Advertisement

A Multiagent System Proposal for 30 Day Readmission Problem Management

Conference paper
  • 1.1k Downloads
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 38)

Abstract

Thirty day readmission rate is an important quality estimator for hospitals. Confident tools that forecast this risk for each patient before hospital discharge are needed by medical staff in order to delay the discharge and to plan additional home care interventions. This paper presents a proposal for a multi agent system that will evaluate this risk by integrating information from each patient and historical data from local and remote medical histories. This systems will not only help with the hospital discharge decision, but it will integrate a basic telecare system in order to reduce readmissions and increment patient quality of life by detecting problems arisen after hospital discharge.

Keywords

Multiagent system Learning agents Decision support systems in healthcare Machine learning 

References

  1. 1.
    Jencks, S.F., Williams, M.V., Coleman, E.A.: Rehospitalizations among patients in the Medicare fee-for-service program. N. Engl. J. Med. 360(14), 1418–1428 (2009)CrossRefGoogle Scholar
  2. 2.
    Ben-Chetrit, E., Chen-Shuali, C., Zimran, E., Munter, G., Nesher, G.: A simplified scoring tool for prediction of readmission in elderly patients hospitalized in internal medicine departments. Isr. Med. Assoc. J. 14(12), 752–756 (2012)Google Scholar
  3. 3.
    Medicare Payment Advisory Commission. Report to congress: Medicare and the health care delivery system. Washington, DC: MedPAC (2011). http://www.medpac.gov/documents/jun11_entirereport.pdf
  4. 4.
    United States Congress House. Office of the Legislative Counsel: Compilation of Patient Protection and Affordable Care Act: as amended through Nov 1, 2010 including Patient Protection and Affordable Care Act health-related portions of the Health Care and Education Reconciliation Act of 2010. Washington: U.S: Government Printing Office (2010)Google Scholar
  5. 5.
    Report to Congress: national strategy for quality improvement in health care (2011) http://www.healthcare.gov/news/reports/quality03212011a.html
  6. 6.
    van Walraven, C., Dhalla, I.A., Bell, C., Etchells, E., Stiell, I.G., Zarnke, K., Forster, A.J.: Derivation and validation of an index to predict early death or unplanned readmission after discharge from hospital to the community. Can. Med. Assoc. J. 182(6), 551–557 (2010)CrossRefGoogle Scholar
  7. 7.
    van Walraven, C., Wong, J., Forster, A.J.: LACE+ index: extension of a validated index to predict early death or urgent readmission after hospital discharge using administrative data. Open Med. 6(3), e80 (2012)Google Scholar
  8. 8.
    Amarasingham, R., Moore, B.J., Tabak, Y.P., Drazner, M.H., Clark, C.A., Zhang, S., Halm, E.A.: An automated model to identify heart failure patients at risk for 30-day readmission or death using electronic medical record data. Med. care 48(11), 981–988 (2010)CrossRefGoogle Scholar
  9. 9.
    Berman, K., Tandra, S., Forssell, K., Vuppalanchi, R., Burton, J.R., Nguyen, J., Chalasani, N.: Incidence and predictors of 30-day readmission among patients hospitalized for advanced liver disease. Clin. Gastroenterol. Hepatol. 9(3), 254–259 (2011)CrossRefGoogle Scholar
  10. 10.
    Cotter, P.E., Bhalla, V.K., Wallis, S.J., Biram, R.W.: Predicting readmissions: poor performance of the LACE index in an older UK population. Age Ageing 41(6), 784–789 (2012)CrossRefGoogle Scholar
  11. 11.
    Müller, J.P., Fischer, K.: Application impact of multi-agent systems and technologies: a survey. In: Agent-Oriented Software Engineering, pp. 27–53. Springer, Berlin Heidelberg (2014)Google Scholar
  12. 12.
    Isern, D., Snchez, D., Moreno, A.: Agents applied in health care: a review. Int. J. Med. Informatics 79(3), 145–166 (2010)CrossRefGoogle Scholar
  13. 13.
    Proctor, E.K., Morrow-Howell, N., Li, H., Dore, P.: Adequacy of home care and hospital readmission for elderly congestive heart failure patients. Health Soc. Work 25(2), 87–96 (2000)CrossRefGoogle Scholar
  14. 14.
    Wang, H., Robinson, R.D., Johnson, C., Zenarosa, N.R., Jayswal, R.D., Keithley, J., Delaney, K.A.: Using the LACE index to predict hospital readmissions in congestive heart failure patients. BMC Cardiovasc. Disord. 14(1), 97 (2014)CrossRefGoogle Scholar
  15. 15.
    Tortajada, S., et al.: Incremental gaussian discriminant analysis based on graybill and deal weighted combination of estimators for brain tumour diagnosis. J. Biomed. Inform. 44(4), 677–687 (2011)CrossRefGoogle Scholar
  16. 16.
    Traver, V., Monton, E., Bayo, J.L., Garcia, J.M., Hernandez, J., Guillen, S.: Multiagent home telecare platform for patients with cardiac diseases. In: Computers in Cardiology, pp. 117–120. IEEE (2003)Google Scholar
  17. 17.
    Bellifemine, F.L., Caire, G., Greenwood, D.: Developing multi-agent systems with JADE, vol. 7. John Wiley & Sons (2007)Google Scholar
  18. 18.
    Foundation for Intelligent Physical agent. http://www.fipa.org/
  19. 19.
    Park, L., Andrade, D., Mastey, A., Sun, J., Hicks, L.: Institution specific risk factors for 30 day readmission at a community hospital: a retrospective observational study. BMC Health Serv. Res. 14(1), 40 (2014)CrossRefGoogle Scholar
  20. 20.
    Isern, D., Snchez, D., Moreno, A.: Ontology-driven execution of clinical guidelines. Comput. Methods Programs Biomed. 107(2), 122–139 (2012)CrossRefGoogle Scholar
  21. 21.
    Tortajada, S., et al.: Incremental logistic regression for customizing automatic diagnostic models. In: Fernn-dez-Llatas, C., Garca-Gmez, J.M. (eds.) Data Mining in Clinical Medicine, Methods in Molecular Biology (2014)Google Scholar
  22. 22.
    Sez, C., et al.: Stability metrics for multi-source biomedical data based on simplicial projections from probability distribution distances. In: Statistical Methods in Medicine (2014). doi:  10.1177/0962280214545122

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.DISCA, Universitat Politècnia de ValènciaValenciaSpain
  2. 2.RIS-Itaca, Universitat Politècnia de ValènciaValenciaSpain
  3. 3.DACYA, Universidad Complutense de MadridMadridSpain
  4. 4.IBIME-Itaca, Universitat Politècnia de ValènciaValenciaSpain

Personalised recommendations