Healthcare intelligence risk detection systems

Reza Safdari, Jebraeil Farzi, Marjan Ghazisaeidi, Mahboobeh Mirzaee, Azadeh Goodini

Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran.

DOI: 10.4236/ojpm.2013.38062                

Abstract

Background: Today, in healthcare field that is changing rapidly, decision-makers encounter with ever-increasing inquiries on clinical and administrative information to realize customers’ legal and clinical requirements. Therefore, making decisions on healthcare has changed into a vital, complex and unstructured issue. The present paper mainly focuses on describing decision-making advantages, possible risk to improve efficiency of decision-making on healthcare, and especially medical procedures. Methods: The present research is a review study, which has been carried out by searching through the authentic scientific sources, including Pubmed, Google scholar, Iranmedex, and other information sources. While defining care intelligence, here, we introduce Knowledge Discovery Database, the Clinical Support Systems, and Intelligence Risk Detection Model and provide the conceptual model. Other issues studied in this paper include the Risk Possibility Assessment Technique, Risk Possibility Detection using knowledge management techniques, and expert systems. Results & Conclusion: Modeling the Intelligence Support System is necessary for designing Real-Time Risk Detection Information Systems in clinical measures. As taking medical procedures involves complex decision-makings and possibility of high risk, operational application of the techniques derived from knowledge and data mining models under study will play a crucial role in increasing possibility of success of the measure and promoting safety of patients.

Keywords

Risk Detection Systems; Decision

Conflicts of Interest

The authors declare no conflicts of interest.

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