Improving High Availability and Reliability of Health Interoperability Systems
The accessibility and availability of patient clinical information are a constant need. The Agency for Interoperation, Diffusion and Archive of Medical Information (AIDA) was then developed to ensure the interoperability among healthcare information systems successfully. AIDA has demonstrated over time the need for greater control over its agents and their activities as the need for monitoring and preventing its machines and agents.
This paper presents monitoring and prevention systems that were developed for machines and agents, which allow not only prevent faults, but also watch and evaluate the behaviour of these components through monitoring dashboards. The Biomedical Multiagent Platform for Interoperability (BMaPI) implemented in Centro Hospitalar do Porto (CHP) revealed provide the necessary data and functionalities capable to manage and to monitor agents’ activities. It was found that the prevention systems identified critical situations successfully, contributing to an increase in the integrity and availability of AIDA implemented in CHP.
KeywordsInteroperability Health Information Systems Monitoring System Fault Forecasting
Unable to display preview. Download preview PDF.
- 1.Duarte, J., Salazar, M., Quintas, C., Santos, M., Neves, J., Abelha, A., Machado, J.: Data quality evaluation of electronic health records in the hospital admission process. In: 2010 IEEE/ACIS 9th International Conference on Computer and Information Science (ICIS), pp. 201–206 (August 2010)Google Scholar
- 3.Miranda, M., Duarte, J., Abelha, A., Machado, J., Neves, J.: Interoperability in healthcare. In: Proceedings of the European Simulation and Modelling Conference (ESM 2010), Hasselt, Belgium (2010)Google Scholar
- 5.Abelha, A., Machado, J., Santos, M., Allegro, S., Rua, F., Paiva, M., Neves, J.: Agency for integration, diffusion and archive of medical information. In: Proceedings of the Second IASTED International Conference-Artificial Intelligence and Applications, Benalmadena, Spain (2002)Google Scholar
- 6.Portela, C.F., Santos, M.F., Silva, Á., Machado, J., Abelha, A.: Enabling a pervasive approach for intelligent decision support in critical health care. In: Cruz-Cunha, M.M., Varajão, J., Powell, P., Martinho, R. (eds.) CENTERIS 2011, Part III. CCIS, vol. 221, pp. 233–243. Springer, Heidelberg (2011)CrossRefGoogle Scholar
- 7.Devaney, G., Lead, W.: Guideline for the use of the modified early warning score (MEWS). Technical report, Outer North East London Community Services (2011)Google Scholar
- 8.Albino, A., Jacinto, V.: Implementação da escala de alerta precoce - EWS. Technical report, Centro Hospitalar do Barlavento Algarvio, EPE, Portimão (2010)Google Scholar
- 9.Silva, P., Quintas, C., Duarte, J., Santos, M., Neves, J., Abelha, A., Machado, J.: Hospital database workload and fault forecasting. In: 2012 IEEE EMBS Conference on Biomedical Engineering and Sciences, Malaysia (2012)Google Scholar
- 10.Boudec, J.: Performance Evaluation of Computer and Communication Systems. Computer and communication sciences. EPFL Press (2010)Google Scholar
- 11.Boshier, A.: Windows Management Instrumentation: A Simple, Powerful Tool for Scripting Windows Management. MSDN Magazine 4 (2000)Google Scholar
- 12.Tereso, M., Bernardino, J.: Open source business intelligence tools for smes. In: 2011 6th Iberian Conference on Information Systems and Technologies (CISTI), pp. 1–4. IEEE (2011)Google Scholar