michigan Dept Pediat Ann Arbor MI 48109 USA Univ Michigan Ctr Comprehens Canc Ann Arbor MI 48109 USA

Objective A full-text search engine can be a useful tool for augmenting the reuse value of unstructured narrative data stored in electronic health records (EHR). A prominent barrier to the effective utilization of such tools originates from users' lack of search expertise and/or medical-domain knowledge. To mitigate the issue, the authors experimented with a 'collaborative search' feature through a homegrown EHR search engine that allows users to preserve their search knowledge and share it with others. This feature was inspired by the success of many social information-foraging techniques used on the web that leverage users' collective wisdom to improve the quality and efficiency of information retrieval. Design The authors conducted an empirical evaluation study over a 4-year period. The user sample consisted of 451 academic researchers, medical practitioners, and hospital administrators. The data were analyzed using a social-network analysis to delineate the structure of the user collaboration networks that mediated the diffusion of knowledge of search. Results The users embraced the concept with considerable enthusiasm. About half of the EHR searches processed by the system (0.44 million) were based on stored search knowledge;0.16 million utilized shared knowledge made available by other users. The social-network analysis results also suggest that the user-collaboration networks engendered by the collaborative search feature played an instrumental role in enabling the transfer of search knowledge across people and domains. Conclusion Applying collaborative search, a social information-foraging technique popularly used on the web, may provide the potential to improve the quality and efficiency of information retrieval in healthcare.

关键词： Collaborative technologies personal health records and self-care systems developing/using clinical decision support (other than diagnostic) and guideline systems systems supporting patient-provider interaction human–computer interaction and human-centered computing improving healthcare workflow and process efficiency system implementation and management issues social/organizational study qualitative/ethnographic field study cognitive study (including experiments emphasizing verbal protocol analysis and usability) methods for integration of information from disparate sources information storage and retrieval (text and images) data exchange communication integration across care settings (inter- and intraenterprise) visualization of data and knowledge developing/using computerized provider order entry

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Machine-learned solutions for three stages of clinical information extraction: the state of the art at i2b2 2010

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JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 2011年第5期18卷 557-562页

作者： de Bruijn, Berry Cherry, Colin Kiritchenko, Svetlana Martin, Joel Zhu, Xiaodan Natl Res Council Canada Inst Informat Technol Ottawa ON K1A 0R6 Canada

Objective As clinical text mining continues to mature, its potential as an enabling technology for innovations in patient care and clinical research is becoming a reality. A critical part of that process is rigid benchmark testing of natural language processing methods on realistic clinical narrative. In this paper, the authors describe the design and performance of three state-of-the-art text-mining applications from the National Research Council of Canada on evaluations within the 2010 i2b2 challenge. Design The three systems perform three key steps in clinical information extraction: (1) extraction of medical problems, tests, and treatments, from discharge summaries and progress notes;(2) classification of assertions made on the medical problems;(3) classification of relations between medical concepts. Machine learning systems performed these tasks using large-dimensional bags of features, as derived from both the text itself and from external sources: UMLS, cTAKES, and Medline. Measurements Performance was measured per subtask, using micro-averaged F-scores, as calculated by comparing system annotations with ground-truth annotations on a test set. Results The systems ranked high among all submitted systems in the competition, with the following F-scores: concept extraction 0.8523 (ranked first);assertion detection 0.9362 (ranked first);relationship detection 0.7313 (ranked second). Conclusion For all tasks, we found that the introduction of a wide range of features was crucial to success. Importantly, our choice of machine learning algorithms allowed us to be versatile in our feature design, and to introduce a large number of features without overfitting and without encountering computing-resource bottlenecks.

关键词： natural language processing semantics classification/*methods computerized medical records systems patient discharge/*statistics & numerical data text mining concept detection relation extraction document coding machine learning modeling physiologic and disease processes linking the genotype and phenotype identifying genome and protein structure and function visualization of data and knowledge

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Targeted screening for pediatric conditions with the CHICA system

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JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 2011年第4期18卷 485-490页

作者： Carroll, Aaron E. Biondich, Paul G. Anand, Vibha Dugan, Tamara M. Sheley, Meena E. Xu, Shawn Z. Downs, Stephen M. Indiana Univ Sch Med Childrens Hlth Serv Res Indianapolis IN 46202 USA Indiana Univ Sch Med Regenstrief Inst Hlth Care Indianapolis IN 46202 USA

Objective The Child Health Improvement through Computer Automation (CHICA) system is a decision-support and electronic-medical-record system for pediatric health maintenance and disease management. The purpose of this study was to explore CHICA's ability to screen patients for disorders that have validated screening criteria specifically tuberculosis (TB) and iron-deficiency anemia. Design Children between 0 and 11 years were randomized by the CHICA system. In the intervention group, parents were asked about TB and iron-deficiency risk, and physicians received a tailored prompt. In the control group, no screens were performed, and the physician received a generic prompt about these disorders. Results 1123 participants were randomized to the control group and 1116 participants to the intervention group. Significantly more people reported positive risk factors for iron-deficiency anemia in the intervention group (17.5% vs 3.1%, OR 6.6, 95% CI 4.5 to 9.5). In general, far fewer parents reported risk factors for TB than for iron-deficiency anemia. Again, there were significantly higher detection rates of positive risk factors in the intervention group (1.8% vs 0.8%, OR 2.3, 95% CI 1.0 to 5.0). Limitations It is possible that there may be more positive screens without improving outcomes. However, the guidelines are based on studies that have evaluated the questions the authors used as sensitive and specific, and there is no reason to believe that parents misunderstood them. Conclusions Many screening tests are risk-based, not universal, leaving physicians to determine who should have a further workup. This can be a time-consuming process. The authors demonstrated that the CHICA system performs well in assessing risk automatically for TB and iron-deficiency anemia.

关键词： Tuberculosis iron-deficiency anemia CHICA screening computer decision-support system visualization of data and knowledge knowledge representations communications networking methods mobility uncertain reasoning and decision theory languages computational methods advanced algorithms methods for integration of information from disparate sources distributed systems agents software engineering: architecture data models automated learning developing/using clinical decision support (other than diagnostic) and guideline systems discovery text and data mining methods

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