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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
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)
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)
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
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)
Report to Congress: national strategy for quality improvement in health care (2011) http://www.healthcare.gov/news/reports/quality03212011a.html
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)
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)
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)
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)
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)
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)
Isern, D., Snchez, D., Moreno, A.: Agents applied in health care: a review. Int. J. Med. Informatics 79(3), 145–166 (2010)
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)
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)
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)
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)
Bellifemine, F.L., Caire, G., Greenwood, D.: Developing multi-agent systems with JADE, vol. 7. John Wiley & Sons (2007)
Foundation for Intelligent Physical agent. http://www.fipa.org/
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)
Isern, D., Snchez, D., Moreno, A.: Ontology-driven execution of clinical guidelines. Comput. Methods Programs Biomed. 107(2), 122–139 (2012)
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)
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
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Mateo Pla, M.A., Zúñiga, L.L., Montañana, J.M., Terol, J.P., Tortajada, S. (2015). A Multiagent System Proposal for 30 Day Readmission Problem Management. In: Jezic, G., Howlett, R., Jain, L. (eds) Agent and Multi-Agent Systems: Technologies and Applications. Smart Innovation, Systems and Technologies, vol 38. Springer, Cham. https://doi.org/10.1007/978-3-319-19728-9_31
Download citation
DOI: https://doi.org/10.1007/978-3-319-19728-9_31
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-19727-2
Online ISBN: 978-3-319-19728-9
eBook Packages: EngineeringEngineering (R0)