Hostname: page-component-77c78cf97d-lphnv Total loading time: 0 Render date: 2026-05-03T23:29:24.153Z Has data issue: false hasContentIssue false
  • English
  • Français

A Physician Advisory System for Chronic Heart Failure management based on knowledge patterns

Published online by Cambridge University Press:  14 October 2016

ZHUO CHEN ,
KYLE MARPLE ,
ELMER SALAZAR ,
GOPAL GUPTA  and
LAKSHMAN TAMIL
ZHUO CHEN
Affiliation:
University of Texas at Dallas, Texas, U.S.A. (e-mail: zxc130130@utdallas.edu, kbm072000@utdallas.edu, ees101020@utdallas.edu, gupta@utdallas.edu, laxman@utdallas.edu)
KYLE MARPLE
Affiliation:
University of Texas at Dallas, Texas, U.S.A. (e-mail: zxc130130@utdallas.edu, kbm072000@utdallas.edu, ees101020@utdallas.edu, gupta@utdallas.edu, laxman@utdallas.edu)
ELMER SALAZAR
Affiliation:
University of Texas at Dallas, Texas, U.S.A. (e-mail: zxc130130@utdallas.edu, kbm072000@utdallas.edu, ees101020@utdallas.edu, gupta@utdallas.edu, laxman@utdallas.edu)
GOPAL GUPTA
Affiliation:
University of Texas at Dallas, Texas, U.S.A. (e-mail: zxc130130@utdallas.edu, kbm072000@utdallas.edu, ees101020@utdallas.edu, gupta@utdallas.edu, laxman@utdallas.edu)
LAKSHMAN TAMIL
Affiliation:
University of Texas at Dallas, Texas, U.S.A. (e-mail: zxc130130@utdallas.edu, kbm072000@utdallas.edu, ees101020@utdallas.edu, gupta@utdallas.edu, laxman@utdallas.edu)
Get access Rights & Permissions [Opens in a new window]

Abstract

Management of chronic diseases such as chronic heart failure (CHF) is a major problem in health care. A standard approach followed by the medical community is to have a committee of experts develop guidelines that all physicians should follow. These guidelines typically consist of a series of complex rules that make recommendations based on a patient's information. Due to their complexity, often the guidelines are ignored or not complied with at all. It is not even clear whether it is humanly possible to follow these guidelines due to their length and complexity. For instance, for CHF, the guidelines run nearly eighty pages. In this paper we describe a physician-advisory system for CHF management that codes the entire set of clinical practice guidelines for CHF using answer set programming (ASP). Our approach is based on developing reasoning templates, that we call knowledge patterns, and using them to systemically code the clinical guidelines for CHF as ASP rules. Use of the knowledge patterns greatly facilitates the development of our system. Given a patient's medical information, our system generates a recommendation for treatment just as a human physician would, using the guidelines. Our system works even in the presence of incomplete information.

Keywords

chronic disease managementknowledge patternanswer set programmingknowledge representationautomated reasoning

Information

Type
Regular Papers
Information
Theory and Practice of Logic Programming , Volume 16 , Special Issue 5-6: 32nd International Conference on Logic Programming , September 2016 , pp. 604 - 618
Copyright
Copyright © Cambridge University Press 2016 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Article purchase

Temporarily unavailable

References

Anderson, G. 2004. Chronic conditions: making the case for ongoing care. Johns Hopkins University.Google Scholar
Baldwin, K. M., Black, D. L. and Hammond, S. L. 2013. Hospital-based post-discharge community case management - podium presentation. In ANCC Pathway to Excellence Conference.Google Scholar
Baral, C., 2003. Knowledge Representation, Reasoning and Declarative Problem Solving. Cambridge University Press.CrossRefGoogle Scholar
Brewka, G., Eiter, T. and Truszczynski, M. 2011. Answer set programming at a glance. Commun. ACM 54, 12, 92–103.CrossRefGoogle Scholar
Cabana, M. D., Rand, C. S., Powe, N. R., et al. 1999. Why don't physicians follow clinical practice guidelines?: A framework for improvement. JAMA 282, 15, 1458–1465.CrossRefGoogle ScholarPubMed
Centers for Disease Control and Prevention. 2016. Chronic disease overview page. http://www.cdc.gov/chronicdisease/overview/index.htm.Google Scholar
Faxon, D. P., et al. 2004. Improving quality of care through disease management principles and recommendations from the american heart association's expert panel on disease management. Stroke 35, 6, 1527–1530.CrossRefGoogle Scholar
Gebser, M., Kaufmann, B. and Schaub, T. 2012. Conflict-driven answer set solving: From theory to practice. In Artif. Intell. 187, 52-89.Google Scholar
Gebser, M., Kaminski, , Kaufmann, B. and Schaub, T. 2014. Clingo = ASP + Control: Preliminary Report. In Proc. ICLP 2014 Proc.Google Scholar
Gelfond, M. and Lifschitz, V. 1988. The stable model semantics for logic programming. Proc. ICLP 1988. MIT Press, 1070–1080.Google Scholar
Go, A. S., Mozaffarian, D., Benjamin, E. J., et al. 2013. Heart disease and stroke statistics 2013 update: a report from the american heart association. Tech. rep.Google Scholar
Group, T. M. N. 2006. Enhancing the use of clinical guidelines: a social norms perspective. Journal of the American College of Surgeons 202, 5, 826–836.Google Scholar
Jacobs, A. K., Kushner, F. G., et al. 2013. ACCF/AHA clinical practice guideline methodology summit report: A report of the american college of cardiology foundation/american heart association task force on practice guidelines. Journal of the American College of Cardiology 61, 2, 213–265.CrossRefGoogle Scholar
Jantos, L. D. and Holmes, M. L. 2006. IT Tools for Chronic Disease Management: How Do They Measure Up? California HealthCare Foundation (chfc.org; retrieved Jan. 2016).Google Scholar
Marple, K. and Gupta, G. Goal-directed execution of answer set programs. Proc. PPDP 2012: 35-44CrossRefGoogle Scholar
Marple, K., Salazar, E. and Gupta, G. 2016. s(ASP). https://sourceforge.net/projects/sasp-system/.Google Scholar
Monteiro, S. 2015. An intelligent telemedicine platform with cognitive support for chronic care management. Ph.D. thesis, Quality of Life Technology Lab, UT Dallas.Google Scholar
Monteiro, S., Gupta, G., Nourani, M. and Tamil, L. 2011. Hygeiatel: An intelligent telemedicine system with cognitive support. In Proceedings of the First ACM Workshop on Mobile Systems, Applications, and Services for Healthcare. mHealthSys '11. ACM, New York, NY, USA, 9:1–2.Google Scholar
Wu, S. Y. and Green, A. 2000. Projection of chronic illness prevalence and cost inflation. Santa Monica, CA: RAND Health, 2000.Google Scholar
Yancy, C. W., Jessup, M., Bozkurt, B., et al. 2013. ACCF/AHA guideline for the management of heartfailure: A report of the american college of cardiology foundation/american heart association task force on practice guidelines. Journal of the American College of Cardiology 62, 16, e147.CrossRefGoogle Scholar