DOCSLIB.ORG

Infectious Disease Informatics and Outbreak Detection

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Infectious Disease Informatics and Outbreak Detection Chapter 13 INFECTIOUS DISEASE INFORMATICS AND OUTBREAK DETECTION Daniel zeng', Hsinchun hen', Cecil ~~nch~,Millicent ids son^, and Ivan ~otham~ '~ana~ementInformation Systems Department, Eller College of Management, University of Arizona, Tucson, Arizona 85721; '~ivisionof Medical Informatics, School of Medicine, University of California, Davis, California 95616; also with California Department of Health Services; 3~ewYork State Department of Health, Albany, New York 12220; also with School of Public Health, University at Albany Chapter Overview Infectious disease informatics is an emerging field that studies data collection, sharing, modeling, and management issues in the domain of infectious diseases. This chapter provides an overview of this field with specific emphasis on the following two sets of topics: (a) the design and main system components of an infectious disease information infrastructure, and (b) spatio-temporal data analysis and modeling techniques used to identify possible disease outbreaks. Several case studies involving real- world applications and research prototypes are presented to illustrate the application context and relevant system design and data modeling issues. Keywords infectious disease informatics; data and messaging standards; outbreak detection; hotspot analysis; data visualization Infectious Disease Informatics and Outbreak Detection 361 1. INTRODUCTION Infectious or communicable diseases have been a risk for human society since the onset of the human race. The large-scale spread of infectious diseases often has a major impact on the society and individuals alike and sometimes determines the course of history (McNeill, 1976). Infectious diseases are still a fact of modern life. Outbreaks of new diseases such as AIDS are causing major problems across the world and known, treatable diseases in developing countries still pose serious threats to human life and exact heavy tolls from nations' economies (Pinner et al., 2003). For instance, the estimated economic cost of Tuberculosis (TB) is 3 billion US dollars per year in India (http://www.healthinitiative.org). In addition to diseases that occur naturally, there has been increasing concern that terrorists may choose to attack by deliberate transmission of infectious disease using biological agents. With greatly expanded trade and travel, infectious diseases, either naturally occurring or caused by bioterrorism attacks, can spread at a rapid rate, resulting in potentially significant loss of life, major economic crises, and political instability (Chang et al., 2003). Information systems play a central role in developing an effective compre- hensive approach to prevent, detect, respond to, and manage infectious disease outbreaks of plants, animals, and humans (Damianos et al., 2002; Buehler et al., 2004). Currently, a large amount of infectious disease data is being collected by various laboratories, health care providers, and government agencies at local, state, national, and international levels (Pinner et al., 2003). Furthermore, many agencies have developed information access, analysis, and reporting systems of varying degrees of sophistication. For example, in its role as the key agency responsible for human reportable diseases in the U.S., the Centers for Disease Control and Prevention (CDC) has developed computerized reporting systems for local and state health departments. Similarly, the US. Department of Agriculture (USDA) is enhancing data systems for certain animal diseases (eg, mad cow disease and foot-and-mouth disease), and the U.S. Geological Survey (USGS), through its National Wildlife Health Center (NWHC) and numerous partners, manages databases for wildlife diseases. Databases may also be available at other federal and state or local health, agriculture, and environment/wildlife agencies and laboratories. In addition to infectious disease-related data sources, the research and public health communities have developed a wide array of analytical and statistical models targeted at analyzing disease data for surveillance and outbreak prediction purposes. For instance, such models have been employed to predict outbreaks of West Nile Virus (WNV) (Eidson, 2001; Eidson et al., 2001; Julian et al., 2002; Guptill et al., 2003; Mostashari et al., 2003; Ruiz et al., 2004; Wonham et al., 2004) and of influenza (Hyman and LaForce, 2003). 3 62 MEDICAL INFORMATICS This chapter introduces infectious disease informatics (IDI), an emerging subfield of biomedical informatics that systematically studies these information management and analysis issues in the domain of infectious diseases. More specifically, the objective of ID1 research can be summarized as the development of the science and technologies needed for collecting, sharing, reporting, analyzing, and visualizing infectious disease data and for providing data and decision-making support for infectious disease prevention, detection, and management. ID1 research directly benefits public health agencies in their infectious disease surveillance activities at all levels of government and in the international context. It also has important applications in law enforcement and national security concerning potential bioterrorism attacks (Siegrist, 1999). Aimed at providing an overview of the emerging field of IDI, this chapter emphasizes the technical side of ID1 research with detailed discussions on (a) the design and various system components of an infectious disease information infrastructure and (b) an important class of ID1 data analysis techniques concerning the identification of possible outbreaks. In order to provide the readers with a concrete sense of ID1 application contexts and relevant system design choices, we discuss both infectious disease information systems and standards that have been deployed in real-world applications and research prototypes for illustrative purposes. The majority of these case studies involve system development and deployment, and research projects in which we have been actively participating. The rest of the chapter is structured as follows. Section 2presents an overview of IDI. It discusses practical challenges arising when managing infectious disease data and presents the main technical components of an infectious disease information infrastructure and related research and system development issues. It also provides the readers with an introduction to analytical models and tools useful for infectious disease data analysis, in particular, outbreak prediction. Section 3 contains three case studies based on real-world applications and research prototypes to illustrate how to apply and synthesize in practice ID1 system development and data analysis techniques introduced in Section 2. Section 4 concludes the chapter by summarizing the main learning objectives of this chapter and discussing future directions in ID1 research and practice. 2. INFECTIOUS DISEASE INFORMATICS: BACKGROUND AND OVERVIEW 2.1 Practical Challenges and Research Issues In practice, infectious disease data collection and analysis are complex and in most cases involve a multi-stage process with multiple stakeholders across organizational boundaries. Due to the nature of epidemics, there is also a critical need for timely data collection and processing. Infectious Disease Informatics and Outbreak Detection 363 The traditional approach to infectious data collection, dissemination, and reporting is a paper-based system that depends on telephone conversations for transmission of data and multiple personnel entering or updating paper-based case report forms. This approach leads to many problems related to information processing. Figure 13-1 illustrates a typical paper-based state and local data management approach for Botulism, a rare but significant infectious disease caused by a disease agent that can be used in a bioterrorism attack. This figure summarizes the information flow between various roles and organizations for Botulism case reporting and demonstrates the multiple areas of potential breakdown in communication (indicated by the 61 sign.) Deternlines Nerd P.oWlisna ..-- for Outbredk Investigation T, 1.d11"' . Seeks subn~its Morbidity Reporl or Reports Colllirnied Food bonw restock San~yledraw Checks spedmes , I S~cci~tien Srnds to State Figure 13-1. Paper-based Botulism Case Reporting Many of these areas of potential breakdown in communication could be overcome with an automated process of data flow provided by a computerized infectious disease information system. Having historical data collected on outbreaks that are readily available for predictive modeling would also lead to improved surveillance activities, fewer data entry errors, and better public health data. Data in an information system would facilitate the required reporting of infectious diseases from local public health jurisdictions to state organizations and from state organizations to national surveillance entities such as the CDC. Additionally, information systems would streamline the reporting requirements for bioterrorism agents to the Department of Justice. Such systems also simplify dramatically the required chain of custody analysis for samples being tested for biological or chemical hazards. Infectious disease information systems also 364 MEDICAL INFORMATICS provide the ability for application of the ever expanding collection of statistical algorithms to data in real time that would not be possible without such systems. Increasingly, infectious disease data are being collected in an electronic form by various laboratories,
Load more

Recommended publications
  • Intelligence and Security Informatics
    CHAPTER 6 Intelligence and Security Informatics Hsinchun Chen and Jennifer Xu University of Arizona ISI: Challenges and Research Framework The tragic events of September 11,2001, and the subsequent anthrax scare had profound effects on many aspects of society. Terrorism has become the most significant threat to domestic security because of its potential to bring massive damage to the nation’s infrastructure and economy. In response to this challenge, federal authorities are actively implementing comprehensive strategies and measures to achieve the three objectives identified in the “National Strategy for Homeland Security” report (U.S. Office of Homeland Security, 2002): (1)preventing future terrorist attacks, (2) reducing the nation’s vulnerability, and (3) minimizing the damage and expediting recovery from attacks that occur. State and local law enforcement agencies, likewise, have become more vigilant about criminal activities that can threaten public safety and national security. Academics in the natural sciences, computational science, informa- tion science, social sciences, engineering, medicine, and many other fields have also been called upon to help enhance the government’s capa- bilities to fight terrorism and other crime. Science and technology have been identified in the “National Strategy for Homeland Security” report as the keys to winning the new counter-terrorism war (U. S. Office of Homeland Security, 2002). In particular, it is believed that information technology and information management will play indispensable roles in making the nation safer (Cronin, 2005; Davies, 2002; National Research Council, 2002) by supporting intelligence and knowledge dis- covery through collecting, processing, analyzing, and utilizing terrorism- and crime-related data (Badiru, Karasz, & Holloway, 1988; Chen, Miranda, Zeng, Demchak, Schroeder, & Madhusudan, 2003; Chen, Moore, Zeng, & Leavitt, 2004).
    [Show full text]
  • Visualization and Analytics Tools for Infectious Disease Epidemiology: 7 5 a Systematic Review
    YJBIN 2161 No. of Pages 12, Model 5G 18 April 2014 Journal of Biomedical Informatics xxx (2014) xxx–xxx 1 Contents lists available at ScienceDirect Journal of Biomedical Informatics journal homepage: www.elsevier.com/locate/yjbin 2 Methodological Review 6 4 Visualization and analytics tools for infectious disease epidemiology: 7 5 A systematic review a a b c d 8 Q1 Lauren N. Carroll , Alan P. Au , Landon Todd Detwiler , Tsung-chieh Fu , Ian S. Painter , a,d,⇑ 9 Q2 Neil F. Abernethy 10 Q3 a Department of Biomedical Informatics and Medical Education, University of Washington, 850 Republican St., Box 358047, Seattle, WA 98109, United States 11 b Department of Biological Structure, University of Washington, 1959 NE Pacific St., Box 357420, United States 12 c Department of Epidemiology, University of Washington, 850 Republican St., Box 358047, Seattle, WA 98109, United States 13 d Department of Health Services, University of Washington, 1959 NE Pacific St., Box 359442, Seattle, WA 98195, United States 1415 1617 article info abstract 3219 20 Article history: Background: A myriad of new tools and algorithms have been developed to help public health professionals 33 21 Received 13 September 2013 analyze and visualize the complex data used in infectious disease control. To better understand approaches 34 22 Accepted 3 April 2014 to meet these users’ information needs, we conducted a systematic literature review focused on the land- 35 23 Available online xxxx scape of infectious disease visualization tools for public health professionals, with a special emphasis on 36 geographic information systems (GIS), molecular epidemiology, and social network analysis.
    [Show full text]
  • Component 5: History of Health Information Technology in the U.S
    Component 5: History of Health Information Technology in the U.S. Instructor Manual Version 3.0/Spring 2012 Notes to Instructors This Instructor Manual is a resource for instructors using this component. Each component is broken down into units, which include the following elements: • Learning objectives • Suggested student readings, texts, reference links to supplement the narrated PowerPoint slides • Lectures (voiceover PowerPoint in Flash format); PowerPoint slides (Microsoft PowerPoint format), lecture transcripts (Microsoft Word format); and audio files (MP3 format) for each lecture • Self-assessment questions reflecting Unit Objectives with answer keys and/or expected outcomes • Application Activities (e.g., discussion questions, assignments, projects) with instructor guidelines, answer keys and/or expected outcomes Health IT Workforce Curriculum History of Health Information 2 Technology in the U.S. Version 3.0/Spring 2012 This material was developed by The University of Alabama at Birmingham, funded by the Department of Health and Human Services, Office of the National Coordinator for Health Information echnologyT under Award Number 1U24OC000023 Contents Notes to Instructors ...................................................................................2 Disclaimer ..................................................................................................5 Component Overview ................................................................................6 Component Objectives ..............................................................................6
    [Show full text]
  • Medical Informatics
    MEDICAL INFORMATICS Knowledge Management and Data Mining in Biomedicine INTEGRATED SERIES IN INFORMATION SYSTEMS Series Editors Professor Ramesh Sharda Prof. Dr. Stefan Vo13 Oklahoma State University Universitat Hamburg Other published titles in the series: E-BUSINESS MANAGEMENT: Integration of Web Technologies with Business Models1 Michael J. Shaw VIRTUAL CORPORATE UNIVERSITIES: A Matrix of Knowledge and Learning for the New Digital DawdWalter R.J. Baets & Gert Van der Linden SCALABLE ENTERPRISE SYSTEMS: An Introduction to Recent Advances1 edited by Vittal Prabhu, Soundar Kumara, Manjunath Kamath LEGAL PROGRAMMING: Legal Compliance for RFID and Software Agent Ecosystems in Retail Processes and Beyond1 Brian Subirana and Malcolm Bain LOGICAL DATA MODELING: What It Is and How To Do It1 Alan Chmura and J. Mark Heumann DESIGNING AND EVALUATING E-MANAGEMENT DECISION TOOLS: The Integration of Decision and Negotiation Models into Internet-Multimedia Technologies1 Giampiero E.G. Beroggi INFORMATION AND MANAGEMENT SYSTEMS FOR PRODUCT CUSTOMIZATIONI Blecker, Friedrich, Kaluza, Abdelkafi & Kreutler MEDICAL INFORMATICS Knowledge Management and Data Mining in Biomedicine edited by Hsinchun Chen Sherrilynne S. Fuller Carol Friedman William Hersh - Springer Hsinchun Chen Sherrilynne S. Fuller The University of Arizona, USA University of Washington, USA Carol Friedman William Hersh Columbia University, USA Oregon Health & Science Univ., USA Library of Congress Cataloging-in-Publication Data A C.I.P. Catalogue record for this book is available from the Library of Congress. ISBN-10: 0-387-2438 1-X (HB) ISBN- 10: 0-387-25739-X (e-book) ISBN- 13: 978-0387-24381-8 (HB) ISBN- 13: 978-0387-25739-6 (e-book) O 2005 by Springer Science+Business Media, Inc.
    [Show full text]
  • Development and Evaluation of Leveraging Biomedical
    DEVELOPMENT AND EVALUATION OF LEVERAGING BIOMEDICAL INFORMATICS TECHNIQUES TO ENHANCE PUBLIC HEALTH SURVEILLANCE by Kailah T. Davis A dissertation submitted to the faculty of The University of Utah in partial fulfillment of the requirements for the degree of Doctor of Philosophy Department of Biomedical Informatics The University of Utah August 2014 Copyright © Kailah T. Davis 2014 All Rights Reserved The University of Utah Graduate School STATEMENT OF DISSERTATION APPROVAL The dissertation of ________________ Kailah T. Davis ________________________ has been approved by the following supervisory committee members: ___ Julio Facelli_________________, Chair ____ 1/27/2014 __ Date Approved ____________Catherine Staes_____________, Member _____2/06/2014____ Date Approved ____________Leslie Lenert________________, Member _____2/03/2014____ Date Approved ____________Per Gesteland _______________, Member _____2/12/2014____ Date Approved ____________Robert Kessler_______________, Member _____6/10/2014____ Date Approved And by _____________ Wendy Chapman_____________________, Chair of the Department _________________ Biomedical Informatics_________________ __ and by David B. Kieda, Dean of The Graduate School. ABSTRACT Public health surveillance systems are crucial for the timely detection and response to public health threats. Since the terrorist attacks of September 11, 2001, and the release of anthrax in the following month, there has been a heightened interest in public health surveillance. The years immediately following these attacks were
    [Show full text]
  • Continuous Artificial Prediction Markets As a Syndromic
    Continuous Artificial Prediction Markets as a Syndromic Surveillance Technique Fatemeh Jahedpari 1 Syndromic Surveillance Appearance of highly virulent viruses warrant early detection of outbreaks to protect community health. The main goal of public health surveillance and more specifically `syndromic surveillance systems' is early detection of an outbreak in a society using available data sources. In this paper, we discuss what are the challenges of syndromic surveillance systems and how continuous Artificial Prediction Market (c-APM) [Jahedpari et al., 2017] can effectively be applied to the problem of syndromic surveillance. c-APM can effectively be applied to the problem of syndromic surveillance by analysing each data source with a selection of algorithms and integrating their results according to an adaptive weighting scheme. Section 2 provides an introduction and explains syndromic surveillance. Then, we discuss the syndromic surveillance data sources in Section 3 and present some syndromic surveillance systems in Section 4. The statement of the problem in this field is covered in Section 5. After that, we discuss Google Flu Trends (GFT) and GP model [Lampos et al., 2015], which is proposed by Google Flu Trends team to improve GFT engine performance, in Section 6 and 7 respectively. Also, in these sections, we evaluate the performance of c-APM as a syndromic surveillance system. Finally, Section 8 provides the conclusion of this paper. 2 Introduction According to the World Health Organisation (WHO) [World Health Organization, 2013], the United Nations directing and coordinating health authority, public health surveillance is: The continuous, systematic collection, analysis and interpretation of health-related data needed for the planning, implementation, and evaluation of public health practice.
    [Show full text]
  • An Educational &Analytical Investigation
    International Journal of Applied Science and Engineering, 8(1): 01-09, June 2020 DOI: ©2020 New Delhi Publishers. All rights reserved Informatics: Foundation, Nature, Types and Allied areas— An Educational &Analytical Investigation P. K. Paul1* and P.S. Aithal2 1Executive Director, MCIS, Department of CIS, Information Scientist (Offg.), Raiganj University (RGU), West Bengal, India 2Vice Chancellor, Srinivas University, Karnataka, India *Corresponding author: [email protected] ABSTRACT Informatics is an emerging subject that concern with both Information Technology and Management Science. It is very close to Information Science, Information Systems, Information Technology rather Computer Science, Computer Engineering, Computer Application, etc. The term Informatics widely used as an alternative to Information Science and IT in many countries. Apart from the IT and Computing stream, the field ‘Informatics’ also available in the Departments, Units, etc. viz. Management Sciences, Health Sciences, Environmental Sciences, Social Sciences, etc., based on nature of the Informatics. Informatics can be seen as a technology based or also as a domain or field specific depending upon nature and thus it is emerging as an Interdisciplinary Sciences. There are few dimensions of Informatics that can be noted viz. Bio Sciences, Pure & Mathematical Sciences, Social Sciences, Management Sciences, Legal & Educational Sciences, etc. This is a conceptual paper deals with the academic investigation in respect of the Informatics branch; both in internationally and in India. Keywords: Informatics, IT, Informatics Systems, Biological Informatics, Emerging Subjects, Academics, Development Informatics is a developing field that cares about both technologies and information. Initially, it was treated as a practicing nomenclature and now it becomes a field of study and growing internationally in different higher educational institutes which are offering a program on simple ‘Informatics’ or any domain specific viz.
    [Show full text]
  • AETA-Computational-Engineering.Pdf
    Computational Engineering A Agent-based computational economics Algorithmic art Artificial intelligence Astroinformatics Author profiling B Biodiversity informatics Biological computation C Cellular automaton Chaos theory Cheminformatics Code stylometry Community informatics Computable topology Computational aeroacoustics Computational archaeology Computational astrophysics Computational auditory scene analysis Computational biology Computational chemistry Computational cognition Computational complexity theory Computational creativity Computational criminology Computational economics Computational electromagnetics Computational epigenetics Computational epistemology Computational finance Computational fluid dynamics Computational genomics Computational geometry Computational geophysics Computational group theory Computational humor Computational immunology Computational journalism Computational law Computational learning theory Computational lexicology Computational linguistics Computational lithography Computational logic Computational magnetohydrodynamics Computational Materials Science Computational mechanics Computational musicology Computational neurogenetic modeling Computational neuroscience Computational number theory Computational particle physics Computational photography Computational physics Computational science Computational engineering Computational scientist Computational semantics Computational semiotics Computational social science Computational sociology Computational
    [Show full text]
  • Development of Guidance on Ethics and Governance of Artificial Intelligence for Health
    WHO Consultation Towards the Development of guidance on ethics and governance of artificial intelligence for health Geneva, Switzerland, 2–4 October 2019 Meeting report WHO consultation towards the development of guidance on ethics and governance of artificial intelligence for health: meeting report, Geneva, Switzerland, 2–4 October 2019 ISBN 978-92-4-001275-2 (electronic version) ISBN 978-92-4-001276-9 (print version) © World Health Organization 2021 Some rights reserved. This work is available under the Creative Commons Attribution-NonCommercial- ShareAlike 3.0 IGO licence (CC BY-NC-SA 3.0 IGO; https://creativecommons.org/licenses/by-nc- sa/3.0/igo). Under the terms of this licence, you may copy, redistribute and adapt the work for non-commercial purposes, provided the work is appropriately cited, as indicated below. In any use of this work, there should be no suggestion that WHO endorses any specific organization, products or services. The use of the WHO logo is not permitted. If you adapt the work, then you must license your work under the same or equivalent Creative Commons licence. If you create a translation of this work, you should add the following disclaimer along with the suggested citation: “This translation was not created by the World Health Organization (WHO). WHO is not responsible for the content or accuracy of this translation. The original English edition shall be the binding and authentic edition”. Any mediation relating to disputes arising under the licence shall be conducted in accordance with the mediation rules of the World Intellectual Property Organization (http://www.wipo.int/amc/en/mediation/rules/).
    [Show full text]
  • Dmitry Korkin, Ph.D. E-Mail: [email protected] WWW
    Bioinformatics and Computational Biology Program Department of Computer Science Worcester Polytechnic Institute, Worcester, MA Dmitry Korkin, Ph.D. e-mail: [email protected] WWW: http://korkinlab.org Education • Postdoc in Bioinformatics and Computational Biology University of California San Francisco: 2003-2007; Rockefeller University: 2002 Research topic: Structural bioinformatics and systems biology of protein-protein interactions • Ph.D. in Computer Science Faculty of Computer Science, University of New Brunswick, NB, Canada: 2003 Research topic: Machine learning with applications to computer-aided drug design • M.Sc. in Mathematics, Applied Mathematics Faculty of Mechanics and Mathematics, Moscow State University, Moscow, Russia: 1999 Research Topic: Application of information theory to Security Policy • B.Sc. in Mathematics, Applied Mathematics Faculty of Mechanics and Mathematics, Moscow State University, Moscow, Russia: 1997 Academic positions • Director, Bioinformatics and Computational Biology Program 2017-present Worcester Polytechnic Institute, Worcester, MA, USA • Associate Professor in Bioinformatics and Computer Science with tenure 2014–present Dept. of Computer Science and Program in Bioinformatics and Computational Biology Courtesy appointment with Data Science Program and Depts. of Applied Mathematics, Biology and Biotechnology, Worcester Polytechnic Institute, MA, USA • Associate Professor in Bioinformatics and Computer Science with tenure 2013–2014 Dept. of Computer Science and Informatics Institute, University of Missouri-Columbia
    [Show full text]
  • Mobile Communications for Medical Care a Study of Current and Future Healthcare and Health Promotion Applications, and Their Use in China and Elsewhere
    Mobile Communications for Medical Care a study of current and future healthcare and health promotion applications, and their use in China and elsewhere Final Report 21 April 2011 Mobile Communications for Medical Care – Final Report 2 21 April 2011 Mobile Communications for Medical Care a study of current and future healthcare and health promotion applications, and their use in China and elsewhere Final Report 21 April 2011 Contents Executive Summary 5 About the Authors 8 Foreword by China Mobile 9 1. Objectives, Approach and Overview of the mHealth Market 11 2. Overview of Existing Applications of mHealth 19 3. Overview of Potential Next-Generation Applications of mHealth 29 4. Illustrative Business Cases for mHealth Provision 41 5. Realising the Health Benefits to Society 59 6. Deployment of mHealth Applications 69 Special Feature: Summary of Case Studies of mHealth Deployments in China 81 Annexes A mHealth Applications Identified in the Course of the Project 93 B Participants in the Workshop and the Interview Programme 113 References 119 Mobile Communications for Medical Care – Final Report 4 21 April 2011 Mobile Communications for Medical Care – Final Report 5 21 April 2011 Executive Summary This report examines the use of mobile networks to enhance healthcare (so-called “mHealth”), as an example of how mobile communications can contribute to sustainable development. We define mHealth as “a service or application that involves voice or data communication for health purposes between a central point and remote locations. It includes telehealth (or eHealth) applications if delivery over a mobile network adds utility to the application. It also includes the use of mobile phones and other devices as platforms for local health-related purposes as long as there is some use of a network.” Innovative mHealth applications have the potential to transform healthcare in both the developing and the developed world.
    [Show full text]
  • Ability of Influenza Case Detection for Disease Surveillance
    Research Article 560 The effects of natural language pro- cessing on cross-institutional port- ability of influenza case detection for disease surveillance Jeffrey P. Ferraro1,2; Ye Ye3,4; Per H. Gesteland1,5; Peter J. Haug1,2; Fuchiang (Rich) Tsui3,4; Gregory F. Cooper3; Rudy Van Bree2; Tho- mas Ginter6; Andrew J. Nowalk7; Michael Wagner3,4 1Department of Biomedical Informatics, University of Utah, Salt Lake City, Utah, USA; 2Intermountain Healthcare, Salt Lake City, Utah, USA; 3Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania, USA; 4Intelligent Systems Program, University of Pittsburgh, Pittsburgh, Pennsylvania, USA; 5Department of Pediatrics, University of Utah, Salt Lake City, Utah, USA; 6VA Salt Lake City Healthcare System, Salt Lake City, Utah; 7Department of Pediatrics, Children‘s Hospital of Pittsburgh of University of Pittsburgh, Pittsburgh, Pennsylvania, USA Keywords Natural language processing, case detection, disease surveillance, generalizability, portability Summary Objectives: This study evaluates the accuracy and portability of a natural language processing (NLP) tool for extracting clinical findings of influenza from clinical notes across two large health- care systems. Effectiveness is evaluated on how well NLP supports downstream influenza case-de- tection for disease surveillance. Methods: We independently developed two NLP parsers, one at Intermountain Healthcare (IH) in Utah and the other at University of Pittsburgh Medical Center (UPMC) using local clinical notes from emergency department (ED) encounters of influenza. We measured NLP parser performance for the presence and absence of 70 clinical findings indicative of influenza. We then developed Bayesian network models from NLP processed reports and tested their ability to discriminate among cases of (1) influenza, (2) non-influenza influenza-like illness (NI-ILI), and (3) ‘other’ diag- nosis.
    [Show full text]