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A randomized controlled trial of screening for maternal depression with a clinical decision support system

JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 2013年第2期20卷 311-316页

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

Objective To determine if automated screening and just in time delivery of testing and referral materials at the point of care promotes universal screening referral rates for maternal depression. Methods The Child Health Improvement through Computer Automation (CHICA) system is a decision support and electronic medical record system used in our pediatric clinics. All families of patients up to 15 months of age seen between October 2007 and July 2009 were randomized to one of three groups: (1) screening questions printed on prescreener forms (PSF) completed by mothers in the waiting room with physician alerts for positive screens, (2) everything in (1) plus 'just in time' (JIT) printed materials to aid physicians, and (3) a control group where physicians were simply reminded to screen on printed physician worksheets. Results The main outcome of interest was whether physicians suspected a diagnosis of maternal depression and referred a mother for assistance. This occurred significantly more often in both the PSF (2.4%) and JIT groups (2.4%) than in the control group (1.2%) (OR 2.06, 95% CI 1.08 to 3.93). Compared to the control group, more mothers were noted to have depressed mood in the PSF (OR 7.93, 95% CI 4.51 to 13.96) and JIT groups (OR 8.10, 95% CI 4.61 to 14.25). Similarly, compared to the control group, more mothers had signs of anhedonia in the PSF (OR 12.58, 95% CI 5.03 to 31.46) and JIT groups (OR 13.03, 95% CI 5.21 to 32.54). Conclusions Clinical decision support systems like CHICA can improve the screening of maternal depression.

关键词： Maternal depression CHICA screening computer decision support system visualization of data and knowledge data models software engineering: architecture agents distributed systems pediatrics

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Utility of gene-specific algorithms for predicting pathogenicity of uncertain gene variants

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JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 2012年第2期19卷 207-211页

作者： Crockett, David K. Lyon, Elaine Williams, Marc S. Narus, Scott P. Facelli, Julio C. Mitchell, Joyce A. Univ Utah Sch Med Dept Biomed Informat Salt Lake City UT USA Univ Utah Sch Med Dept Pathol Salt Lake City UT USA Intermt Healthcare Clin Genet Inst Salt Lake City UT USA Univ Utah Ctr High Performance Comp Salt Lake City UT USA

The rapid advance of gene sequencing technologies has produced an unprecedented rate of discovery of genome variation in humans. A growing number of authoritative clinical repositories archive gene variants and disease phenotypes, yet there are currently many more gene variants that lack clear annotation or disease association. To date, there has been very limited coverage of gene-specific predictors in the literature. Here the evaluation is presented of "gene-specific" predictor models based on a naive Bayesian classifier for 20 gene-disease datasets, containing 3986 variants with clinically characterized patient conditions. The utility of gene-specific prediction is then compared with "all-gene" generalized prediction and also with existing popular predictors. Gene-specific computational prediction models derived from clinically curated gene variant disease datasets often outperform established generalized algorithms for novel and uncertain gene variants.

关键词： Amino acid properties gene variant classification machine learning phenotype prediction bioinformatics gene variants classification gene disease database developing/using computerized provider order entry designing usable (responsive) resources and systems methods for integration of information from disparate sources high-performance and large-scale computing distributed systems agents software engineering: architecture data exchange communication integration across care settings (inter- and intra-enterprise) system implementation and management issues languages computational methods statistical analysis of large datasets advanced algorithms identifying genome and protein structure and function detecting disease outbreaks and biological threats visualization of data and knowledge

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An informatics agenda for public health: summarized recommendations from the 2011 AMIA PHI Conference

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JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 2012年第5期19卷 688-695页

作者： Massoudi, Barbara L. Goodman, Kenneth W. Gotham, Ivan J. Holmes, John H. Lang, Lisa Miner, Kathleen Potenziani, David D. Richards, Janise Turner, Anne M. Fu, Paul C. RTI Int Ctr Adv Hlth IT Atlanta GA 30341 USA Univ Miami Eth Programs Miami FL USA New York State Dept Hlth Healthcom Network Syst Management Albany NY USA Univ Penn Perelman Sch Med Ctr Clin Epidemiol & Biostat Philadelphia PA 19104 USA NIH Natl Informat Ctr Hlth Serv Res & Hlth Care Techn Natl Lib Med Bethesda MD 20892 USA Emory Univ Rollins Sch Publ Hlth Dept Behav Sci & Hlth Educ Atlanta GA 30322 USA Univ N Carolina Sch Med Chapel Hill NC USA US Ctr Dis Control & Prevent Ctr Global Hlth Div Global HIV AIDS Atlanta GA USA Univ Washington Sch Med NW Ctr Publ Hlth Practice Dept Hlth Serv Seattle WA USA Univ Washington Sch Med NW Ctr Publ Hlth Practice Dept Med Educ Seattle WA USA Univ Washington Sch Med NW Ctr Publ Hlth Practice Dept Biomed Informat Seattle WA USA Univ Calif Los Angeles Sch Publ Hlth Los Angeles Biomed Res Inst Los Angeles Cty Harbor UCLA Med CtrDept Pediat Torrance CA USA Univ Calif Los Angeles Sch Publ Hlth Los Angeles Cty Harbor UCLA Med Ctr Los Angeles Biomed Res InstDept Hlth Serv Torrance CA USA

The AMIA Public Health Informatics 2011 Conference brought together members of the public health and health informatics communities to revisit the national agenda developed at the AMIA Spring Congress in 2001, assess the progress that has been made in the past decade, and develop recommendations to further guide the field. Participants met in five discussion tracks: technical framework;research and evaluation;ethics;education, professional training, and workforce development;and sustainability. Participants identified 62 recommendations, which clustered into three key themes related to the need to (1) enhance communication and information sharing within the public health informatics community, (2) improve the consistency of public health informatics through common public health terminologies, rigorous evaluation methodologies, and competency-based training, and (3) promote effective coordination and leadership that will champion and drive the field forward. The agenda and recommendations from the meeting will be disseminated and discussed throughout the public health and informatics communities. Both communities stand to gain much by working together to use these recommendations to further advance the application of information technology to improve health.

关键词： Conferences consensus development as topic informatics public health informatics public health practice public health ethics privacy confidentiality bioethics policy monitoring the health of populations knowledge representations statistical analysis of large datasets developing/using clinical decision support (other than diagnostic) and guideline systems discovery and text and data mining methods other methods of information extraction automated learning systems to support and improve diagnostic accuracy distributed systems agents software engineering: architecture health services research health reform health data standards qualitative/ethnographic field study improving the education and skills training of health professionals knowledge acquisition and knowledge management system implementation and management issues quality measures

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The Hub Population Health System: distributed ad hoc queries and alerts

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JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 2012年第E1期19卷 E46-E50页

作者： Buck, Michael D. Anane, Sheila Taverna, John Amirfar, Sam Stubbs-Dame, Remle Singer, Jesse New York City Dept Hlth & Mental Hyg Bur Primary Care Informat Project Queens NY 11101 USA Columbia Univ Dept Biomed Informat New York NY USA

The Hub Population Health System enables the creation and distribution of queries for aggregate count information, clinical decision support alerts at the point-of-care for patients who meet specified conditions, and secure messages sent directly to provider electronic health record (EHR) inboxes. Using a metronidazole medication recall, the New York City Department of Health was able to determine the number of affected patients and message providers, and distribute an alert to participating practices. As of September 2011, the system is live in 400 practices and within a year will have over 532 practices with 2500 providers, representing over 2.5 million New Yorkers. The Hub can help public health experts to evaluate population health and quality improvement activities throughout the ambulatory care network. Multiple EHR vendors are building these features in partnership with the department's regional extension center in anticipation of new meaningful use requirements.

关键词： Decision support systems clinical public health informatics population surveillance electronic health records medical informatics developing/using computerized provider order entry methods for integration of information from disparate sources distributed systems agents software engineering: architecture PCIP ambulatory care new york city cardiovascular disease food environment population health

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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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A knowledge discovery and reuse pipeline for information extraction in clinical notes

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JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 2011年第5期18卷 574-579页

作者： Patrick, Jon D. Nguyen, Dung H. M. Wang, Yefeng Li, Min Univ Sydney Sch Informat Technol Fac Engn & IT Sydney NSW 2006 Australia

Objective Information extraction and classification of clinical data are current challenges in natural language processing. This paper presents a cascaded method to deal with three different extractions and classifications in clinical data: concept annotation, assertion classification and relation classification. Materials and Methods A pipeline system was developed for clinical natural language processing that includes a proofreading process, with gold-standard reflexive validation and correction. The information extraction system is a combination of a machine learning approach and a rule-based approach. The outputs of this system are used for evaluation in all three tiers of the fourth i2b2/VA shared-task and workshop challenge. Results Overall concept classification attained an F-score of 83.3% against a baseline of 77.0%, the optimal F-score for assertions about the concepts was 92.4% and relation classifier attained 72.6% for relationships between clinical concepts against a baseline of 71.0%. Micro-average results for the challenge test set were 81.79%, 91.90% and 70.18%, respectively. Discussion The challenge in the multi-task test requires a distribution of time and work load for each individual task so that the overall performance evaluation on all three tasks would be more informative rather than treating each task assessment as independent. The simplicity of the model developed in this work should be contrasted with the very large feature space of other participants in the challenge who only achieved slightly better performance. There is a need to charge a penalty against the complexity of a model as defined in message minimalisation theory when comparing results. Conclusion A complete pipeline system for constructing language processing models that can be used to process multiple practical detection tasks of language structures of clinical records is presented.

关键词： agents automated learning classification clinical controlled terminologies and vocabularies designing usable (responsive) resources and systems discovery distributed systems information classification information extraction i2b2 challenge knowledge bases natural language processing ontologies software engineering: architecture text and data mining methods 2010 i2b2 challenge

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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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A secure protocol for protecting the identity of providers when disclosing data for disease surveillance

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JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 2011年第3期18卷 212-217页

作者： El Emam, Khaled Hu, Jun Mercer, Jay Peyton, Liam Kantarcioglu, Murat Malin, Bradley Buckeridge, David Samet, Saeed Earle, Craig Childrens Hosp Eastern Ontario Res Inst Ottawa ON K1H 8L1 Canada Univ Ottawa Sch Informat Technol & Engn Ottawa ON Canada Univ Texas Dallas Dallas TX 75230 USA Vanderbilt Univ Nashville TN USA McGill Univ Dept Epidemiol & Biostat Montreal PQ Canada Ontario Inst Canc Res Toronto ON Canada Inst Clin Evaluat Sci Toronto ON Canada

Background Providers have been reluctant to disclose patient data for public-health purposes. Even if patient privacy is ensured, the desire to protect provider confidentiality has been an important driver of this reluctance. Methods Six requirements for a surveillance protocol were defined that satisfy the confidentiality needs of providers and ensure utility to public health. The authors developed a secure multi-party computation protocol using the Paillier cryptosystem to allow the disclosure of stratified case counts and denominators to meet these requirements. The authors evaluated the protocol in a simulated environment on its computation performance and ability to detect disease outbreak clusters. Results Theoretical and empirical assessments demonstrate that all requirements are met by the protocol. A system implementing the protocol scales linearly in terms of computation time as the number of providers is increased. The absolute time to perform the computations was 12.5 s for data from 3000 practices. This is acceptable performance, given that the reporting would normally be done at 24 h intervals. The accuracy of detection disease outbreak cluster was unchanged compared with a non-secure distributed surveillance protocol, with an F-score higher than 0.92 for outbreaks involving 500 or more cases. Conclusion The protocol and associated software provide a practical method for providers to disclose patient data for sentinel, syndromic or other indicator-based surveillance while protecting patient privacy and the identity of individual providers.

关键词： Privacy reidentification de-identification consent ethics integration across care settings (inter- and intraenterprise) languages computational methods advanced algorithms personal health records and self-care systems assuring information system security and personal privacy anonymization other methods for security and policy enforcement cryptography data exchange communication ethical study methods statistical analysis of large datasets methods for integration of information from disparate sources distributed systems agents software engineering: architecture detecting disease outbreaks and biological threats policy legal historical simulation of complex systems (at all levels: molecules to work groups to organizations) monitoring the health of populations privacy and security machine learning health data standards vocabulary ontology scientific information and health data policy consumer health/patient education information information retrieval NLP public-health informatics clinical trials syndromic surveillance secure computation

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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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