Knowledge Representation and Management: Towards Patient Health Self-management

A.-M. Rassinoux; Section Editor for the IMIA Yearbook Section on Knowledge Representation and Management

doi:10.1055/s-0038-1639442

Yearbook of Medical Informatics, Table of Contents

Yearb Med Inform 2012; 21(01): 126-129
DOI: 10.1055/s-0038-1639442

Synopsis

Georg Thieme Verlag KG Stuttgart

Knowledge Representation and Management: Towards Patient Health Self-management

Authors

A.-M. Rassinoux

¹Information Systems Division, Geneva University Hospitals, Geneva, Switzerland

Section Editor for the IMIA Yearbook Section on Knowledge Representation and Management

Abstract

Summary

Objectives

To summarize excellent current research in the field of knowledge representation and management (KRM).

Method

A synopsis of the articles selected for the IMIA Yearbook 2012 is provided and an attempt to highlight the current trends in the field of health management is sketched.

Results

Among the five selected papers, two confirm the benefit of exploiting open-source language toolkits for the automatic extraction of medical concepts, assertions and/or relationships from clinical texts. One paper aims at exploiting domain-specific terminologies to improve the parsing of biomedical noun phrases, and another one aims at discovering rare diseases associations embedded into disparate textual sources. Finally, the last paper describes a collaborative search approach integrated into a homegrown EHR search engine.

Conclusions

This selected set of papers confirms that natural language processing, as well as knowledge extraction, discovering and retrieval, are still active and fruitful research fields. Although these papers are not directly focusing on personal health informatics applications„ important features are highlighted and tailored to fit the requirements of patient health self-management. Delivering timely, friendly and secure access to functional, accurate, up-to-date and sustainable personal health records is a significant challenging task for supporting self-managed healthcare.

Keywords

Open-source language toolkits - Knowledge extraction - discovering and retrieval - Health self-management - Health behavior

Full Text

References

References
1 Bekker H, Thornton JG, Airey CM, Connelly JB, Hewison J. et al. Informed decision making: an annotated bibliography and systematic review. Health Technol Assess 1999; 03 (01) 1-156.
2 Chi EH. Augmented social cognition: Using social web technology to enhance the ability of groups to remember, think, and reason. Proceedings of the 35th SIGMOD international Conference on Management of Data (SIGMOD ‘09). New York: ACM Press; 2009: 973-84.
3 Kaelber DC, Jha AK, Johnston D, Middleton B, Bates DW. A research agenda for personal health records (PHRs). J Am Med Inform Assoc 2008; Nov-Dec; 15 (06) 729-36.
4 Archer N, Fevrier-Thomas U, Lokker C, McKibbon KA, Straus SE. Personal health records: a scoping review. J Am Med Inform Assoc 2011; Jul-Aug; 18 (04) 515-22.
5 Hoerbst A, Ammenwerth E. Electronic health records.A systematic review on quality requirements. Methods Inf Med 2010; 49 (04) 320-36.
6 D’Avolio LW, Nguyen TM, Goryachev S, Fiore LD. Automated concept-level information extraction to reduce the need for custom software and rules development. J Am Med Inform Assoc 2011; Sep-Oct; 18 (05) 607-13.
7 Islamaj RDogan, Névéol A, Lu Z. A context-blocks model for identifying clinical relationships in patient records. BMC Bioinformatics 2011; 12 Suppl (Suppl. 03) S3.
8 I2B2. Informatics for integrating Biology & the Bedside. Available from: http://www.i2b2.org/NLP/ Relations/Main.php
9 Uzuner Ö, South BR, Shen S, DuVall SL. 2010 i2b2/VA challenge on concepts, assertions, and relations in clinical text. J Am Med Inform Assoc 2011; Sep-Oct; 18 (05) 552-6.
10 Savova GK, Masanz JJ, Ogren PV. et al. Mayo clinical Text Analysis and Knowledge Extraction System (cTAKES): architecture, component evaluation and applications. J Am Med Inform Assoc 2010; 17: 507-13.
11 McCallum AK. MALLET: A Machine Learning for Language Toolkit. 2002 [http://mallet. cs.umass.edu]
12 Rassinoux AM. Decision Support, Knowledge Representation and Management: Transforming Textual Information into Useful Knowledge. In: Kulikowski CA, Geissbuhler A, editors. Yearb Med Inform 2010; 64-7.
13 Rassinoux AM. Knowledge Representation and Management: Benefits and Challenges of the Semantic Web for the Fields of KRM and NLP. In: Kulikowski CA, Geissbuhler A. editors. Yearb Med Inform. 2011: 121-4.
14 Clark C, Aberdeen J, Coarr M, Tresner-Kirsch D, Wellner B. et al. MITRE system for clinical assertion status classification. J Am Med Inform Assoc 2011; Sep-Oct; 18 (05) 563-7.
15 Savova G, Bethard S, Styler W. et al. Towards temporal relation discovery from the clinical narrative. AMIA Annu Symp Proc 2009; 2009: 568-72.
16 Fan JW, Friedman C. Deriving a probabilistic syntacto-semantic grammar for biomedicine based on domain-specific terminologies. J Biomed Inform 2011; Oct; 44 (05) 805-14.
17 Holmes AB, Hawson A, Liu F, Friedman C, Khiabanian H, Rabadan R. Discovering disease associations by integrating electronic clinical data and medical literature. PLoS One 2011; 06 (06) e21132.
18 Zheng K, Mei Q, Hanauer DA. Collaborative search in electronic health records. J Am Med Inform Assoc 2011; May; 18 (03) 282-91.
19 Lau AY, Siek KA, Fernandez-Luque L, Tange H, Chhanabhai P. et al. The Role of Social Media for Patients and Consumer Health. Contribution of the IMIA Consumer Health Informatics Working Group. Yearb Med Inform 2011; 131-8.