Skip to main content
SpringerLink
Log in

Preliminary Result on Finding Treatments for Patients with Comorbidity

  • Conference paper
  • First Online:
Knowledge Representation for Health Care (KR4HC 2014)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8903))

Abstract

According to some research, comorbidity is reported in 35 to 80 % of all ill people [1]. Multiple guidelines are needed for patients with comorbid diseases. However, it is still a challenging problem to automate the application of multiple guidelines to patients because of redundancy, contraindicated, potentially discordant recommendations. In this paper, we propose a mathematical model for the problem. It formalizes and generalizes a recent approach proposed by Wilk and colleagues. We also demonstrate that our model can be encoded, in a straightforward and simple manner, in Answer Set Programming (ASP) – a class of Knowledge Representation languages. Our preliminary experiment also shows our ASP based implementation is efficient enough to process the examples used in the literature.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 34.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 44.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    Many incompatible sets are known facts are directly from the medical field.

  2. 2.

    They are logically inconsistent.

References

  1. Jakovljević, M., Ostojić, L.: Comorbidity and multimorbidity in medicine today: challenges and opportunities for bringing separated branches of medicine closer to each other. Psychiatr. Danub. 1, 18–28 (2013)

    Google Scholar 

  2. Field, M.J., Lohr, K.N., et al.: Guidelines for Clinical Practice: From Development to Use. National Academies Press, Washington (1992)

    Google Scholar 

  3. Peleg, M., Tu, S., Bury, J., Ciccarese, P., Fox, J., Greenes, R.A., Hall, R., Johnson, P.D., Jones, N., Kumar, A., et al.: Comparing computer-interpretable guideline models: a case-study approach. J. Am. Med. Inf. Assoc. 10(1), 52–68 (2003)

    Article  Google Scholar 

  4. de Clercq, P.A., Blom, J.A., Korsten, H.H., Hasman, A.: Approaches for creating computer-interpretable guidelines that facilitate decision support. Artif. Intell. Med. 31(1), 1–27 (2004)

    Article  Google Scholar 

  5. Isern, D., Moreno, A.: Computer-based execution of clinical guidelines: a review. Int. J. Med. Inf. 77(12), 787–808 (2008)

    Article  Google Scholar 

  6. Boyd, C.M., Darer, J., Boult, C., Fried, L.P., Boult, L., Wu, A.W.: Clinical practice guidelines and quality of care for older patients with multiple comorbid diseases. JAMA J. Am. Med. Assoc. 294(6), 716–724 (2005)

    Article  Google Scholar 

  7. Sittig, D.F., Wright, A., Osheroff, J.A., Middleton, B., Teich, J.M., Ash, J.S., Campbell, E., Bates, D.W.: Grand challenges in clinical decision support. J. Biomed. Inf. 41(2), 387–392 (2008)

    Article  Google Scholar 

  8. Real, F., Riaño, D.: An autonomous algorithm for generating and merging clinical algorithms. In: Riaño, D. (ed.) K4HelP 2008. LNCS, vol. 5626, pp. 13–24. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  9. Abidi, S.R., Abidi, S.S.R.: Towards the merging of multiple clinical protocols and guidelines via ontology-driven modeling. In: Combi, C., Shahar, Y., Abu-Hanna, A. (eds.) AIME 2009. LNCS, vol. 5651, pp. 81–85. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  10. Wilk, S., Michalowski, W., Michalowski, M., Farion, K., Hing, M.M., Mohapatra, S., et al.: Mitigation of adverse interactions in pairs of clinical practice guidelines using constraint logic programming. J. Biomed. Inf. 46(2), 341–353 (2013)

    Article  Google Scholar 

  11. Michalowski, M., Mainegra Hing, M., Wilk, S., Michalowski, W., Farion, K.: A constraint logic programming approach to identifying inconsistencies in clinical practice guidelines for patients with comorbidity. In: Peleg, M., Lavrač, N., Combi, C. (eds.) AIME 2011. LNCS, vol. 6747, pp. 296–301. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  12. Wilk, S., Michalowski, M., Michalowski, W., Hing, M.M., Farion, K.: Reconciling pairs of concurrently used clinical practice guidelines using constraint logic programming. In: AMIA Annual Symposium Proceedings. American Medical Informatics Association, vol. 2011, p. 944 (2011)

    Google Scholar 

  13. McCarthy, J.: Elaboration tolerance. In: Common Sense, vol. 98, Citeseer (1998)

    Google Scholar 

  14. Gelfond, M., Kahl, Y.: Knowledge Representation, Reasoning, and the Design of Intelligent Agents. Manuscript (2013)

    Google Scholar 

  15. Faber, W., Pfeifer, G., Leone, N., Dell’armi, T., Ielpa, G.: Design and implementation of aggregate functions in the dlv system. Theory. Pract. Log. Program. 8(5–6), 545–580 (2008)

    Article  MATH  MathSciNet  Google Scholar 

  16. Gebser, M., Kaufmann, B., Schaub, T.: Conflict-driven answer set solving: from theory to practice. Artif. Intell. 187–188, 52–89 (2012)

    Article  MathSciNet  Google Scholar 

  17. Tu, S.W., Campbell, J.R., Glasgow, J., Nyman, M.A., McClure, R., McClay, J., Parker, C., Hrabak, K.M., Berg, D., Weida, T., et al.: The sage guideline model: achievements and overview. J. Am. Med. Inf. Assoc. 14(5), 589–598 (2007)

    Article  Google Scholar 

  18. Gelfond, M., Lifschitz, V.: The stable model semantics for logic programming. In: Proceedings of ICLP-88, pp. 1070–1080 (1988)

    Google Scholar 

  19. Mileo, A., Merico, D., Pinardi, S., Bisiani, R.: A logical approach to home healthcare with intelligent sensor-network support. Comput. J. 53(8), 1257–1276 (2010)

    Article  Google Scholar 

  20. Nogueira, M., Balduccini, M., Gelfond, M., Watson, R., Barry, M.: An A-Prolog decision support system for the Space Shuttle. In: Provetti, A., Son, T.C. (eds.) Answer Set Programming: Towards Efficient and Scalable Knowledge Representation and Reasoning. AAAI 2001 Spring Symposium Series, March 2001

    Google Scholar 

  21. Baral, C.: Knowledge Representation, Reasoning, and Declarative Problem Solving. Cambridge University Press, Cambridge (2003)

    Book  MATH  Google Scholar 

  22. Riaño, D., Collado, A.: Model-based combination of treatments for the management of chronic comorbid patients. In: Peek, N., Marín Morales, R., Peleg, M. (eds.) AIME 2013. LNCS, vol. 7885, pp. 11–16. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  23. López-Vallverdú, J.A., Riaño, D., Collado, A.: Rule-based combination of comorbid treatments for chronic diseases applied to hypertension, diabetes mellitus and heart failure. In: Lenz, R., Miksch, S., Peleg, M., Reichert, M., Riaño, D., ten Teije, A. (eds.) ProHealth 2012 and KR4HC 2012. LNCS, vol. 7738, pp. 30–41. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

Download references

Acknowlegment

We would like to thank Michael Gelfond and Samson Tu for discussions on this subject. Yuanlin Zhang’s work is partially supported by the NSF grants IIS-1018031 and CNS-1359359. Zhizheng Zhang’s work is partially supported by Project 60803061 and 61272378 sponsored by National Natural Science Foundation of China, and Project BK2008293 by Natural Science Foundation of Jiangsu.

Author information

Authors and Affiliations

  1. Texas Tech University, Lubbock, USA

    Yuanlin Zhang

  2. Southeast University, Nanjing, China

    Zhizheng Zhang

Authors
  1. Yuanlin Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Zhizheng Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yuanlin Zhang .

Editor information

Editors and Affiliations

  1. Vienna University of Technology, Vienna, Austria

    Silvia Miksch

  2. Universitat Rovira i Virgili, Tarragona, Spain

    David Riaño

  3. Vrije Universiteit Amsterdam, Amsterdam, The Netherlands

    Annette ten Teije

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Zhang, Y., Zhang, Z. (2014). Preliminary Result on Finding Treatments for Patients with Comorbidity. In: Miksch, S., Riaño, D., ten Teije, A. (eds) Knowledge Representation for Health Care. KR4HC 2014. Lecture Notes in Computer Science(), vol 8903. Springer, Cham. https://doi.org/10.1007/978-3-319-13281-5_2

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-13281-5_2

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-13280-8

  • Online ISBN: 978-3-319-13281-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation